remote sensing in soil science
TRANSCRIPT
Developments in Soil Science 15
REMOTE SENSING IN SOIL SCIENCE
Further Titles in this Series
1 . I . V A L E T O N BAUXITES
2. I A H R FUNDAMENTALS O F TRANSPORT PHENOMENA IN POROUS MEDIA
3. F.E. ALLISON SOIL ORGANIC MATTER AND ITS ROLE IN CROP PRODUCTION
4. R. W. SIMONSON (Editor)
5 A . G.H. B O L T and M.G.M. BRUGGENWERT (Editors)
5B. G.H. BOLT (Editor)
6. H.E. DREGNE
NON-AGRICULTURAL APPLICATIONS O F SOIL SURVEYS
SOIL CHEMISTRY. A. BASIC ELEMENTS
SOIL CHEMISTRY. B. PHYSICO-CHEMICAL MODELS
SOILS O F ARID REGIONS
7. H. A U B E R T and M. PINTA TRACE ELEMENTS IN SOILS
8. M. SCHNITZER and S. U. K H A N (Editors) SOIL ORGANIC MATTER
9. B.K.G. THENG FORMATION AND PROPERTIES OF CLAY-POLYMER COMPLEXES
10. D. Z A C H A R SOIL EROSION
11A. L.P. WILDING, N.E. SMECK and G.F. H A L L (Editors) PEDOGENESIS AND SOIL TAXONOMY. I. CONCEPTS AND INTERACTIONS
1 IB. L.P. WILDING, N.E. SMECK and G.F. H A L L (Editors) PEDOGENESIS AND SOIL TAXONOMY. 11. THE SOIL ORDERS 12. E.B.A. BISDOM and J . DUCLOUX (Editors) SUBMICROSCOPIC STUDIES O F SOILS
13. P. K O O R E V A A R , G . MENELIK and C. DIRKSEN ELEMENTS OF SOIL PHYSICS
14. G.S. CAMPBELL SOIL PHYSICS WITH BASIC -- TRANSPORT MODELS FOR SOIL-PLANT SYSTEMS
Developments in Soil Science 15
REMOTE SENSING IN SOIL SCIENCE
M.A. MULDERS
Department of Soil Science and Geology, Agricultural University of Wageningen, P.O. Box 37, Wageningen, The Netherlands
ELSEVIER - Amsterdam - Oxford - New York -Tokyo 1987
ELSEVIER SCIENCE PUBLISHERS B.V. Sara Burgerhartstraat 25 P.O. Box 211, 1000 AE Amsterdam, The Netherlands
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ELSEVIER SCIENCE PUBLISHING COMPANY INC. 52, Vanderbilt Avenue New York, NY 10017, U.S.A.
Lihrary of Cnngcss CataloginginPublication Data
Mulders , Michel Adrianus, 1941- Renote sens ing i n s o i l sc ience .
(Developments i n s o i l s c i e t x e ; 1:) Includes b: i i icgraphies and index. 1. S o i l science--Renote sens ing . I . T i t l e .
11. S e r i e s . f 5 C . .135.Md 19:'i i 31.4 'CLi '7 57-54,3 ISBN 0-444-4,713-X
ISBN 0-444-42783-X (Vol. 15) ISBN 0-444-40882-7 (Series)
0 Elsevier Science Publishers B.V., 1987
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Printed in The Netherlands
V
PREFACE
The soil scientist is involved in the study of environment since the
environmental conditions have to be evaluated for their impact on soil
formation. However, it may be that the impact of past environmental conditions
has been of even more importance on soil morphology than the present
conditions. Therefore geo- and morphogenesis form also part of his field of
study.
His subject of interest is often not visible. In areas covered by vegetation,
he has to use combinations of aspects such as natural vegetation or land use
and relief to find a clue to the geographical extension of soil bodies.
The combinations are not f i x e d but depend on the type of landscape. For
example, vegetation may be the effect of human interference and may not at all
offer a clue to soil condition.
Scientists involved in geographical distribution of soil, especially in medium
and small scale surveys, obtain much profit of remote sensing techniques
because they offer an overview over large areas and make the study of various
landscape elements individually as well as their interrelationship possible.
During the past decade, remote sensing techniques developed rather fast.
Therefore, it is possible that a soil surveyor becomes old-fashioned by not
knowing the potential use of modern techniques.
This book is dealing with remote sensing techniques and their application
in the field of soil science. It may be used by students and scientists in
soil science, geography, geology, hydrology, ecology, agriculture and civil
engineering. Basic knowledge of soils, geomorphology, geology and physics will
provide useful background.
The reader is stepwise introduced to remote sensing by the following subjects:
- basic physics concerning the interaction of electromagnetic radiation with matter (chapter 2);
- spectral data of soils, rocks and plants (chapter 3) as a transition of
chapter 2 to chapters 9, 10 and 11;
- technical aspects (chapters 4 , 5, 6 and 7 ) ;
- interpretation of remote sensing data (chapters 8, 9, 11, 12 and 13).
A guide for reading is presented in the following scheme:
VI
Subjec t
Phys ica l a s p e c t s
Chapters
s o l a r r a d i a t i o n
i n t e r a c t i o n p rocesses
Future p rospec t s 14
The purpose of t h e hook i s t o p r e s e n t , bes ides remote s e n s i n g techniques and
a p p l i c a t i o n , i n t e r p r e t a t i o n methods a s wel l as most of t h e b a s i c parameters
u sab le f o r model l ing of t h e i n t e r a c t i o n .
ACKNOIJLEDCEHENTS
The wide range of techniques and a p p l i c a t i o n s made i t necessary t o d i s c u s s
v a r i o u s t o p i c s with s p e c i a l i s t s . Thanks a r e due f o r d i s c u s s i o n on p a r t s o f t h e
manuscr ip t t o s e v e r a l Dutch co l l eages .
The au tho r f e e l s g r e a t l y indehted t o D r . K. Schurer , Ir . L. Routen, Ir. J . H .
Loedeman, Ir. E.P.IJ. Attema, Ir. J .T . van d e r Veer, D r . 1 r . 14. t e n Rerge, D r s .
G.F. Epema and Ir. R . Jordens f o r t h e i r sugges t ive c r i t i c i s m .
Acknowledgement i s made t o co-opera tors of t h e Department of f i e l d c rops and
g ras s l and s c i e n c e of t h e A g r i c u l t u r a l Un ive r s i ty Wageningen f o r t h e v a l u a b l e
in fo rma t ion , they provided on s o i l c o n d i t i o n and f i e l d c rops i n t h e i r expe r i -
mental f i e l d s . However my g r e a t e s t debt of g r a t i t u d e i s t o Prof . D r . I r . J.
Rennema ( -t ) f o r h i s encouragement and i n i t i a t i v e f o r s t a r t i n g up t h i s book-
p r o j e c t . The l i n g u i s t i c a b i l i t i e s of Drs. J . M . de Zwart have been of
cons ide rab le va lue f o r a c o r r e c t p r e s e n t a t i o n of t h e Engl i sh t e x t . I ' m indebted
t o Mw. Th. van Hummel-Mom and Mw. M.H. van Eldik-v. Mi l tenhurg of t h e Depart-
ment of s o i l s c i ence and geology of t h e A g r i c u l t u r a l Un ive r s i ty TJageningen f o r
type-wr i t ing t h e manuscr ip t and t o Mr. P.G.M. Versteep,, Hr. G . Ruurman and Hr.
O.D. Jeronimus of t h e sane department f o r performing t h e drawings.
VII
CONTENTS
PREFACE ACKNOWLEDGEMENTS 1. INTRODUCTION
1.1. Remote sensing 1.2. Concept of soil 1.3. Soil mapping 1.4. Remote sensing in soil science 1.5. Conclusions 1.6. References 1.7. Additional reading
2. INTERACTION OF ELECTROMAGNETIC RADIATION WITH MATTER 2.1. The nature of electromagnetic radiation 2.2. Radiation laws 2.3. Solar irriadiance and earth emittance 2.4. Concepts of matter 2.5. Atomic-molecular effects on the interaction process;
polarization, dielectric constant, refractive index and absorption factor
description using the wave model of EMR 2.6. Macroscopic effects on the interaction process; a
2.7. Thermal properties 2.8. Atmospheric effect on EMR 2.9. Energy balance 2.10. Spectral reflectance 2.11. Conclusions 2.12. References 2.13. Additional reading
3. DATA ON INTERACTION OF SHORT WAVE RADIATION WITH NATURAL
3.1. Interaction of short wave radiation with minerals OBJECTS
and rocks Spectral reflectance Spectral emissivity
Spectral reflectance Thermal data
Spectral reflectance Thermal properties
3.2. Interaction of short wave radiation with soils
3.3. Interaction of short wave radiation with plants
3.4. Implications for remote sensing 3.5. Conclusions 3.6. References 3.7. Additional reading
4. DETECTION OF ELECTROMAGNETIC RADIATION 4.1. Human vision 4.2. Photographic techniques 4.3. Non-photographic techniques 4.4. Remote sensing from various platforms 4.5. The nature of remote sensing data 4.6. Ground-investigations 4.7. Conclusions
PAGES
1-11 1-4 4-5 5-8 8-10 11 11 11
12-54 12-16 16-18 18 19-22
22-26
26-36 36-40 40-45 45-48 48-50 50-52 52-53 53-54
55-91
55-60 55-58 58-60 60-75 60-69 69-75 75-86 75-83 83-86 86-87 87-88 88-90 90-91
93-124 93-101 101-109 109-112 112-1 15 115-117 117-121 12 1-1 22
VIII
4.8. References 4.9. Add i t iona l r ead ing
5. PROCESSING OF REMOTE SENSING DATA AND AUTOMATED CLASSIFICATION 5.1. Technica l a s p e c t s i n p rocess ing of photographic imagery 5.2. P rocess ing of d i g i t a l d a t a 5.3. In format ion e x t r a c t i o n p rocess 5.4. Automated c l a s s i f i c a t i o n 5.5. Geometrical a s p e c t s 5.6. Conclusions 5.7. References 5.8. Addi t iona l r ead ing
122-123 123-124
6 . IMAGE 6.1. 6.2. 6.3. 6.4. 6.5. 6.6. 6 .7 . 6.8.
CHARACTERISTICS Reso lu t ion and scale Grey tone , c o n t r a s t and co lou r Airphotos Images de r ived from l ine-scanning dev ices Image-enhancement Conclusions References Addi t iona l r ead ing
7. AERIAL PHOTOGRAPHY 7.1. General a s p e c t s 7.2. S te reoscopy 7 .3 Aerial mapping cameras 7.4. Photomosaics, o r thophotographs and s t e r e o t r i p l e t s 7.5. Requirements f o r a e r i a l su rvey 7.6. True co lou r a e r i a l photography 7.7. I n f r a r e d a e r i a l photography 7.8. M u l t i s p e c t r a l a e r i a l photography 7.9. U l t r a v i o l e t photography 7.10. Conclusions 7.11. References 7.12. Add i t iona l r ead ing
8. GENERAL DIRECTIONS FOR PHYSIOGRAPHIC INTERPRETATION OF REMOTE SENSING IMAGERY I N S O I L MAPPING
8.1. Methods of image- in t e rp re t a t ion 8.2. Landtypes 8 . 3 . R e l i e f , s l o p e and s i t e 8.4. Na tu ra l d ra inage p a t t e r n s 8.5. Na tu ra l v e g e t a t i o n 8.6. Land use , c rops and p a r c e l l i n g 8.7. Drainage c o n d i t i o n 8.8. Other a s p e c t s 8.9. Conclusions 8.10. References 8.11. Addi t iona l r ead ing
9 . INTERPRETATION OF AIRPHOTOS FOR SOIL MAPPING AND LAND EVALUATIOfi
9.1. I n t e r p r e t a t i o n of black-and-white a i r p h o t o s 9.2. The legend of t h e a i r p h o t o - i n t e r p r e t a t i o n map 9.3. From a i r p h o t o - i n t e r p r e t a t i o n map.to s o i l map
125-140 125-131 131-1 35 135-136 136-138 138 138- 139 139-140 140
1 4 1-1 5 4 141-1 4 3 143-144 144-148 148-151 151-153 153-1 54 154 154
155- 180 155-16 2 162-167 167-171 172 172-174 174-1 76 176-177 177-1 7 8 178 178- 179 179-180 1 80
i x i - z i n 182-186 186-18R 188- 192 192-200 2nn-20 3 20 3- 20 5 20 5 206-208 209 209 210
211-245 211-219 219-222 223-2 26
IX
9.4. 9.5. 9.6. 9.7. 9.8. 9.9. 9.10. 9.11. 9.12.
Land evaluation and planning of field survey Interpretation of true COlOUK airphotos Interpretation of black-and-white Infrared airphotos Interpretation of false colour airphotos Application of multispectral photography Interpretation of sequential aerial photography Conclusions References Additional reading
10. AIRBORNE LINE-SCANNING IN THE 0.3 - 8 um ZONE 10.1. Airborne line-scanners 10.2. Detection in the Ultraviolet 10.3. Detection in the Visible zone and near Infrared 10.4. Detection in the mid Infrared 10.5. Conclusions 10.6. References 10.7. Additional reading
11. REMOTE SENSIITG FROM SPACE IN THE 0.3 - 3 pm ZONE 11.1 Manned space missions and unmanned satellites 11.2. Technical aspects Landsat 11.3. Annotations Landsat MSS imagery 11.4. Processing and interpretation of Landsat MSS data. 11.5. Interpretation of Thematic Mapper (TM) data 11.6. Application 11.7. Conclusions and comments 11.8. References 11.9. Additional reading
12. THERMAL INFRARED LINE-SCANNING AND RADIOMETRY IN THE INFRARED AND MICRC-WAVE ZONES 12.1. Airborne Infrared line-scanners and Infrared imagers 12.2. Satellite programs 12.3. Characteristics of airborne thermal Infrared imagery 12.4. Thermal models 12.5. Interpretation of thermal data 12.6. Application of thermal Infrared line scanning. 12.7. Non-imaging sensing in the Infrared and passive
12.8. Conclusions 12.9. References 12.10 Additional reading
Microwave sensing
13. ACTIVE SENSOR SYSTEMS 13.1. Laser systems 13.2. Radar systems 13.3. Interaction of Microwaves with objects at the earth
surf ace Surface roughness Slope /orient at ion Dielectric properties Determination of soil moisture
13.4. Ground penetrating radar 13.5. Vegetation backscattering 13.6. Radar image characteristics
226-235 235 235 236-239 239-240 240-24 1 241-242 24 2-24 3 243-245
246-255 246-248 248-249 249-253 253 253 254 254-255
256-287 256-258 258-264 264-266 266-281 28 1-284
284-285 285-287 28 7
284
288-314 289 289-291 291-295 295-300 300-305 305-306
306-309
309-31 1 309
311-313
314-354 3 14-3 15 315-323
323-332 323-324 325 325-329 329-332 332- 3 34 334-33 5 3 35- 339
X
13.7. Interpretation of radar imagery 13.8 Remote sensing with radio waves 13.9 . Applications and future developments 13.10 Conclusions 13.11 References 13 .12 Additional reading
14 . IMPLICATIONS OF REMOTE SENSING 14.1 . Summary on applications 14 .2 . Land evaluation 14.3 . Methodology 14.4 . Recent and future developments 14 .5 . Political and legal considerations 14.6 . Education and training 14 .7 . References 14.8. Additional reading
Plates 1 - 5 Abbreviations, symbols, units of measure INDEX
339-346 347-348 348-350 350-351 351-353 353-354
355-370 355-356 356-357 357-360 360-366 366-367 367-369 369-370 370
37 1-373 374-375 37 6- 3 7 9
1
1. INTRODUCTIOIJ
Ry way of an introduction, the meaning of the term remote sensing and the
concepts of soil are discussed. The role of remote sensing in soil science is
a logical consequence of these concepts.
1.1. Remote sensing
Remote sensing OK teledetection (French: t616dGtection), sensu strict0
means sensing from a distance, whereby the distance itself is not defined.
A well-known form of remote sensing is the use of OUK senses. An example
of a sensing mechanism, OK sensor. is the eye, which is sensitive to solar
radiation of a particular wavelength. Looking at an object means sensing the
light reflected by that object. The signals are translated into object
characteristics (recognition) and into distance. In Order to reduce the
in'tensity of strong sunlight we can use filters (e.g. sunglasses). Defects of
the eye may be corrected by the use of optical lenses, while we can observe at
a far distance with the aid of binoculars.
As stated before, the distance itself is not defined, therefore, X-ray
machines collecting information from a very short distance as well as radar
operating from a l o n g distance can be regarded as remote sensing means. In
engineering, a measuring device which collects signals at one place, these
being displayed at another place by using radiocommunication, is called a
remote sensing unit.
In the present text, a remote sensor, is defined as a device collecting
data from a distance that varies from a few metres to hundreds of kilometres.
The data may be kept in a storable form (e.g. aerial photographs, magnetic
tapes etc). In contrast to our memory, which is not capable of exactly
recalling past scenery, the stored information enables the user to look
simultaneously at various recordings of the scenery of a specific place but
recorded at different times.
Remote sensing may be executed in various ways, using Electromagnetic
Radiation (EMR), soundwaves OK gravity forces. An important part of remote
sensing belongs to the field of study of the geophysicians.
For remote sensing of the environment there are three basic aspects:
- the physical aspects related to the interaction of EMR with objects or
features at the earth surface resulting in specific data which can be
2
used for recognition and identification of these objects and features,
- the morphographic and physiographic aspects related to the appearance of
the environment on remote sensing imagery enahling identification and
description of objects and features which may be used for a subdivision
of land in land-units,
- the morphogenetic aspects related to the appearance of the environment
and the processes that have shaped the land-units (landscape genesis).
If radiation of wavelengths outside the Visible zone of the
Electromagnetic Spectrum (EMS) is used, and as a consequence the image is not
familiar to the human eye, physical aspects will become more important.
For soil science, we focus in this text on remote sensing by Em. The
systems used f o r remote sensing may be passive when the EMR available in
nature is used, o r active when the EMR has to be supplied for remote
detection. Various stations are used for remote sensing of the earth (see par.
4 . 4 ) , like groundborne platforms (e.g. towers), airborne platforms (e.g.
aircraft) and spaceborne platforms (e.g. satellites). The wavelength zones of
the EMS normally used for remote sensing may vary from the Visible, the Near
Infrared, the Far Infrared (e.g. thermal infrared) to that of the Microwaves
(see par. 2.1). An active system using Microwaves is radar (chapter 13).
Remote sensing is not a new science, since one of the techniques, aerial
photography, has been used for decades. The first aerial photographs were
taken from balloons, around 1850 (De Breuck en Daels, 1967).
During the Second World War, considerable experience was gained in
interpreting airphotos for military purposes. The so-called false COlOUK-fflm
was invented for the detection of green painted camouflaged tanks and
artillery of the enemy. A t present airphoto-interpretation is an important aid
for mapping the natural environment, in particular in less-developed countries
and more generally in areas having a low population density. Besides mapping,
the modern and more sophisticated techniques of remote sensing are making a
number of interesting other applications possible. They may expand our "view"
by the use of various devices as well as by the use o f different wavelength
zones throughout the EMS. Moreover, a relatively accurate view may be obtained
through the application of spectral signatures in combination with shape,
size, grade, density and site as diagnostic characteristics of objects and
features.
Typical for remote sensing research is the multiconcept, which comprises
the following:
3
multispectral (or multiband) observation, which is the observation in
different wavebands enabling a spectral signature of objects;
multistation, which is the observation from different stations at the
same altitude (stereosco.py) or different altitudes (multistage with
different scaies);
multipolarized observation used for the study of polarizing properties of
objects;
multidate (OK multitemporal) observation, which is the observation of the
same area or object at different times e.g. in different seasons; in this
manner, dynamic features like soil moisture and plant growth can be
monitored in the areas under consideration;
multi-enhancement or the enhancement of imagery derived from digital
processing or photographic recording.
The extensive application of remote sensing techniques for military
purposes is linked to the advantages of radar and 'thermal' scanning in
nighttime operations and the use of satellites for detection from out of
space. Automatic data acquisition has a high priority as a result of the large
amount of data to be gathered and processed, and the fact that the information
usually has to be available at the shortest possible notice.
The difficulties encountered in inventoring and monitoring the natural
environment are generally of a more complex nature than those encountered in
the military field.
Environmental studies are concerned with the identification and understanding
of a large variety of natural features and dynamic processes, which are often
interrelated in a very complex way. By using remote sensing techniques, we are
able to study the interrelations and interactions fixed in the images. The
interpretation of these images, often in close cooperation with other
disciplines in order to reveal the underlying basic processes and relation-
ships, will enable us to control and ameliorate the use of the environment.
The application of modern remote sensing techniques and physics in
environmental sciences is not an easy task. Once a certain technique is
accepted, the use of it might become a habit and only reluctantly will it be
replaced. On the other hand scientists might become so mesmerized by the
possibilities of modern remote sensing that they tend to forget the
established values of the older techniques.
4
It is regrettable to state that some of the remote sensing techniques are
still in a juvenile stage as regards their methodology, despite the expected
potentialities. Therefore in order to avoid disappointment during this stage
of the development of remote sensing, it is essential to indicate with care
the best-fitted and proven remote sensing technique for a particular
environmental study.
1.2. Concept of soil
The Russian and American concepts of soil are briefly discussed below.
The Russian school developed the following concept of soil: Soils are natural
bodies, each with a unique morphology resulting from a unique combination of
climate, living matter, earthy parent materials, relief and age of landform.
The morphology of each soil, as expressed by a vertical section through the
differing horizons, reflects the combined effects of the particular set of
genetic factors responsible for its development (Glinka, 1927).
Soil as defined in the U.S. Soil Taxonomy (Soil Survey Staff, 1975) is
"the collection of natural soil bodies on the earth's surface, in places
modified or even made by man of earthy materials, containing living matter and
supporting, or capable of supporting, plants out-of-doors". Soil according to
this definition does not need to have discernible horizons, although the
presence or absence of horizons and their nature is of extreme importance to
its classification. Soils have many properties that fluctuate with the seasons
like temperature, moisture and biologic regimes.
The smallest unit of soil is a pedon. It has three dimensions. Its lower limit
is the often vague limit between the soil and "not soil" below. Its lateral
dimensions are large enough to represent the nature of any horizon and
variability that may be present. In practice, the lateral dimensions have to
be determined by examination of trenches or digging with a spade or by
augering at frequent intervals.
The pedon is usually too small to be a practical mapping unit in soil
surveys. A larger unit is needed, a combination of pedons or a polypedon,
which occurs as a landscape component or natural soil body. This unit is then
a mappable feature distinguished from its surroundings on the basis of
discriminating criteria, which may be parent material, age of landform, relief
and other soil forming factors. According to the U.S. Soil Taxonomy,
differences between polypedons may be related to the nature and arrangement of
horizons or the soil as a whole e.g. differences in mineralogy, structure,
5
consistence, texture of subhorizons and moisture regime. Between natural soil
bodies there can be transitional zones e.g. horizons can become thinner at
places and properties can change gradually. This is illustrated in fig. 1.1.
In large-scale soil mapping (par. 1.3), it is often possible to present
exact soil boundaries. In medium-scale soil mapping, the boundaries are
normally indicated in the centre of transitional zones or complexes of
polypedons are presented on the map.
1.3. Soil Mapping
A systematic soil survey comprises the mapping of individual soil units
or polypedons. The maps can be used in the planning of many different forms of
land-use and management practices. Basic data of this nature are of particular
value in less developed countries in order to make a prediction of the most
desirable form of land-use.
A systematic soil survey usually involves airphoto-interpretation
combined with systematic field checking on the nature and homogeneity of the
soil units.
Generally, the upper metre of soil is described. During the course of the
survey, the establishment of the diagnostic criteria of each uniL and a
continued refinement of the mapping legend takes place. If necessary, specific
field investigations (deep augerings, up to 4 or 5 m) are initiated.
Furthermore, in order to improve the field-observations, soil sampling for
laboratory analysis is carried out, so that earlier estimates can be adjusted,
resulting in more reliable future estimates. However, the field-observations
are the main bases of soil mapping, since cost is often the limiting factor
with regard to laboratory analysis.
The kind of information collected by fieldchecks and additional
laboratory analysis during the soil survey usually depends on the purpose of
the survey. A survey conducted for multiple goals requires information on a
broad scale, while for a limited, well-defined aim, only information on a few
characteristics of the soils is wanted.
According to the Soil Survey Manual (Soil Survey Staff, 1951), a soil map
is a map designed to show the distribution of soil types or other soil mapping
units in relation to other prominent physical and cultural features of the
earth's surface. From a comprehensive soil map, a series of interpretation
maps may be derived, showing for example: the suitability of soils for certain
6
Fig. 1.1 Example of a natural soil body assemblage. X soils of the foot slope Y soils of the slope Z soils of the plateau transitional so i l s X I , Z' with many properties of X or Z polypedons respectively XY, YZ with properties of X and Y, and Y and Z polypedons
indications: - - minor boundary of polypedons -- major boundary of polypedons u V U brown or red mottles -- - - - grey soil matrix due to presence of groundwater
respectively
-- ----
crops, the erosion hazards under defined classes of management, drainage
requirements for an optimum production, or the irrigation potentialities of
the area.
The optimum scale of the soil survey depends on a number of factors (see
Soil Survey Staff, 1 9 5 1 ) :
I
- the purpose to be served;
- the intensity of land use;
- the pattern of soils;
- the scale of remote sensing imagery and other cartographic materials
available.
The pattern of soils may be so dense that the distribution of soils can only
be shown accurately on large-scale maps (e.g. 1:10,000 or 1:5,000). However,
often a scale of 1:20,000 is sufficient.
Difference is made between the scale of field mapping and the publication
scale. The former is often reduced two or three times to the publication
scale. The minimum dimensions of units that can be shown on the publication
map may be given as follows:
-
- 2 mm diameter for elongated forms.
Those units that are too small for presentation on the final map can be
described under associated soils. To obtain a broad idea about the amount of
augerings needed at a certain publication scale, the following rule can be
applied. If aided by remote-sensing-means, it is necessary to have 1-3
augering(s) per cm2 map area at publication scale. The exact amount is
determined by landscape complexity within the limits given. Besides augerings,
there are profile descriptions of soil pits, laboratory analyses, physical
field-data, deep augerings and observations with regard to parent material,
slope and topographic position, which present further evidence on soil
properties and soil geography.
25 mm2 for rounded or square forms;
There is no generally accepted classification of scales. The following
classes are proposed:
detailed 1:lO.OOO scale and larger
semi-detailed smaller than 1:lO.OOO up large-scale
to 1:25.000 scale
medium-scale reconnaissance smaller than 1:25.000 up
(medium intensity) to 1:lOO.OOO scale
reconnaissance smaller than 1:lOO.OOO
(low intensity) up to 1:250.000 scale
exploratory smaller than 1 : 250 .OOO
up to 1:500.000 scale
8
schematic smaller than 1:500.000 scale
The presentation of soil maps is largely dependent on scale. At a large-
scale, taxonomic units and phases are generally preferred. At a small-scale, a
physiographic entry may give more direct information as well as contrasts
among regions so that broad areas can be viewed as a whole.
In most less developed countries, detailed soil maps are not sufficiently
available, and exploratory and reconnaissance maps have to be compiled to
point out areas with a high potential, which thereafter have to be mapped in
greater detail. In view of this, remote-sensing-means are indispensable tools
and morphographic or physiographic descriptions (see par. 8.1) make up often
the first entry to the legend of these maps, because:
- the knowledge of soil forming processes is generally too l o w for
indication of taxonomic units,
- landtypes and landforms determine the landscape performance, that is a
daily reality to man; the physiographic maps are readily understood and
geographic soil associations can be indicated both at the second and the
third level.
1.4. Remote sensing in soil science
Soil science comprises the mapping of natural soil bodies as well as the
study of dynamical aspects. The mapping of natural soil bodies or soil
geography is concerned mainly with the more or less permanent properties of
soil whereas the study of dynamical aspects regards features such as soil
temperature, soil moisture and structural changes e.g. surface sealing.
Most remote sensing techniques use radiation which shows only a shallow
penetration upon interaction with soil, rock and plant materials. By using
these techniques, it is only possible to obtain direct information about the
surface of soils and rocks or about vegetation covering the soil. Fieldwork is
necessary to estimate the properties of the three-dimensional soil profile.
Through combinations of interpretation aspects, soil profile properties may be
inferred, but of course these suppositions have to be verified by fieldwork.
Therefore, it would be a mistake to regard the interpretation of such remote
sensing data as decisive for soil distribution without the undertaking of
fieldwork.
Even remote sensing aids that have a deeper penetration (e.g.
microwaves), or provide data (with thermal Infrared) which are the result of
9
soil physical structure that is not limited to the soil surface alone, do not
enable to reveal the complete complex of soil properties.
The above emphasis is given to stress the necessity of fieldwork. Besides
this, there is the basic physics, which deserves our attention as another
aspect of modern remote sensing.
Imagery obtained by the use of Visible radiation is familiar to the eye and in
fact may be interpreted through direct recognition and identification, which
in cases may be followed by deducing the underlying processes.
However, other types of radiation, e.g. UV, IR or Microwaves, may also be used
for image production to visualize certain properties of the earth's surface. A
proper understanding of such imagery needs a physical basis focused on the
interaction process of the radiation under consideration with the objects and
features at the earth's surface.
Specific studies require specific remote sensing techniques.
The choice as to which remote-sensing-means is to be used, can be determined
by four features.
- the purpose of the study;
- the scale of the study;
- the specific characteristics of objects at the earth's surface in the
area under consideration;
- the climatic conditions.
The purpose of the study may be one or more of the following:
- soil inventory; airphoto-interpretation is a good aid for this purpose at
large and medium scales; at small scales, the use of satellite data as
well as airphotos is recommended;
- mapping of dynamical features, such as erosion and soil moisture;
multitemporal techniques are required for the study of dynamics;
- land evaluation; this requires a good insight in natural vegetation and
land-use as well as in soil dynamical aspects; airphoto-interpretation
and multitemporal techniques are very useful.
The scale of the study determines to a great extend the choice of the
most appropriate techniques. For large scale surveys, airborne methods are
required, medium scale surveys may be aided by both airborne and spaceborne
methods whereas small-scale surveys are served most by the use of satellite-
data.
One should realise that the characteristics of the objects at the earth's
surface are in fact the most decisive with regard to the choice of remote-
sensing-means. To illustrate this, three contrasting situations with specific
climatic conditions will be considered: (1) the temperate zone, (2) the arid,
semi-arid and sub-artic zones, and ( 3 ) the tropical rainforest.
The temperate climatic zones are generally intensively used for
agricultural purpose. The soil is mainly covered by crops or planted forests
and in places by semi-natural vegetation. The semi-natural vegetation may show
a close relationship with the soil conditions but in case of crops or planted
forests, the vegetative cover of soil cannot be regarded as an important key
to determine the soil condition. Only locally (on arable land) is the soil
surface bare during some period of the year. Therefore, spectral signature of
the soil surface generally only offers information on places which are part of
a greater unit (the natural soil body). The dimensions of the natural soil
body have to be determined through a combination of different aspects which is
usual in aiKphOtO-inteKpKetatiO~.
Arid, semi-arid and sub-artic regions are characterized by a scarce
vegetation-cover and bare rock or soils. Spectral signatures of the soil
surface may offer valuable information for soil mapping. Up to now, airphoto-
interpretation in these regions is the most current tool for soil mapping, but
there are good possibilities for the application of multispectral remote
sensing in improving accuracy and decreasing the amount of fieldwork in
mapping of soil.
The third situation we want to consider is the tropical rain forest. In
these regions, the natural vegetation, together with the aspects of relief,
slope and drainage pattern, offers a good key to soil distribution in many
places. Modern remote sensing techniques providing for a synoptic view and
airphoto-interpretation have proved to be of great value for mapping of soils
in these regions.
Finally, climatic circumstances may be decisive with regard to the choice
of the most appropriate remote sensing technique. When the climatic conditions
rule out techniques that make use of short wave radiation (Visible or Near
Infrared) due to permanent cloud cover, one should make use of long wave
radiation (radar), which can penetrate humid air and clouds.
11
1.5. Conclusions
The application of various remote sensing aids may reveal different soil
properties and the interpretation units may show a close relation to soil
conditions. Unfortunately, ideal remote sensing techniques are limited to
research projects., Mostly, one' has to work with means that are basically not
intended for soil survey purposes. From this it can be inferred that there is
a good reason that one should have knowledge of the applicability of the
present great range in remote sensing techniques. Another reason may be found
in the advantages arising from the application of different techniques.
Knowledge of basic physics is essential for their optimum use.
1.6 References
Breuck, W. de, and Daels, L., 1967. Luchtfoto's en hun toepassingen. E. Story- Scientia. P.V.R.A. Gent, 176 pp.
Glinka, K.D., 1927. Dokuchaiev's Ideas in the Development of Pedology and Cognate Sciences. In Russian Pedol. Invest. I. Acad. Sci. U.S.S.R., Leninggrad, 32 pp.
Soil Survey Staff, 1951. Soil Survey Manual. Agric. Res. Adm. US Dept. of Agric.: 503 pp.
Soil Survey Staff, 1975. Soil Taxonomy. A Basic System of Soil Classification for making and interpreting Soil Surveys. U.S. Dept. of Agric. Handbook No 436, 754 pp.
1.7 Additional reading
Barrett, E.C. pnd Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and Hall, 336 pp.
Estes, J.E. and Senger, L.W. (ed), 1974. Remote Sensing Techniques for Environmental Analysis. Hamilton Publ. Cy, Santa Barbara, California, U.S.A., 340 pp.
Mulders, M.A., 1977. Application of Teledetection in Pedology. 1-er Colloque PBdologie T616d6tection A.I.S.S. (I.S.S.S.), Rome: pp. 311-324.
Reeves, R.G., Anson, A. and London, D. (ed), 1975. Manual of Remote Sensing. Amer. SOC. of Photogramm. Falls Church, Virginia, Vol. I and 11, 2144 PP *
Rudd, R.D., 1974. Remote Sensing. A better View. Duxbury Press, North Scituate, Masachussetts, U.S.A., 135 pp.
12
2. INTERACTION OF ELECTROMAGNETIC RADIATION WITH MATTER
Energy can occur in different forms e.g. kinetic, potential, mechanical,
chemical, electrical and thermal energy.
Ocean waves make themselves manifest by their way of propagation. The
waves are due to a disturbance at the air-water interface. They are transverse,
that is the vibration of the particles is perpendicular to the direction of the
propagation. A number of aspects connected with wave motion becomes visible
when observing these waves, such as direction, wavelength, amplitude, velocity
and frequency . Electromagnetic radiation (EMR) is energy that propagates through vacuum
(free space) or through material media in the form of an advancing interaction
between electric and magnetic fields. It can make itself manifest by its
interaction with matter. Light and thermal energy are examples of EMR. Besides
by radiation, thermal energy may travel by conduction and convection.
In this chapter, physical concepts of EMR and its interaction with the
atmosphere and objects at the earth's surface are discussed. The interaction
process is of great importance to the remote sensing specialist.
2.1. The nature of electromagnetic radiation
The properties of EM waves can be summarized as follows (see Fig. 2.1):
- the waves are transverse; - the electric (E) and magnetic ( H ) vectors are perpendicular to the direction
of propagation, mutual perpendicular and in phase.
EM waves can be characterized by wavelength, amplitude, phase, frequency,
direction, velocity, polarization and coherence of the radiation.
EMR which has a fixed direction of the electric vector is said to be plane
polarized. Polarization of light can take place upon interaction with matter.
The coherence of waves concerns the relationship of phases; coherent waves or
uniform plane waves have a regular or systematic relationship between their
phases, while incoherent waves have phases that are related in a random
fashion. Radiant energy of natural sources is normally incoherent, however,
some artificial sources, such as radar and lasers, are constructed to produce
coherent radiation.
Interference in a point OCCUKS when the EM field in that point is made up
out of contributions from more than one coherent source. When the distances
13
Fig. 2.1 Electric ( E ) and magnetic ( H ) vectors of an EM wave.
the waves have travelled differ by a whole number of wavelengths, there will
he a maximum of intensity. When the distance transversed differs by odd
multiples of a half wavelength, the two waves will exactly cancel each other.
Interference may occur when reflections of the surface and of an interface
meet each other.
A surface illuminated by laser light looks grainy and seems to sparkle.
As the waves are scattered from neighbouring points on the surface, they
interfere with one another and reinforce one another if in phase, or cancel
one another when out of phase. The interference pattern depends on the angle
at which the surface is viewed (Schawlow, 1968).
Ordinary light does not produce such interference, because the light waves are
unrelated to one another as to phase.
The polarization of a uniform plane wave refers to the time varying hehaviour
of the electric vector field at some fixed point in space.
Consider a uniform plane wave travelling in the z direction with the E and 11
vectors in the x-y plane (Fig. 2.1). If Ex = 0 and only Ey is present, the
wave is said to he polarized in the y direction: a similar statement holds for
polarization in the x direction. If both Ex and Ey are present and in phase,
the resultant electric vector will have a direction dependent on the relative
amplitudes of Ex and Ey. The direction of the resultant vector is constant
with time and the wave is said to be linearly polarized.
If E, and Ey are not in phase, that is, if they don't reach their maximum
values at the same time, then the direction of the resultant electric vector
14
will not be constant with time. In the particular case where Ex and Ey have
equal magnitudes and a 90-degree phase difference: the wave is said to be
circularly polarized. Other out of phase cases, produce elliptical polarization
(Jordan et al., 1968).
The generation of EM waves occurs in wave trains or bursts of radiation.
Each wave train, elementary quantum or photon, carries a radiant energy ( Q in
J) which is proportional to the frequency (f in s-') of the wave, so that
where h is Planck's constant with a value of 6.626 x J S.
The EM waves travel through vacuum at a fixed velocity (c = 2,998 x lo8 m 6 - l ) .
The general relationship between velocity (c in m s-l) wavelength ( A in m) and
wave frequency (f in s-l) is:
c = f A (2 - 2)
Combining 2 - 1 and 2 - 2 results in
Q=h ' x ( 2 - 3)
Consequently, the energy of a photon is proportional to the frequency (2 - 2), and inversely proportional to the wavelength (2-3).
The processes involved in the generation of EMR produce radiant energy
with specific photon energy, frequency and wavelength. These quantities provide
a scale for the so-called electromagnetic spectrum (EMS). Particular zones are
essential for life, e.g. the Visible zone and the Infrared, or are made use of
for practical reasons, e.g. Microwaves and Radiowaves (see Fig. 2.2).
The radio spectrum is also indicated in Fig. 2.2. Part of it, that is from Very
- High - Frequency (VHF) up to Extremely - High - Frequency (EHF) is used for radar and is called Microwaves. For subdesignations of this zone, the reader is
referred to chapter 13.
15
v v - E
E E E x
0 0 0 0
E E E x
E x E E O x 0 E a o E E U
m m m m m m m m m m m m m m m m m m 0 0 0 0 0 0
g E 0 !5 F E S 0
0 1
I 1 I I 1 1 1 1 I I I 1 1 1 1 1 I J
wavelength (m)-
N N N N N N N N I I I I I I I I
0 0 0 0 0 0 0 0
I 1 I 1 1 I 1 I
0 N ! ? E t " " S " 7 c c c c 7 c c
N
H = h igh L = low V = very E = extremely M = medium
U = u l t r a
I N - N - N c
W I N - I N - I N - W I N X : I N Y I N
Y I 0 W I 0 0 w o 0 0 0 0 0
" E o Y 0 0
- 7 c c _ _ _ c 7 _ w; W W 3 > -1
300 30 3 300 30 3 300 30 3 GHz GHz GHZ MHz MHz MHz KHz KHz KHz
3bf;8;;01 ;51;)0 l!b 3iO km 3 3 4 3 60
1 1 1 1 I 1 I 1 1 1 109876 5 4 3 2 1 KHz
Fig. 2.2 The electromagnetric spectrum Abbreviations: V,B,G,Y,O,R = violet, blue, green, yellow, orange, red respectively
16
The Visible zone is subdivided acc. to Weast ( 1 9 7 4 ) into the following bands :
COlOUK Wavelength in nm
violet 400-424 blue 424-491 green 491-575
orange 585-647 red 647-700
yellow 575-585
Wavelength in nm representative
for COlOUK
410 470 520 580 6 0 0 6 5 0
However, the eye shows a low sensitivity outside this zone respectively
down to 380 nm in the short wavelength range, and up to 7 8 0 nm in the long
wavelength range (Schurer et al., 1980) Therefore, the Visible zone is often
extended.
2.2. Radiation laws
All bodies with temperatures above absolute zero emit radiant energy.
The radiation laws use the concept of a perfect absorber and radiator, the so-
called black body . These laws are: - the Stefan - Boltzmann's law, which states that the total of radiation
emitted from a black body (Me in Wm-') is proportional to the fourth power of
its absolute temperature (T in K) according
( 2 - 4 ) M e = o T 4
2 TI k4 = 5.7 10-8 wm-2 K -4
15 c h 2 3 where a =
in which c = velocity of light in m s-l
h = Planck's constant (see 2 - 1) k = Boltzmann's constant = 1.38 x 5K-l
- Kirchhoff's law; since no real body is a perfect emitter, the real emittance
(M) of a radiator is a fraction of the emittance of a perfect radiator (Me),
thus
17
where E the emissivity (M/Me) of the real body, has a value between 0 (white
body or perfect reflector) and 1 (black body);
- Wien’s displacement law; this states that the wavelength, which is
correlated to the maximum radiant emittance of the black body ( A max), is
inversely proportional to its absolute temperature T according to:
Where C 3 = 2898 IJ m K; the equation indicates that as the temperature
increases, the dominant wavelength of the radiation emitted shifts towards the
short wavelengths (see F:
-- l o 5
5 l o 4
ul l o 3
9 l o 2
I E
4J + v
c
V W
:: .lo-: U .
Wavelength (pn)
:. 2 . 3 ) ;
0
Fig 2.3 The spectral radiance of a blackbody (after Higham e.a. 1973, adapted from Jamieson et al., 1963)
- Planck’s law. describes the spectral relationships between temperature and radiative properties of a black body when thermodynamic equilibrium exists;
18
the law may be expressed by
1
M dX= 2 TI h c2 X X (2 - J)
where M dX
h = Planck's constant (see 2 - I ) ,
c = velocity of light m s- ' ,
k = Roltzmann's constant (see 2 - 4). A = wavelength in m,
T = absolute temperature in K,
e = base for natural logarithms.
The equation enables the assessment of proportions of total emittance for a
range between selected wavelengths.
= radiant energy in Wm-2 within a unit range of d X , X
2.3. Solar irradiance and earth emittance
The spectrum of solar irradiance (radiant power received per unit area)
outside the earth's atmosphere resembles that of a 6000 K black body spectrum,
while the spectrum of terrestrial emittance (power emitted per unit area)
approximates the 300 K black body. There is a global equilibrium between heat
gained from the sun and heat lost to space.
Fig. 2.4. shows the EMS of solar and terrestrial radiation. Solar radiation is
significantly attenuated by the earth's atmosphere.
The spectrum of solar radiation at the earth's surface is in fact a
transmission spectrum, since part of the radiation is specularly reflected,
scattered, or absorbed by the molecules present in the earth's atmosphere.
The total solar irradiance arriving at the earth's surface can be divided into
a direct and a diffuse component. The latter is the result of scattering by
atmospheric aerosols and molecules and will vary with the visual range in
spectral properties and intensity.
Most of the solar radiation which reaches the earth's surface has wavelengths
shorter than 4.0 urn, whereas the radiation emitted by the earth is found
mainly in the band 4.0 - 40 um (infrared). Maxima in solar radiation and
terrestrial radiation are found respectively at 0.5 and 10 um.
2.4. Concepts of matter
In remote sensing of the environment, many different types of matter are
encountered, these being:
19
uv VIS Infrared I 1
- body i r rad iance a t 6000 K -. -- 2000
-.
Estimated infrared emission -.
-.
-.
-.
I E a
cu 1000
-
I E x v
~ 500 0, L W C w
200
100
50
20
10
5
2
1 0.7
I I / I I I I
7 0.1 0.2
: x t r a t e r r e s t r i a l s o l a r i r rad iance I
A Di f f u s e '\, s o l a r I
i r r a d i - ance a t the e a r t h ' s surface
/ Absorption band
0 . 5 1.0
Direct beam (normal incidence) Solar i r rad iance a t the e a r t h ' s surface
t lack body emittance 300 K
2.0 5.0 10 20 50 100
Wavelength (pm)
Fig. 2.4 Electromagnetic spectra of solar irradiance and terrestrial emittance (modified after Barrett and Curtis, 1976, originally Sellers, 1965)
- diatomic gases (e.g. 02, N 2 , CO);
- polyatomic gases (e.g. H 2 0 , C02);
- complex molecular organic materials (vegetation and soil organic matter);
- solid inorganic substances (minerals). To understand the interaction of EMR with matter, we need to go down to
the atomic and molecular level.
If external energy is available, the atoms of a gas may become ionized that
20
is, electrons may be freed from an atom, leaving it as an ion with a net
positive charge. On the other hand, electrons may attach themselves to an
atom, thus forming a negative ion. In a metal, some of the electrons are free
to move from one atom to the next giving rise to the conduction of electricity
(Jordan et al., 1968).
Substances that contain few or no free charges and consequently are poor
conductors of electric current, are called dielectric substances. A good
dielectric is one in which the absorption of electric energy is a minimum: a
vacuum is the only perfect dielectric (Reeves, 1975) .
In structures such as molecules, the energy states give rise to specific
features. Although the number of energy states increases with the density of
the structure, that is from gas over liquid to solid, a general understanding
may be obtained from the energy states of molecules, such as in gases.
Molecules in gases possess three types of internal energy states: rotational,
vibrational and electronic. For any electronic state, a variety of vibrational
states is possible, and for any vibrational state a variety of rotational
states is possible. The total internal energy of the molecules at any time is
the sum of the energy of the three states.
Electronic states are separated by energy differences corresponding to the
energy carried by photons in the UV, blue and green regions; pure vibrational
states by photon energy in the yellow, red and near Infrared and pure
rotational states by middle - far Infrared and Microwave portions of the EM
spectrum (Lintz and Simonett, 1976) .
In liquids, the atoms or molecules are in continual motion but there is a
certain amount of ordrr extending over a relatively short distance.
In solids unrestricted motion is not possible and the molecules are fixed in
position in an orderly arrangement. The basic unit is a crystal.
Because rotational energy states are precluded in liquids and solids, only
vibrational and electronic states remain.
A number of fundamental vibrational modes are:
- the OH, S i - 0, Si - 0 - Si, Al - 0 - Si and Fe - 0 stretching modes,
- the H - 0 - 11 and A1 - OH bending modes.
The modes of vibration show allowed frequency bands separated by forbidden
regions.
Crystals possess a long range order, a periodicity of structure. The
forces acting between the atom in crystals are determined by the way in which
the outer electrons of the composing atoms are distributed in space. One may
21
distinguish between the following
a. ionic crystals (e.g. NaCl),
b. valence crystals (e.g. diamond
C. metals (Cu, Ag),
extreme types (Dekker, 1958) :
,
d. van der Waals crystals (many organic crystals).
In ionic crystals, one or more electrons of one type of atoms are
transferred to another, leading to the formation of positive and negative
ions. The cohesive energy is provided mainly by Coulomb interaction between
the heterogeneous ions. At elevated temperatures these crystals exhibit ionic
conductivity. Ionic crystals are characterized by a strong absorption in the
Infrared.
In valence crystals, the neighbouring atoms share their valence electrons
under the formation of strong bonds. They are very hard and show a poor
electrical and thermal conductivity.
In metals, the outer electrons of the atoms have a high degree of mobility to
which these materials owe their high electrical and thermal conductivity. The
cohesive energy is provided by Coulomb interaction between the positive ion
and the "negative smeared out charge" of the conduction electrons.
Molecules like H20 and HC1 may be considered to consist of two ions. They
possess a permanent dipole moment which is equal to the effective charge per
ion, times the separation of the ions.
The interaction between such permanent dipoles provides, besides other forces,
the cohesive energy in van der Waals crystals such as organic crystals. In
this case, the other forces refer to the socalled dispersion forces which are
due to fluctuating dipoles by combination of moving electrons and the nucleus
of an atom. The weakness of the forces is expressed by the low melting point
of these materials. Between the extreme groups, there are many intermediate
ones e.g. semi-conductors, being intermediate between valence crystals and
metals.
To understand these intermediate groups, the electron orbits are
considered as energy levels separated by energy gaps.
Crystals for which a certain number of energy levels are completely filled
with electrons, the other levels being completely empty, are insulators
(dielectrics). On the other hand, a metallic character is caused by the
presence of an incompletely filled energy level.
If the energy gap between the empty and the filled energy levels is low, as
for intermediate groups, an insulator may become a semi-conductor by thermal
22
e x i t a t i o n . When t h i s happens, some of t h e e l e c t r o n s of t h e upper f i l l e d l e v e l
a r e e x i t e d i n t o the next empty l e v e l and conduct ion becomes p o s s i b l e (Dekker,
1958) .
In normal l i q u i d s o r gases , t h e o r i e n t a t i o n of t h e molecules i s random
and t h e p h y s i c a l p r o p e r t i e s become independant of t h e d i r e c t i o n a long which
they are measured; they a r e i s o t r o p i c .
The p h y s i c a l p r o p e r t i e s of s i n g l e c r y s t a l s i n g e n e r a l depend on t h e d i r e c t i o n
a long which they are measured r e l a t i v e t o t h e c r y s t a l axes . This phenomenon i s
c a l l e d an i so t ropy . T r igona l , t e t r a g o n a l and hexagonal systems a r e o p t i c a l l y
u n i a x i a l , be ing i s o t r o p i c f o r t r ansmiss ion p a r a l l e l t o t h e p r i n c i p a l a x i s of
symmetry. Orthorombic, monocl in ic and t r i c l i n i c systems a r e o p t i c a l l y b i a x i a l .
However, cub ic systems a r e o p t i c a l l y i s o t r o p i c .
Besides s o l i d matter, rocks may a l s o c o n t a i n l i q u i d s and gases . For
s o i l s , t h e presence of water and a i r i s a must. The s o l i d s i n rocks and t h e
rock fragments o r mine ra l s i n s o i l s may range from l a r g e b locks wi th e i t h e r
smooth, po l i shed s u r f a c e s , o r rough s u r f a c e s , t o smal l p a r t i c l e s t h a t vary i n
shape and packing.
The macroscopic p r o p e r t i e s , as w e l l as t h e a tomic - molecular - and l a t t i c e
s t r u c t u r e s , de te rmine t h e i n t e r a c t i o n wi th EMR.
2 . 5 . Atomic - molecular e f f e c t s on t h e i n t e r a c t i o n process : p o l a r i z a t i o n ,
d i e l e c t r i c c o n s t a n t , r e f r a c t i v e index and a b s o r p t i o n f a c t o r .
Since ma t t e r i s l a r g e l y made up of charged " p a r t i c l e s " , e x t e r n a l e l e c t r i c
and magnetic f i e l d s must e x e r t some k ind of i n f luence . This i n f l u e n c e w i l l be
p r e s e n t whether t h e p a r t i c l e s a r e f r e e t o move about o r are t i g h t l y hound
t o g e t h e r ( Jo rdan e t a l . , 1968) .
In t h e case of good conductors such as me ta l s , t h e e l e c t r i c f i e l d of t h e
i n c i d e n t wave causes conduct ion c u r r e n t s t h a t produce t h e i r own e l e c t r i c f i e l d
and g ive r ise t o very s t r o n g r e r a d i a t i o n of t h e EM wave (mi r ro r - e f f e c t ) .
D i e l e c t r i c s o r i n s u l a t o r s d i f f e r from conductors , i n t h a t they c o n t a i n no
f r e e charges , bu t r a t h e r cha rges which a r e t i g h t l y bound toge the r t o form
i o n s , atoms, p a r t i a l molecules and molecules. The a p p l i c a t i o n of a s t e a d y
e x t e r n a l EM f i e l d causes a s m a l l bu t s i g n i f i c a n t s e p a r a t i o n of t h e bound
cha rges , so t h a t each i n f i n i t e s i m a l element of volume behaves as i f i t were an
e l e c t r o s t a t i c d ipo le . The induced d i p o l e . f i e l d t ends t o oppose t h e a p p l i e d
f i e l d ( p o l a r i z a t i o n ) .
On an atomic s c a l e , e l e c t r o n i c p rocesses a r e impor tan t , and charge s e p a r a t i o n
23
can occur due to the displacement of the negative electron cloud relative to
the positive nucleus; this is called electronic polarization.
On a molecular scale, vibrational processes (par. 2.4) with atomic or ionic and
orientational polarization are important.
Atomic or ionic polarization results from the displacement of atoms or ions
within molecules (due to an external field).
Orientational polarization arises in materials whose molecules are permanently
polarized but randomly oriented; an external EM field causes the molecules to
align themselves.
On a still larger scale, one encounters space-charge polarization. In that
case, free conduction electrons are present, but are prevented from moving over
relatively great distances by barriers such as grain boundaries. The applicat-
ion of an external EM field results in piling up of these electrons against
these barriers producing the separation of charge required to polarize the
material (Jordan et al., 1968).
For each type of polarization there is a typical resonance frequency, which has
the precise radiant energy (h.f see 2-1) needed for the energy transition.
Material properties important for the interaction are the permittivity or
dielectric constant ( E ) and the conductivity ( u ).
The dielectric constant of a medium is defined by the equation (Weast ed.,
1974) :
where F is the force of attraction between two charges Q and Q' separated by a
distance R in a uniform medium (capacitance of a capacitor with specific
dielectric material). Often E~ is used, the relative dielectric constant:
where E is the dielectric constant of free space (8.859 x lo-" V-' A s m-')
The dielectric constant is a measure for the amount of polarization upon
interaction. To obtain normalization, so-called static E~ values may be derived
by application of a static EM field (frequence zero).
The static cL. values of most dielectric media are between 1 and 6 , but water
having dipole molecules has an exceptionally high value of about 80 (Prins,
24
1955). Temperature, p re s su re and composition have impact on t h e E va lues . So
does t h e f requency of dynamic o r a l t e r n a t i n g f i e l d s .
I f t h e frequency i s low (e .g . a t Microwave f r equenc ie s and Radiobands),
the m a t e r i a l behaves e i t h e r l i k e a conductor or semi-conductor, whi le a t h igh
f r equenc ie s i t behaves l i k e a d i e l e c t r i c (e.g. I n f r a r e d and V i s i b l e ) .
The p o l a r i z a t i o n of e l e c t r o n s may be a t t a i n e d s imul taneous ly wi th an
in s t an taneous EM f i e l d bu t t h e o t h e r t ypes of p o l a r i z a t i o n r e q u i r e r e l a t i v e l y
much t i m e t o a t t a i n t h e i r s t a t i c va lue . Dekker (1958) mentions a t i m e f o r
d i p o l a r p o l a r i z a t i o n which v a r i e s between days and S. Since t h e masses
of t h e microscopic bodies c o n t r i b u t i n g t o t h e p o l a r i z a t i o n i n c r e a s e i n t h e
range of e l e c t r o n s , i o n s , molecules up t o complex m a t e r i a l s l i k e g r a i n s , t h e
resonance f r equenc ie s f o r t h e s e success ive p o l a r i z a t i o n e f f e c t s have t o
dec rease . This is, because i n e r t i a of t h e p a r t i c l e s becomes r e l a t i v e l y g r e a t
and consequent ly t h e p a r t i c l e s a r e unable t o fo l low rap id o s c i l l a t i o n s of t h e
a p p l i e d f i e l d .
By way of i l l u s t r a t i o n , E~ v a l u e s a t r a d i o f r equenc ie s a r e g iven i n t a b l e 2.1.
Most m a t e r i a l s show v a l u e s between 1 and 14 w i t h i n t h i s f requency range. For
example, sodium c h l o r i d e having a n gr of 6.12 a t VLF shows a lower va lue i n
t h e V i s i b l e ( E ~ = 2.25 acc. t o P r i n s , 1955). Its resonance f r equenc ie s are i n
Table 2.1. R e l a t i v e d i e l e c t r i c c o n s t a n t of s o l i d s a t r a d i o f requency and a t T = 17 - 22" C u n l e s s s p e c i f i e d d i f f e r e n t l y (Weast ed., 1974).
s o l i d s f requency €1.
a p a t i t e 1 o p t i c a x i s VHF 3 x lo8 9.50 7.41 I t 11 11 11 I,
diamond 108 5.5 11
I, I,
I,
11
11
I t
d o l i m i t e 1 o p t i c a x i s 8.0 6.8
f e r r o u s oxide (15°C) 14.2 r u t i l e 1 o p t i c a x i s 86
170
11 I, 11
11 ,I I, 1,
z i r c o n 1 ,I1 o p t i c a x i s 1 2 sodium ca rbona te (10H20) 6 x lo7 5.3 q u a r t z 1 o p t i c a x i s HF 3 x lo7 4.34
I t 4.21 c a l c i t e I o p t i c a x i s VLF 104 8.50
8.00 5.66 6.12
gypsum sodium c h l o r i d e tourmal ine 1 o p t i c a x i s 7.10
11 11 I t 11
11 I t 11 I, I,
11
11
11
11 I t 11 I1 I' 6.3
25
the Infrared. The relatively heavy ions involved cannot follow the rapid
ossillations in the Visible. The same applies for E of water for the high
frequencies in the Visible, E being around 1,77. r
In an electric field, the frictional work done in polarization of atoms
and molecules absorbs energy from the field. When the field is removed the
orientation is lost by thermal agitation. If free charge carriers are present,
the current also causes heat loss because of the resistance of the material.
At high frequencies (Infrared, Visible and UV), the losses are relatively
high, only electronic or ionic (or atomic) polarizations are active and
permanent dipoles are not able to follow the field variations.
At low frequencies (radio and audio), the losses are relatively small and
permanent dipoles contribute their full share to the polarization.
Another term used to describe the interaction of EMR with matter is the
index of refraction (n ) which indicates the ratio of the velocity of EMR
travelling through free space (c) to its velocity in a specified medium (A)
nA n = - = C n vA
( 2 - 10)
where n A is the refractive index of the specified medium, and no that of free
space. For the same frequency, E of dielectrics is related to n as follows:
E r = n 2 (2 - 11)
Normally, the EM wave experiences exponential damping in traversing the
material. The damping in electronic, atomic or ionic displacements is caused
by the restoring and frictional forces. Although for electronic polarization
in a specific case with low damping, absorption and emission at a critical
frequency may be produced simultaneously (selective reflection acc. to Jenkins
et al., 1957), generally, a considerable portion of the incident radiation is
absorbed. The radiation absorbed is converted into radiation of a lower
frequency and a longer wavelength: mainly thermal radiation.
Lambert's law relates the original intensity (10) to the intensity (I) after
passing through a thickness x of a material with an absorption factor k:
I = Ige-kx ( 2 - 12)
The wave may penetrate only a very short distance in good conductors
26
before being reduced to a negligible small percentage of its original
strength.
The depth of penetration 6 or skin depth is defined as that depth in which
the wave has been attenuated to l/e or approximately 37 percent of its
original value. At that distance kx = 1 (see 2 - 12) and since 6 = x in that
case
1 (2 - 13) k
s = - 6
For absorbing media, the index of refraction does not properly describe
the interaction process. One has to use a loss term in addition. This is
expressed by the complex refractive index (it), which is given by:
where k is the absorption factor (2 - 12), and j= a. From this relation together with 2 - 11, it follows for absorbing media
that
where E is the complex dielectric constant ( X,T) with E ' as the real part
defining velocity and wavelength in the material, and E" is the imaginary
part which expresses the energy losses in the medium.
(2 - 15)
(2 - 16) E" and E" = 2nK or n = - 2K
2.6. Macroscopic effects on the interaction process; a description using the
wave model of EMR.
In section 2.5, the displacement of charges (polarization) is introduced.
The EM field which causes the polarization is an alternating field. The
displacements are elastic and have a restoring force which is proportional to
the displacement itself. They can be treated as harmonic oscillations.
The external EM energy is in resonance when its photon energy is equal to the
27
difference between two energy levels of the atoms or molecules in the target.
Actually, the atoms OK molecules also react to EMR of any frequency: the
socalled nonresonant reaction. The molecules and atoms act as oscillators if an
EM wave passes over them. The EM wave induces a vibration of the oscillator in
the target, so that it oscillates with the frequency w(=2nf) of the field and
not with its own resonance frequency
In principle, a vibrating charge is an emitter of E m .
In gases, there is an individual incoherent scattering by each oscillator.
There is no particular interference among the oscillators of gases.
However, the molecules or atoms of solids (and of liquids or even cloud
droplets) show an orderly arrangement, which results in interference of the
reemitted waves. The interference is destructive in all directions except for
the forward direction where it is constructive. In the forward direction, the
reemitted waves build up to a single refracted wave.
This is not so near the surface of the material. There is a thin layer (about $ A
thick) of oscillators at the surface for which the back radiation is not
completely canceled by interference. The radiation "backward" of these
oscillators adds up to a reflected wave. The intensity of the reflected
radiation is proportional to N2, where N represents the number of oscillators
producing radiation waves which are in phase at a given point in space
(Weisskopf, 1965; N2 is proportional to A
wo *
4 ).
Macroscopic effects such as true surface or specular reflection,
scattering and refraction take place at boundaries and are a function of
chemicophysical structure as well as roughness and orientation of the
boundaries.
To obtain a simple model, EMR is assumed to travel from a less dense medium
(air) to a more dense medium with a plane surface. Upon interaction, part of
the EMR is reflected from the surface, the rest enters the substance and is
transmitted to a degree depending on the absorption characteristics.
The angle Bi formed by the direction of propagation of the incident
radiation with the normal to the surface (see Fig. 2.5) differs from
angle of refraction, which is the angle formed by the direction of propagation
of the radiation penetrating the substance with the normal to the surface. Fig.
2.5 presents specular reflection, which occurs when surfaces are smooth
Or the
28
ref 1 ec ted rad ia t ion i nc i den t radiat ion I J
o p t i c a l l y layer ( A )
o p t i c a l l y layer ( B )
transrni tted/ I radiat ion a
o p t i c a l l y 1 ayer
l e s s dense
more dense
l e s s dense
Fig. 2.5 Specular reflection, refraction and transmission of light.
a) general situation b) specific case: angle between reflected and refracted rays is 90"
0 perpendicular to plane of incidence (horizontal polarization). -parallel to plane of incidence (vertical polarization).
Plane of incidence: plane formed by the normal to the surface and the direction of propagation of the incident wave. Horizontal and vertical refer to the plane surface upon which the wave is incident, although the direction can only be near vertical at grazing angles.
29
and highly polished. It follows Snell's law, which gives the index of
refraction (n) relative to free space for each medium. When the media A and B
are concerned:
n sin 0
n sin 0 B - i _-- A
This relationship is expressed in Fig. 2 . 6 . Two conclusions may be
derived from this figure: at low angles of incidence ( Oi = 10" - 2 0 " ) a
difference in the index of refraction does not cause great differences between
Oi and 0, (low Oi - Elr); Oi - 0, becomes
angles (Oi = 70" - 8 0 " ) .
8ol /
very high for high n at grazing
n = l ,O
n = l , l
n=l ,3
n=l ,5
n=2,0
n=2,7
nB
nA Fig. 2.6 Relationship between Oi, 0, and n (n= - ) ,
The horizontally polarized components of the incident EMR (see Fig. 2.5b)
parallel to the interaction surface do not meet discontinuities in that
surface and therefore are strongly reflected.
The Fresnel reflection factors apply to flat smooth boundaries between
two homogeneous and isotropic media, coherent monochromatic EMR and a medium
in which multiple reflections do not occur. They have the following form:
30
2 ei + Jn2 - s i n
ei Rv = q = - n2 cos ei + A' - sin2 E~ - n2 cos e
i
2 ei cos ei - Jn2 - sin
ei
E~ ' = T = cos ei + Jn2 - sin2
( 2 - 1 8 )
( 2 - 1 9 )
where \ = reflection factor for vertical polarization,
Rh = reflection factor for horizon polarization,
Ei = amplitude of incident electric field with v OK h polarization
E, = amplitude of reflected electric field with v or h polarization,
0 = angle of incidence,
n = index of refraction ratio between two media, i
In table 2.2 some values are given for \ and Rh equations 2 - 18 and 2 - 19 .
calculated according to
Table 2.2 Values of p and ph at Oi 2 0 , 4 0 , 60 and 80" OK n = 1 ,5 and n = 2.
n = 1.5 n = 2 oi
'G PV Rh ph % PV Rh Ph 200 -0.288 0.083 -0.104 0.012 -0.311 0.097 -0.354 0.125 40" -0.146 0.021 -0.252 0.064 -0.235 0.055 -0.424 0.179 60" 0.112 0.012 -0.645 0.416 -0.518 0.268 -0.565 0.319 80" 0.487 0.237 -0.795 0.632 0.431 0.186 -0.819 0.671
In table 2.2 the reflectance for horizontal polarization:
ph = ( R h ) 2 = Irh where Irh is intensity of reflected radiation with Ii h
horizontal polarization, and Iih is intensity of incident radiation with
horizontal polarization (item p v). The negative signs indicate phase changes.
These, however, are immaterial for the intensities since the latter are
dependent on the squares of the amplitudes.
When we consider the intensity figures of table 2 .2 , we see that for
vertical polarization with increasing angle of incidence an angle will be
reached where the intensity becomes zero, this in contrast to horizontal
polarization the intensity of which increases with increasing angle of
31
incidence. The angle at which vertical polarization is lowest, and therefore
the reflected radiation is best polarized, is called the Rrewster angle.
When this situation occurs Snell's law (2 - 17) can be written as:
nB sin B i - = = tan 0 nA sin (90 - 0,) i
(2-20)
The situation is presented schematically in Fig. 2.5b.
Fig. 2.7a shows the reflectance of horizontal( ph ) and vertical
polarization ( pv) in relation to the angle of incidence for a dielectric
medium with n = 1.5. The polarizing angle or Brewster angle (tan Oi = 1.5) is
at about 56'. From the data in Fig. 2.7a, it may be concluded that upon
interaction at Oi larger than 30" , the reflected EMR shows a predominance of
horizontally polarized radiation (surface reflection).
1 .o f ref1 ec tance
P . -
Brewster
I-
angle of incidence 1 9n0
1 .o + re f lec tance
t b.
I I 1 I I I I ' 1 ' I ' h
angle of incidence goo
angle
Fig. 2.7 Reflectances (Higham et al., 1973) (a) non-absorbing medium (b) absorbing medium
Fig. 2.7b shows ph and p for an absorbing medium. It appears that the
pv does reflectances are higher than for the non-absorbing medium and that
not become zero at the Brewster angle.
So far, targets with a plane surface and coherent radiation have been
considered. It will be evident that granular materials (e.g. soils) and
32
incoherent radiation offer more complications.
Besides reflection at the surface, internal reflection OCCUKS at surface
boundaries within the granular material. The internally reflected ray leaves
the grain upon refraction at the grain surface and is added to the total
reflected radiance.
Therefore for incoherent illumination, the total reflected radiance of a
granular object is thought to be composed of a surface component and an
internal, or volume component.
The total reflectance (PT) may be given by:
( 2 - 21)
where p, = reflectance of the surface
and pi = internal reflectance (Leu, 1977).
Minerals show differences in the magnitudes of the surface and the
internal components of reflectance depending on their refractive index and
absorption.
Most low absorptive minerals with low refractive index show a relatively small
P (1) and will become brighter due to a high p ( A ) when grain size is
decreased. However high absorptive minerals are generally characterized by a
high p ( A ) and low p ( A ) .
Most of the colours, we see around us are due to preferential absorption.
The reflection from the surface is practically colourless; the principal
colour is derived from light that has penetrated and which, after being
reduced by the absorbing effect of the medium, is reflected by a second (or
third) surface (Weiskopf, 1968).
If the surface reflectance is very large, the material is said to have a
surface colour (e.g. metals). When the radiation reflected from within the
material is predominant, the material exhibits a body colour which accounts
for most minerals and vegetation.
Diffraction occurs when EMR interacts with an edge oE an object. The
reflected wave fronts spread out and the EMR departs from rectilinear
propagation.
Scattering is closely connected both with reflection and with diffraction.
When the size of a reflector is somewhat greater than the wavelength of the
incident radiation, spherical and regular wavelets are produced in the centre
33
of the reflector to form short segments of plane wave fronts, while at the edges
the reflected wave fronts spread out owing to diffraction. It is
understandable, that there is greater spreading when the reflector becomes
smaller with respect to the incident wavelength.
The spreading may become so great that the reflected waves differ very little
from uniform spherical waves, and plane wave fronts are not produced; the
radiation is said to be scattered (Jenkins et al., 1957)
Some of the earliest models assumed that scattering of the surface arose from
many point scatterers and followed Lambert's cosine law:
I (Oi) = I. cos Oi ( 2 - 22)
where I(Bi) = intensity (W/sr) as a function of angle of incidence (0) and
I. = intensity (W/sr) for Bi = 0.
According to 2 - 22, at, Oi l o " , 50" and 70", I (Bi) is respectively 0.98 Io,
0,64 I. and 0.34 10.
The distribution is hemispherical and is often referred to as the normal
Lambertian behaviour.
The model might be applicable for specific vegetation types when using
coherent radiation for detection, but it does not explain the behaviour of
scattering from many other surfaces.
A different approach is found in the so-called facet models. In these
models, a rough surface is described through a series of small planar facets.
The models treat the scattering or reflection from the assemblage of facets by
taking into account their size, slope, orientation and distribution.
A wide finite facet, being many wavelengths across, shows a narrow reradiation
pattern, in contrast to a narrow finite facet (approaching the wavelength),
which has a wider reradiation pattern.
In Fig. 2.8 from left to right, the facet size is increasing. Small facets (at
the left) are almost nondirective. Larger facets concentrate the scattered
energy more at normal incidence. For an infinite large facet, all the energy
is reflected back at the source.
When the illumination is incident from an other direction than normal to
the surface, the general shape of the patterns remains the same, but the peak
of the reradiation pattern is in the direction of reflection (Fig. 2.8b).
Therefore, an infinite plane facet only produces much reradiation back at the
34
small moderate large very large moderate
(a) normal incidence (b) oblique incidence
Fig. 2.8 Facet patterns at normal (a) and oblique (b) incident illumination.
source when the direction of the incident radiation is normal to the surface.
Natural surfaces, generally show a very complicated assemblage of facets,
which may be described in a broad way by roughness.
Rayleigh's criterion defines roughness as a function of wavelength and Oi.
A surface is smooth according to this criterion if:
h < A/(8 cos Oi) (2 - 23)
where
h = height: above a plane in wavelengths.
The roughness concerns microrelief. If the microrelief becomes
significantly small, the surface is smooth and reflects with high directivity.
When the microrelief is greater than the criterion given above, the surface
scatters with a nondirective pattern. However, there will be an upper limit at
which the influence of diffractive patterns is negligible and directive
reflection dominates (see large facet Fig. 2.8).
As can be seen, the wavelength of the radiation dominates the roughness upon
interaction. Most natural surfaces appear to be rough when illuminated by
short wavelength radiation such as the Visible, but may be smooth for long
wavelength radiation (Microwaves). The angle of incidence is also important,
the smoothness criteria acc. Rayleigh being at 50' and 70' about
118 A s 1/5 A and '/3 A respectively.
Oi = 10'
Another aspect related to the angle of incidence and surface roughness is
35
shadow. The shaded area has to be taken into account in calculating the total
reflectance.
To illustrate this, Fig 2.9 is given, which shows the effect of normal and
oblique incident radiation on a surface with regular roughness.
This figure demonstrates the complexity of roughness. Normal incidence in
Fig. 2.9a results in reflection at the horizontal surfaces only, their sum
being equal to the orthogonal projected surface. The total reflecting surface
in Fig. 2.9b consists of the horizontal upper facet as well as the vertical
facets towards the source and the horizontal lower facets minus the shaded
areas of these facets. In this case the total reflecting surface is somewhat
larger than the orthogonal projected surface.
So the effect of oblique incidence and consequent shadow is a small
increase in reflected radiation. The simple statement, roughness produces
shadow and thus reduction in reflected radiation, has no general validity.
The non- Lambertian behaviour of many natural surfaces, which may show a
wide distribution of grain sizes, is mentioned above. The work of Coulson
(1966), being a study on hemi-spherical reflectance of soil and grass surfa-
a. incident rad ia t ion normal t o a surface w i t h regular roughness
\ incident radiat ion
b. oblique t o a surface with regular roughness
Fig. 2.9 Incident radiation in relation to regular roughness of a surface of which each facet acts as a diffuse reflector.
36
ces, illustrates this (chapter 3 ) .
Coulson found at high oblique incidence ( e.g. Oi = 53"), maxima in scattered
Visible and near Infrared radiation, not at the specular point, but forward
beyond this point as well as in the backward direction (Fig. 2.10). Using ps
and pi (2 - 21) and the effect of shadow on rough surfaces, the following
explanation is given.
Fig. 2.10 Model of scattering from natural surfaces at high oblique illumination. The vectors indicate schematically the intensity of scattered radiation from a low absorbent medium.
At high oblique incidence of radiation on rough natural surfaces such as
soils, the contribution of ps in the forward direction is reduced, since the
irregular surface minus the shaded area offers only few facets for reflection.
However, for low absorbent materials, pi, due to reflection from internal
facets, is high and contributes to the p in forward direction producing a
maximum in the scattered radiation. In the antisource direction, however, no
shadow is present to reduce Ps and another maximum is found. The latter will
be more pronounced for high absorbent materials, which are characterized by a
high ps , while the forward maximum for these materials is not pronounced, owing to their low pi.
2.7. Thermal properties
A number of materials which show absorption due to electron orbital
motion changes are capable of converting the absorbed energy into emitted
radiation of a longer wavelength band without first converting the absorbed
37
energy into thermal energy. The process is called luminiscence or
fluorescence. The fluorescence of natural materials is in the Ultraviolet,
Visible or near Infrared.
However, at the high frequencies of the Visible and the near Infrared, a con-
siderable portion of the incident energy is wasted due to energy exchange with
the components of the surrounding lattice. The absorbed energy ultimately
appears as thermal radiation. In such a way, some of the solar radiation in
the Visible is converted into middle and far Infrared upon interaction with
the earth's surface.
Some concepts and parameters used in description of the thermal
interaction process are discussed below (see also par. 2.2).
The emissivity E is defined as the ratio of the spectral emissivity of a
material to that of a black body at the same temperature (2 - 5). For a black
body, the spectral emissivity is equal to the spectral absorptance, which is
by definition equal to 1.
For natural bodies, we can distinguish absorbed energy ( M ), reflected energy
( MP) and transmitted energy ( M ). Therefore, the incident energy (Mi) can
be divided into (Janza, 1975):
M . = M + M + M 2 - 24) i a p ~
or normalizing with Ei
a ( X ) + p ( X ) + r ( X ) = l 2 - 25)
Natural bodies which approach the properties of black bodies with respect
to emissivity are the so-called opaque materials. Opaque bodies may be
considered to have a T = 0. Then a + p = 1 and because a = E:
E = 1 - p (2 - 26)
where p is low and E is high for opaque natural bodies, while the opposite is
true for highly reflectant natural bodies.
Similar to reflectance, one may use the terms absorptance and transmittance.
Absorptance is defined as the ratio of the radiant flux absorbed hy a body to
the radiant flux incident upon it. Spectral absorptance refers to the
38
absorptance in specified wavebands.
Transmittance is the ratio of the radiant energy transmitted through a body to
that incident upon it.
The emissivity, like reflectance, is sensitive to variables of look angle,
wavelength and polarization.
Janza (1975) used an air-sand interface (a lossless medium with a complex
dielectric consistent E~ = 3.2 - j0 at a real temperature of 27510 for example
to indicate the magnitudes of the parameters and their variations with the
angle of incidence. Since it concerns a lossless medium, the emissivities f o r
vertical polarization and horizontal polarization, respectively ( E and tj, 1,
are given by 1 - p and 1 - p h, respectively. In that case, the %/O and
E / e curves can be constructed (see Fig. 2.11). h
3= 1.0 w 2 0.9 0
," 0.8
a, 0 . 7
E 0.6
+J 8
.r
V
x
5
c, 0.4
VI 0.3 .r
.r
v) .- 5 0.2
0 . 1
0 0 10 20 30 40 50 6 0 70 80 90
Angle o f inc idence, 8 (degrees)
Fig. 2.11 Emissivities f o r air-sand interface as a function of angle of
(Used by permission of Am. S O C . for Photogrammetry and Remote Sensing.) incidence (Janza, 1975).
Lillesand et al., (1979) give typical emissivity values, the measurements
being taken normal to the surface of the objects and at a temperature of 20°C.
39
By way of illustration some of these values are given below:
Material E
distilled water 0.96
wet soil 0.95
dry soil 0.92
sand 0.90
wood 0.90
The radiometric temperature (TB) of an object can be related to the real
temperature (T or thermometric temperature) by using the emissivity values
( E ) therefore (Janza, 1975):
TB = ET (2 - 27)
The third measure of temperature is the antenna temperature or TA, as it
is measured from remote distances. This measure has to be calibrated against a
standard in the radiometer. In relating the calibrated TA with the TB of the
object, the condition of the atmosphere between the object and the antenna has
to be taken into account.
To indicate temperature change or heat transfer in a medium or a system,
a number of expressions are used.
The specific heat of a substance is the ratio of the total
quantity of heat required to produce unit temperature change in a unit mass of
that substance, to that required to produce the same change in a unit mass of
water at 15" C (Janza, 1975)
The thermal capacity or the ability of material to store heat is equal to the
product of density ( p in Kg. m-3) and specific heat: pC in Jm-3K-' (at
constant pressure; Reeves, 1975).
The thermal conductivity A in JS-lm-lK-l or Wm-lK-' is defined to be equal to
the quantity of heat that flows through a unit area of a plate of unit
thickness, having unit temperature difference between its faces. It is a
measure of the ease of heat transfer within a substance. Metals have high
conductivity values, while those of insulating materials are low.
The change in temperature caused by a certain quantity of heat flow is
expressed by the thermal diffusivity (a in m2s-l), which is equal to:
( C in Jkg-lK-')
40
The thermal inertia is a measure of the rate of heat transfer at the
interface between two dissimilar media. Materials with low thermal inertia are
relatively insensitive to change in temperature at their boundaries. They feel
cooler in the hand when hot, and warmer when cold, since the rate of heat
transfer is low.
The thermal inertia ( P in Jm-' K-' S M f ) is given by:
P = m ( 2 - 29)
Some examples may serve to illustrate the differences and relationships
between the parameters.
Materials with a low density normally have a low thermal conductivity. Cork is
extremely insensitive to heat flow, due to its high content of air. Air has an
extremely low thermal conductivity.
The thermal diffusivities of wood and brick may be the same (although wood has
a low A and pC, while brick has a high X and pC), that is the change in
temperature in these materials takes place within nearly the same period of
time. However, the thermal conductivities are very different and cause the
quantities of heat in these materials under the same temperature gradient to
be very different. The difference may be expressed by their thermal inertia
values.
2 . 8 . Atmospheric effect on EMR
The extraterrestrial solar radiation is influenced on its way to the
earth's surface by absorption, scattering, direct reflection at clouds and
refraction. Spectra of the absorptivity of the main constituents of the
atmosphere, and the atmosphere as a whole are given in Fig. 2.12.
The most important absorbers of radiation in the atmosphere are:
oxygen, ozone, carbon dioxide and water vapour.
However, the atmosphere is largely transparent between A 0.3 u m and 0.7 u m.
With increasing wavelength, more or less sharply defined absorption bands
alternate with relatively transparent zones. These transparent zones, also
known as "windows", are of great importance for remote sensing.
41
3 1
& I
.r > c, .r
a 0
VI n 4
0 1
0 1
0 1
0 1
0 0.
Fig. 2.12 Spectra of absorptivity of the atmosphere and the atmosphere as a whole (modified after Barrett and Curtis, 1976; originally Fleagle and Businger, 1963).
Scattering by atmospheric particles alters the direction of solar
radiation in a random way. Its impact is related to the wavelength of
radiation, the diameters of the particles, and the optical density of the
atmosphere as well as its absorptivity.
The three common types of scattering are (Barrett and Curtis, 1976):
- Rayleigh scattering, which refers to interactions of solar radiation with
molecules and other tiny particles with diameters much less than the
incoming radiation;
- Mie scattering, which is active in the presence of spherical particles
whose diameters approximate the wavelengths of the incoming radiation, e.g.
small water droplets (slightly overcast sky) and dust particles;
- Non selective scattering, which occurs when particles with diameters
several times the wavelengths of the incoming radiation are present, e.g.
large water droplets (clouds, fog).
Rayleigh scattering helps to explain the dominance of blue in a clear sky and
42
of orange and red at sunset. It is characterized by an inverse fourth power
dependence on wavelength (preferential re-emission). Blue light ( 4 7 0 nm) is
scattered about four times as much as red light (650 nm). Clear skies,
therefore, show up in blue, owing to the strong scattering of short wavelength
radiation. At sunset, the short wavelength is cut out mainly by powerful
scattering due to the great pathlength through the atmosphere, and only the
long wavelength radiation (including yellow, orange and red) reaches the
earth's surface.
In Mie scattering, the scattering properties of particles with identical
absorption are determined by the R/X ratio (radius over wavelength ratio).
The so-called Mie extinction coefficient u (extinction OK attenuation due to
scattering and absorption), is equal to the product of the number of particles
( N ) times the extinction cross-section:
u= N K nR2
where
K = the extin tion fa or,
KnR2 = the extinction cross-section.
( 2 - 30)
The wavelength dependency in Mie scattering is different from that in
Rayleigh scattering. In contrast to the latter, 'Mie scattering tends to
influence longer wavelengths. Generally, both are active, and, depending on
the particular atmospheric condition the colour of the atmosphere can range
from blue to nearly white.
Non-selective scattering causes all wavelengths of the Visible radiation
to scatter with equal efficiency. As a consequence clouds and fog appear
whitish, since a mixture of all colours in approximately equal quantities
produces white light.
Differences in intensity of solar radiation at the surface of the earth
may be due to one or more of the following aspects (see Robinson, 1966 and
Gibson, 1978) :
- variations in the radiant emittance of the sun;
- variations in the distance between earth and sun;
- amount of water vapour in the atmosphere;
- dustiness of the atmosphere;
- altitude of the sun depending on latitude and time o f day;
43
- elevation of the surface.
The amount of water vapour and the dustiness of the atmosphere may be
expressed by the optical transmittance, while the altitude of the sun and the
elevation of the surface are factors which determine the path length through
the atmosphere.
Yost and Wenderoth (1969) discuss the spectral distribution with time of day
and with atmospheric conditions at Davis, California on 31 July 1967.
From Fig. 2.13, the wide variation i n spectral distribution which may occur
during a clear day is evident. There is a relative increase i n transmitted
Infrared radiation at 750 nm in the afternoon (16.00 and 17.00) as compared
with that i n the morning. This is thought to be caused by strong scattering of
the Visible radiation by relatively large dust particles which have been
churned up in the fields during the day.
m v ) Q L W a J m c , I a J O E L O u s .- m E C
C \
E h U m-. L W s aJ
'7 N
140 1 t ime o f day
120
100
80
60
40
20
0
- - 09.30 ....... 09.55
upper cu rve 12.05 ----I600 - 1zoo
350 450 550 650 750 850 950 1050 1150 Wavelength i n nanometers
Fig. 2.13. Spectral distribution of incident solar radiation (during a clear day, 31 July 1967) at Davis, California, after Yost and Wenderoth (1969). Reprinted from 'Remote Sensing in Ecology', edited by Philip L. Johnson, 0 1969 the University of Georgia Press. Reprint- ed by permission of the University of Georgia Press.
It will be evident that the spectral distribution with respect to the
local conditions have to be taken into account in quantitative studies on
remote sensing.
44
c.. ‘ rNE 6 0 - x u m-. L W S 0
c, 40 - S W -0
u S
- .r
H
20 -
0
The spectral difference between direct solar radiation and diffuse
skylight, which is the only illuminant of shady areas, is illustrated in Fig.
2.14. The shady areas are low-intensity regions with a spectrum that shows a
maximum in the blue region. Sensing in the blue may therefore reveal specific
properties in these areas.
I \ I
I I
\ ‘\ ./ \ \ \
I \ I \ I \
I \ I \
\ I I
I
I \ ,’--, \- 1 \
\ \ \ \ \ -
I 1 I 1 1 I > I
V I V ) c , L c , a J
/-. I ‘.
. , \
\
45
Furthermore, the high penetration capability of Microwaves for rain is evident
from the data given in Fig. 2.16, e.g. microwaves with X = 3 cm at heavy rain
and X = 6 cm at excessive rain, only show 0,5 dB/km attenuation. This helps to
explain the enormous advantages of the application of radar in the wet
aequatorial areas with tropical rainforest.
4 Microwaves -- I n f r a r e d - wavelength (m)
10 cm 1 cm 1 mm 100 pm 10 pm
500
200 100
50
20
10
5
2
1
0.5
0.2 0.1
0.05
0.02 0.01
2 3 5 10 1 o 2 l o 5 Frequency ( GHz)
Fig. 2.15 Atmospheric attenuation (dBkm-l) for a horizonta path at a temperature of 293 K and a watercontent of 7.5 gm-' (Krul, 1982; derived from Preissner, 1978); dB = 10 log Pl/P2, where P1 = power top atmosphere and P2 = power after passage of 1 km atmosphere.
2.9 Energy balance
With the information given in the previous sections, a two-dimensional
model on the interaction of solar radiation with the earth's surface can be
composed; such a model is given schematically in Fig. 2.17.
46
L 0 r m L 0 + E
m
h
Y ... -0 v
K 0
c,
3 K aJ c, c, m
u + V W a
wl
.,- m
.C
.r
50
20
10 5
2
1
4 Microwaves - Infrared - - Wavelength (m)
1 0 cm 1 cm 1 mm 100 pm 10 pm
2 3 5 10 1 o2 1 o3 lo5 Frequency (GHz)
Fig. 2.16 Atmospheric attenuation for different rain intensities and for f w or drizzle conditions (Krul , 1982; derived from Preissner, 1978).
On its way down to the earth's surface, the incoming solar radiation is
altered by the various processes active in the atmosphere. The radiation which
reaches the earth's surface under clear weather conditions, is composed of a
direct and a diffuse component. Interaction with objects at the earth's surface
causes the incident radiation to be reflected, refracted, absorbed or
transmitted. The absorbed energy can be reradiated (emission).
The interaction process is guided by the following principle: the energy
sum of the different components active in the interaction is equal to the sum
of the incident energy. However, over a certain period of time, there can be a
gain in radiation upon interaction, the so-called net radiation (k in wm-2), which is composed of the following components (Janza, 1975):
47
J transmission Fig. 2.17 Two dimensional interaction model of solar radiation with an object
at the earth’s surface.
(2 - 31) R,, = Ris + Rid + Rit - [ P (Ris + Rid) + Rot 1 where Ris = incident direct solar radiation (Wm-’);
Rid = incident diffuse solar radiation (Wm-’);
Rit = incoming longer wavelength radiation (Wm-’) ;
Rot = outgoing longer wavelength radiation (Wm-*) ;
p = reflectance of the surface.
48
The net radiation is used for a number of processes (Janza, 1975):
Q = S + A + LE + P + M ( 2 - 32)
where
S = heat radiation from or into the soil ( ~ J I I I - ~ ) ,
A = heat radiation from or into the air (Clm- ),
LE = radiation used for evapotranspiration (Ilm-2),
P = radiation required for photosynthesis (Wm-2),
M = radiation required for miscellaneous conversions (Wm-2).
2
2.10. Spectral reflectance
By way of introduction to chapter 3, spectral reflectance is treated
below by giving a summary of spectral features. The spectral reflectance is
the ratio of the radiant energy within a specific wavelength range reflected
by a body, to the incident energy within the same wavelength range.
Spectral reflectance curves may be used to indicate spectral properties. The
curves may be characterized by features like absorption maxima, denoted below
as bands. A summary of these features in the 0.4-2.5 um wavelength region is
given in Fig. 2.18. The bands found in this spectral range are related to the
presence of H20, Fe(II), Fe(III), OH' OK C03" in solid matter (see Fitzgerald,
1974).
The bands generated by electronic processes (see par. 2.4) in solid
matter are generally broad and OCCUK in the Ultraviolet, extending less
frequently into the Visible and near Infrared with a band at 1.1 m as a limit.
The ground state of ferrous iron in an octahedral electrical field splits into
two levels. The transition allowed between these levels gives rise to the band
at 1.1 urn.
Transitions between the remaining levels of ferrous iron do only result in
very weak bands at 0.43 urn, 0.45 urn, 0.51 !m and 0.55 um. Furthermore, an
additional band can be produced at 1.8-1.9 urn in a highly disordered
octahedral site.
Ferric ion has a ground state that will not split in any crystal field.
Transitions to higher levels appear only weakly in the spectrum, e.g. at
0.4 urn and at 0.7 urn. Other transitions 3re observed at 0.45 m, 0.49 m and 0.87 urn.
49 ...
FQ Fe"' Fy .. .. ... .. .. I I ! ! ! I ! ! I
I I 1 0.4 pm 0.6 0.8 1 .o
- o f C O i I--.--.-+ OH '
Fp' H-0 H,O O H ' OH' 1 1 L A
9 ' 1
1 I' I' 1.0 pm 1.5 2.0 2.5
s t r o n g weak I broad band
1 I s h a r p band
Fig. 2.18. Absorption bands due to electronic and vibrational processes in the 0.4 - 2.5 urn wavelength range of the EMS.
The bands produced by vibrational processes in solid matter are relatively
sharp. The vibrational features observed in reflectance spectra in the Visible
and near Infrared are due to overtones or combination tones of H 2 0 , OH' and
C03" . The fundamental vibrational bands can be found in the mid- and far
Infrared. Overtones occur when a fundamental mode is excited with two or more
quanta. Combinations occur when two or more fundamental modes and/or overtones
of different modes are added or subtracted.
Water molecules may occur at various sites in minerals:
- as free molecules in small interstices or pockets (e.g. in quartz);
- singly or in clusters as a part of the crystal lattice (e.g. gypsum);
- in specific sites in the crystal lattice without being essential to its
structure (e.g. in zeolites);
- physically adsorbed at the surface of mineral grains and between the layers
of layer-silicates.
The variety in sites also leads to a variety in frequencies of the fundamental
modes. In the near Infrared, two water absorption bands occur at 1.4 urn and 1.9 um, respectively, due to overtones or combination tones of the water
fundamental. When these bands are sharp, the water molecules are supposed to be
located in well defined ordered sites. Broad bands indicate the water
50
molecules to be relatively unordered and at various sites.
The vibration of the hydroxylgroup, the OH stretching mode, results in
bands at 1.4 um and 2.8 vm. Combination of the OH stretching mode (at 1.4 m)
with lattice vibrational modes, produces a band at 2.2 Itm.
Layer-silicates and micas show OH-groups which are strongly direction-
oriented. Variation in the orientation of the OH-groups, due to Si-A1
substitution, produces a broadening of the band at 1.4 Lim.
Furthermore, overtone and combination tones of internal vibrations of C03
anion radical, or with the lattice vibrations, result in bands between 1.6 ~m
and 2.5 Lim.
I ,
Data on spectral features covering most of the Infrared region are given
by Kahle et al., (1980) and Siegal et al., (1980). A summary is presented in
table 2.3 . Interesting is the possibility of detecting gypsum by using near
Infrared radiation.
Silicates show intense absorption due to the silicon-oxygen Stretching
vibration at 10 um. However, at the onset of this absorption band at 7-9 m,
they show a peak in reflection.
Below, some attention is paid to an important constituent of soils:
organic matter. Schmitzer et al., (1972) and Flaig et al., (1975), present
data on the spectral reflectance of soil organic matter.
Soil organic matter is composed of :
a) nonhumic substances such as carbohydrates, proteins, peptides, amino-
acids, fats, waxes, resins and pigments;
b) humic substances being humic acids, fulvic acids and humins.
The assignment of specific absorption bands is limited by the fact that in
most cases, soil organic matter consists of mixtures of complex molecules, and
therefore shows overlapping of absorption bands.
To get an impression of its complexity, the main Infrared absorption
bands of humic acids are given in table 2.4. In addition to the modes
presented in this table OH and Si-0-Si are frequently found in soil organic
matter. The utility of the bands in table 2.4 has to be tested for remote
sensing.
2.11. Conclusions
E M R may be generated by a change in electronic energy levels and by
changes in the vibrational and rotational energy of atoms, ions and molecules.
It occurs in wave trains or bursts of radiation that carry a radiant energy
51
Table 2.3 Summary on vibrational features according to Siegal et al., (1980).
Constituents modes
H2O
OH'
oxides hematite carbonates phosphates sulphates gypsum
silicates
symmetric stretch asymmetric stretch H-0-H bend stretching fundamental Al- OK Mg - OH bend Al - OH bend fundamental Fe-0 fundamental stretching
overtones and combination of OH stretching in molecular water fundamental bending mode of constitutional water Si-0 bending Si-0 stretching H-0-A1 bending Si-0-Si, A1-O-Si stretches (Si, A l ) - O - ( A l , Si) stretch deformation and bending modes of
O--(Al. Si)-O- 0 - ( A l , Si)-0, (Si, Al)-0-(Si, Al),
bands in m
3.106 2.903 6.08 2.77 2.2 OK 2.3 11 5 20 7, 11-12, 13-15 9.25, 10.3, 18, 28.5 9, 10.2, 16, 22.2
1.75, 2.3
6 around 5 10 11 12-15 15-20
20-40 .~ - Al, Si-0-metal valence stretching 20-40
Table 2.4 Main Infrared absorption bands of humic acids after Flaig et al., (1975).
modes - bands in um
C-H 3.25-3.30 C-H, C-H2, C-H3 3.39-3.50 carboxylate ion 3.50-4 .00 c= 0 5.80-6.10 c=c 6.10-6.3 1 NO 6.50 C=Z 6.60 C-H deformation 6.80-7.0 5 salts of carboxylic acids 7.20-7.50 co 7.80-8.80
which is proportional to the frequency and inversely proportional to the
wavelength.
Two laws of radiation for black bodies are formulated: 1) the total of
radiation emitted from a black body is proportional to the fourth power of its
52
absolute temperature; 2) the wavelength of the maximum radiant emittance of a
black body is inversely proportional to its absolute temperature.
There is a spectrum of EMR with wavelength regions such as Ultraviolet,
Visible, Infrared and Microwaves. The particular zones are essential for life
(Visible and Infrared) or are made use of for practical reasons (Microwaves
and Radiowaves).
Solar irradiance has its maximum at approx 0.5 um. Terrestrial emittance shows
a maximum which is located at approx 10 um, and has a very low energy level as
compared to solar irradiance. The atmosphere modifies solar radiation by
absorption and scattering before it reaches the earth's surface. The
absorption by atmospheric particles is relatively strong in the Infrared, but
some wavelength zones are relatively free of absorption. These are known as
windows and are of much importance to remote sensing.
Spectral reflectance may reveal specific properties of materials at the
earth's surface. However, the atmospheric windows determine its potential use
in remote sensing.
2.12.References
Barrett, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote
Coulson, K.L., 1966. Effects of Reflection Properties of Natural Surfaces in
Dekker, A.J., 1958. Solid State Physics. London, MacMillan h Co Ltd: 540 pp. Fitzgerald, E., 1974. Multispectral Scanning Systems and their Potential
Application to Earth-Resources Surveys. Spectral Properties of Materials. ESRO CR-232, Neuilly, France: 231 pp.
Flaig, W., Beutelspacher, H. and Rietz, E., 1975. Chemical Composition and Physical Properties of Humic Substances in Soil Components V o l . I. Organic Components (ed. Gieseking, J.E.) . Springer Verlag, New York: 213 PP.
Fleagle, R.G. and Rusinger, J.A., 1963. An Introduction to Atmospheric Physics. Academic Press, New York.
Gibson, H.L., 1978. Photography by Infrared. Its Principles and Applications. John Wiley h Sons, New York: 545 pp.
Higham, A.D., Wilkinson, B. and Kahn, D., 1973. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Basic Physics & Technology. European Space Research Organisation: 186 pp.
Jamieson et al., 1963. Infrared Physics and Engineering. McGraw Hill. Janza, F.J., 1975. Interaction Mechanisms. Chapter 4 in Manual of Remote
Sensing. Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 75- 179.
Jenkins, F.A. and White, H.E., 1957. Fundamentals of Optics. McGraw-Hill Book Cy, Inc., New York: 637 pp.
Jordan, E.C., Balmain, K.G., 1968. Electromagnetic waves and Radiating
Sensing. London, Chapman and Hall: 336 pp.
Aerial Reconnaissance. Applied Optics, Vol 5, No 6: pp. 905-917.
53
Systems. P r e n t i c e - H a l l I n c . , New J e r s e y : 753 pp. Kahle, A.B. and Rowan, L.G., 1980. E v a l u a t i o n of M u l t i s p e c t r a l Middle I n f r a r e d
A i r c r a f t images f o r L i t h o l o g i c Mapping i n t h e East T i n t i c Mountains, Utah. Geology. The Geol. SOC. of Amer., Boulder , Colorado: pp. 234-239.
Krul , L., 1982. F y s i s c h e Aspecten van de A a r d o b s e r v a t i e w a a r b i j de nadruk l i g t op h e t systeem. A g r i c u l t u r a l U n i v e r s i t y , Wageningen, The N e t h e r l a n d s . PAO-cursus " T e l e d e t e c t i e i n landbouw en na tuurbeheer" : 1 1 pp.
Leu, D. J . , 1977. V i s i b l e and Near I n f r a r e d R e f l e c t a n c e of Beach Sands: A s t u d y on t h e S p e c t r a l R e f l e c t a n c e / G r a i n S i z e R e l a t i o n s h i p . Remote Sens ing of Environment 6, E l s e v i e r N-Holland: pp. 169-182.
L i l l e s a n d , T.M. and K i e f e r , R.W., 1979. Remote Sens ing and Image I n t e r p r e t a t - ion . John Wiley & Sons, New York: 612 pp.
L i n t z , J.Jr. and Simonet t , D.S., 1976. Remote Sens ing of Environment, Addison- Wesley Publ. Cy., Reading, Massachuse t t s : 694 pp.
P r e i s s n e r , J., 1978. The I n f l u e n c e of t h e Atmosphere on P a s s i v e Radiometr ic Measurements. AGARD Conference Proc. No 245: pp. 48.1 - 48.14.
P r i n s , J . A . , 1955. Grondbeginse len van de hedendaagse Natuurkunde. \ J o l t e r s , Groningen, Nederland: 320 pp.
Reeves , R.G., 1975. G l o s s a r y i n Manual of Remote S e n s i n g Vol. 11.. Amer. SOC. of Photogrammetry, F a l l s Church, V i r g i n i a ; pp. 2061-2210.
Robinson, N. (ed . ) , 1966. S o l a r R a d i a t i o n . E l s e v i e r Publ. Cy., Amsterdam:
Schawlow, A.L., 1968. Laser L i g h t . S c i e n t i f i c American. Vol. 219, n r . 3: pp.
Schmi tzer , M. and Khan, S.U., 1972. Humic S u b s t a n c e s i n t h e Environment.
S c h u r e r , K. and Rigg, J . C . , 1980. Grootheden en Eenheden i n de Landbouw en
S e l l e r s , W.D., 1965. P h y s i c a l Cl imato logy . Univ. of Chicago P r e s s , Chicago. S i e g a l , B.S. and G i l l e s p i e , A.K., 1980. Remote Sens ing i n Geology. John Wiley
& Sons, New York: 702 pp. Ulaby, F.T., Moore, R.K., Fung, A.K. , 1981-1982. Microwave Remote Sens ing
Vol. I and I1 Addison-Wesley Publ . Cy., London: 1064 pp. Weast, R.C. ( e d . ) , 1974. Handbook of Chemistry and P h y s i c s . CRC P r e s s ,
Cleve land , Ohio. Weisskopf , V.F., 1968. How l i g h t i n t e r a c t s w i t h Matter. S c i e n t i f i c American,
Vol. 219, n r . 3: pp. 60-71. Yost , E. and Wenderoth, S. , 1969. E c o l o g i c a l A p p l i c a t i o n s of M u l t i s p e c t r a l
Color Aerial Photography. I n : Remote Sens ing i n Ecology ed . by P.L. Johnson, Athens, Univ. of Georgia P r e s s : pp. 46-62.
347 pp.
120-136.
Marcel Dekker, New York: 327 pp.
B i o l o g i e . Pudoc, Wageningen, The N e t h e r l a n d s : 121 pp.
2 .13 .Addi t iona l r e a d i n g
Bazarov, I.P., 1964. Thermodynamics. Pergamon P r e s s , London: 287 pp. R.I.P.M., 1977. The I n t e r n a t i o n a l System of U n i t s (S.1.). 3rd edn. H.M.S.O.
London. I.S.B.N. 0-11-480045-6: 54 pp. Colwel l , R.N., 1963. Report of Subcomm. I. Bas ic Mat te r and Energy R e l a t i o n
s h i p s Involved i n Remote S e n s i n g Reconnaissance. American S o c i e t y of Photogrammetry: pp. 761-809.
D i t c h b u r n , R.W., 1976. L i g h t . 3rd edn. Vol. 1 and 2. Academic P r e s s , London
Feynman, R.P., Le ighton , R.B. and Sands, M., 1970. The Feynman L e c t u r e s on P h y s i c s . Mainly Mechanics, R a d i a t i o n and Heat. 5 t h edn. Adison Wesky Publ. Cy, Menlo Park , C a l i f o r n i a .
775 pp.
54
Heel, A.C.S. van and Velzel, C.H.F., 1967. Wat is licht? Wereldakademie, W. de
Goody, R.M., 1964. Atmospheric Radiation. Oxford, Clarendon Press. Holz, R.K. (ed.), 1973. The Surveillant Science. Remote Sensing of the
Environment. Houghton Mifflin Cy, Boston: 391 pp. Kronig, R. (red.), 1962. Leerboek der Natuurkunde. Scheltema & Holkema N.V.,
Amsterdam: 891 pp. Longhurst, R.S., 1962. Geometrical and Physical Optics. Longmans, Green and
Co. Ltd London: 551 pp. LOOK, G.P., de, 1983. The Dieletric Properties of Wet Materials. IEEE Trans.
on Geoscce and Remote Sensing, Vol. GE-21, No. 3: pp. 364-369. Meyer-Arendt, J.R., 1972. Introduction to Classical and Modern Optics.
Prentice-Hall International Inc., London: 558 pp. Monteith, J.L., 1973. Principles of Environmental Physics. Edward Arnold
(publ.) Ltd, London: 241 pp. Peake, W.H. and Oliver, T.L., 1971. The Response of Terrestrial Surfaces at
Microwave Frequences. Ohio State Univ. Electroscience Lab., Tech Rep. AFAL-TR-70- 30 1.
Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. American Society of Photogrammetry. Falls Church, Virginia. Vol. I: 867 pp.
Rudd, R.D., 1974. Remote Sensing. A better View. Duxbury Press, North Scituate, Masachusetts: 135 pp.
Wade, F.A. and Mattox, R.B., 1960. Elements of CKystallOgKaphy and Mineralogy. Harper & Brothers Publ., New York: 332 pp.
Wahlstrom, E.E., 1954. Optical Crystallography. 2nd edn., New York, John Wiley & Sons Inc.: 247 pp.
White, D.C.S., 1974. Biological Physics. Halsted Press. New York: 293 pp.
Haan/J.M. Meulenhof: 245 pp.
55
3. DATA ON INTERACTION OF SHORT WAVE ELECTROMAGNETIC RADIATION WITH NATURAL
OBJECTS.
In this chapter, emphasis is given to the results of laboratory
measurements on reflectance and thermal parameters. The ranges of the EMS
covered are those between 0.4-2.5 urn and 8-14 um , which form important
portions of the spectra of solar irradiance and earth emittance.
In par. 3.1, minerals as constituents of rocks and soils are discussed. Later
on in par. 3.2, the reflectance and thermal properties of soils are dealt with,
being highly influenced by moisture condition, organic matter content,
structure and texture.
A summary on the properties of plants and plant canopies is given in par. 3.3.
Laboratory measurements normally concentrate on individual components or
combinations of these representing part of the natural variation. The
laboratory details have to be transformed to the assemblage of components as
depicted by remote sensing aids (par. 3.4). This chapter, therefore, is a
transition between interaction theories (chapter 2) and remote sensing data
such as given in the chapters 9-11.
3.1. Interaction of short wave radiation with minerals and rocks.
sF!ectELrerlect2_nce Minerals occur in cemented granular form in duricrusts and hard rocks or
in loose granular form in unconsolidated sediments, rotten rock and soils. A
comprehensive text on the Visible and Near Infrared spectral features of
minerals is given by Hunt, Salisbury et al., (1970-1976). A summary of part of
their work is provided by Fitzgerald (1974) .
Below a brief treatise is given on the spectral properties in the Visible
and Near Infrared of dominant minerals such as:
- quartz and feldspar;
- amphibole and pyroxene;
- mica and layer-silicates;
- limonite;
- carbonate and gypsum.
Quartz shows a very high reflectance and the spectrum in the Visible and
near Infrared is almost devoid of spectral features (such as absorption maxima
denoted as bands), unless impurities occur. The same is true for feldspar.
56
8 v
a, V S
rn + 50-
7
le a, E
0 , I I I 1 I I I
Only, water-bearing fluid inclusions and contamination by iron result in
spectral features.
Amphibole shows a band near 1 urn, indicating that it contains ferrous
ions. It displays a very sharp hydroxyl band at 1.4 um and less sharp bands
between 2.0 um and 2.5 urn. The latter are due to overtone and combination tones
of the OH stretch. The bands mentioned are characteristic for the variety
Tremolite.
Another variety, Actinolite, shows in addition a broad band near 0.7 wn due to
the presence of ferric ions (see fig. 3.1.a).
Pyroxenes do not show the hydroxyl bands unless some alteration has taken
place. The relatively high content of iron is expressed by a broad band at
0.9 um, and in the variety Hypersthene by an additional broad band at 1.8 rn which is probably due to ferrous ions in a highly disordered octahedral site
(see fig. 3.1.b).
h
Amphibole, v a r . A c t i n o l i t e Pyroxene, v a r . Hypersthene
A i n p m A i n pm
(a) (b)
Fig. 3.1 Reflectance (relative to MgO) of Amphibole, var. Actinolite, and Pyroxene, var. Hypersthene; grain size 74-250 prn (after Hunt and Salisbury, 1970).
The mica var. Muscovite displays hydroxyl bands at 1.4 pm as well as between
2.2 um and 2.6 um. Biotite may show a much broader hydroxyl band and in
addition shows a very broad band in the 0.6 to 1.5 urn region, due to ferrous
and ferric ions.
Layer-silicates are characterized by hydroxyl bands centered near 1.4 ~rm
and 2.2 D m.
Absence of appreciable amounts of bound water is typical for Kaolinite. There-
fore, it shows only a weak band at 1.9 u m (fig. 3.2.a). On the contrary
57
Montmorillonite is capable of holding much water and may show very strong bands
at 1.9 um as well as at 1.4 u m (see fig. 3.2.b). The band near 1.15 u m is also a waterband, where as the bands at 0.9 u m and 0.5 u m are due to the
Kaolinite
0.5 1.0 1.5 2.0 2.5
A in pm
Montmorilloni te
1
1 I I I I I
0.5 1.0 1.5 2.0 2.5
A in prr
Fig. 3.2 Reflectance (a) (relative to MgO) of Kaolinite (b ) and Montmoril- lonite; resp. with grainsize 0.1-5 u m and 0.1-74 u m (after Hunt and Salisbury, 1970)
presence of ferrous ions.
Limonite is often used to indicate hydrated ferric oxide material while
goethite is synonymous for the ferric oxide hematite. The water content of
limonite is variable. The band at 0.9 u m typical of the ferric oxides and
hydration bands near 1.4 u m and 1.9 u m may show up in the spectra.
Calcite exhibits carbonate bands between 1.8 u m and 2.5 LI m, and may
display a very weak hand of ferric ion a t 0.8 u m. The latter may be due to
iron contamination in often very small amounts. Fine grained calcite has a very
high reflectance as is shown in fig. 3.3. Note the strong absorption band at
2.35 u m.
Gypsum shows bands at 1.8 LI m and at 2.3 LI m, due to overtones and combination
of OH stretching in molecular water.
If we consider rocks, we mostly have to deal with an assemblage of
minerals, and various spectral features will occur e.g. limestones may display
carbonate bands as well as water and hydroxyl features, being dependent on the
admixture of constituents such as layer-silicates. Features due to the presence
of ferrous ions (intrinsic to the presence of clay) and ferric ions (coatings)
58
m c, u W
+ 7
50-
may also OCCUK.
Spectral emissivity - ----------------- The spectra of emitted thermal radiation from minerals are generally
characterized by emissivity minima in the 7-15 !J m region. These minima are
known as the "reststrahlen" bands and are due to vibrational transitions of the
Fig. 3.3 Reflectance (relative to MgO) of Calcite of grain size 74-250 m (after Hunt and Salisbury, 1971).
main anion of the mineral.
In silicates, the fundamental frequency of the Si-0 stretching mode occurs
near 10 !J m and the 0-Si-0 bending or deformed ion mode is found near 20 IJ m.
The fundamental Si-0 vibration near 10 !J m shifts with the type of igneous
rock. Quartz shows an emissivity minimum at 9 !J m, which is the shortest
wavelength of any emissivity minimum of silicates.
The spectral emissivity of a number of igneous rocks is given in fig. 3.4. From
this figure, we can read that the examples given of acid-igneous rocks
have emissivity minima from 8.8 to 9.6 u m (e.g. granite near 8.80 p m), while
those of basic and ultrabasic igneous rocks have emissivity minima higher than
10.1 !Jm (e.g. Limburgite 10.53 IJ m). The intermediate igneous rocks show minima
between 9.2 and 10.0 u m. To discriminate silicates from non-silicates, the spectral emissivity may be
used. For example, carbonates show, much contrast with silicates in having
strong absorption at 7.0 iI m.
The diurnal variation in surface temperature changes of rock formations is
59
the most significant short term variation in rock properties that can be used
in remote sensing. The difference in the amplitude of the diurnal variation in
temperature between rocks is due to their differences in thermal inertia. The
thermal inertia (2-29) is a function of the thermal capacity and conductivity
as influenced by porosity, texture, structure, chemical composition and
> c,
> In In
.I-
.I-
.I-
E W
7
m L c, u W
Ln n
L 1 . 1
Andesi t e Nephe l ine Syen i te
Hypersthene Andesi t e ~
INTERMEDIATE ROCKS
% 10.53
Q u a r t z A u g i t e
Aug i t e ---
B a s a l t
D i o r i t e D i o r i t e
D i o r i t e -----
BASIC
1 --- I
1 ROCKS
-----------
i P e r i d o t i t e Serpent ine
Limburg i t e ULTRABASIC ROCKS
1 _ _ _ - - - - - - - - I
1 1 I I , ,
8 9 10 11 1 2 1 3 pm
Fig. 3 . 4 Spectral emissivities of igneous rocks from 8-13 m (modified from Lyon, 1965)
60
moisture content. The day-night temperature difference can be used to calculate
the thermal inertia of surface materials.
3 . 2 Interaction of short wave radiation with soils.
The interaction of solar radiation with soils plays an important part in
soil forming processes and more specific in the heat balance of soil.
The dry/wet soil colour designations are actually observations on spectral
reflectance, which may indicate the presence of organic matter and of oxidized
OK reduced iron compounds.
Although soils are composed of granular mineral materials which are
generally mixed in their surface layers with organic matter, their reflectant
and emittant properties are greatly influenced by moisture condition, texture
and structural arrangement of the constituents which often predominate over the
effects of chemical composition.
Spectral reflectance _____-------__------ Several authors have provided spectral reflectance data of soil materials
which have been obtained under laboratory conditions (Orlov, 1966; Planet,
1969-1970; Skidmore et al., 1975; Gold and Asher, 1976). I will first
concentrate on spectral features which are due to chemical soil composition:
Obukhov and Orlov (1964) present some curves in the spectral zone from 0.40 to
0.75 um, of which the results are given in fig. 3.5.
Three types of curves are distinguished in this wavelength range:
a) monotonously rising curves, from short to longer wavelengths; the slope of
the curves becomes somewhat weaker at the longer wavelength end (fig. 3.5 nrs
1, 3 and 6) ;
b) a curve with minor slope and low reflectance values (fig. 3.5 nr. 4 ) ; the
low reflectance values apparently are due to the high content of organic
matter;
c) the type of curve represented by nr. 5 in fig. 3.5; the slope of the curve
increases at a moderate rate up to about 0.53 LI m and then rises sharply to
about 0.58 u m, where a definite decrease of slope occurs; this type of curve is typical for samples rich in ferric ion, which show absorptance in the
shorter wavelength range and high reflection in the orange and red.
For further discussion on types of curves, one is referred also to Condit
(1972) , who gives special reference to American soils.
61
Fig. 3.5 Spectral reflectance data of Russian soils (modified sketch after Obukhov and Orlov, 1964).
1. Sod-podzolic soil, A1 0-10 cm; OM* 1.6 %; clay loam. 2. Grey Forest soil, A1 15-26 cm; OM* 3.8 %; silty clay loam. 3. Light Chestnut soil, A1 0-10 cm; OM* 2.7 %; clay loam. 4 . Chernozem, Asod 0-5 cm; OM* 10.3 %; silty clay loam. 5. Red coloured soil on limestone, A1 4-11 cm; OM* 3.2 % ; clay. 6. Light coloured Sierozem, A1 0-10 cm; OM* 1.1 %; clay loam. * OM or organic matter content.
Valuable information about the composition of soils may be obtained by
extending our view into the near Infrared. Soil reflectance spectra including
the near Infrared (as well as the Visible) are reported by several authors:
Bowers and Hanks (1965), Mathews et al., (1973), Janse and Bunnik (1974), Damen
(1975), Janse et al., (1976) and Girard (1977).
Numerous reflectance measurements of American soils in the 0.52-2.32 pm
wavelength range have been presented by Stoner et al., (1980). It has been
pointed out that soils rich in organic matter (Histosols, Mollisols) frequently
have a concave shaped reflectance curve between 0.5 P m and 1.3 P m, whereas
soils low in organic matter (e.g. Alfisols) frequently show convex shaped
curves over the same wavelength region. Ultisols often resemble the curves of
Alfisols but they additionally show weak absorption bands at 0.7 and near
0.9 P m caused by the presence of iron.
Besides the chemical composition, other soil properties such as moisture
content, texture, structure and roughness of the soil surface have a marked
influence on reflectance and thus have to be evaluated.
The influence of soil moisture content on the reflectance of silt-loam as
measured by Bowers and Hanks (1965) is often cited in literature. I present
62
the curves in fig. 3.6. The water absorption bands (1.4 and 1.9 u m) are
clearly marked as well as a weak hydroxyl band (2.2 p m). Increase of soil
moisture content results in an overall decrease of reflectance in the Visible
as well as in the near Infrared.
Damen (1975) states that soil moisture tension values are most suitable
for analysis of soil moisture, and presents spectral reflectance curves of soil
material at different soil moisture tensions. The water absorption bands are
clearly marked in the range of soil moisture tension form 0.005 bar up to 16
bar and the total reflectance, as can be expected, decreases with decrease of
Fig. 3.6
V I
h
3 60 a, V
+J u a,
m
G 40
20
0 t h (nm) Spectral reflectance of Newtonia silt-loam at various moisture contents (moisture contents indicated directly above each curve) after Bowers and Hanks (1965) .
I 1 obo 2000 Wavelength (nm) U I
Spectral reflectance of Newtonia silt-loam at various moisture contents (moisture contents indicated directly above each curve) after Bowers and Hanks (1965) .
soil moisture tension (fig. 3.7). At low soil moisture tension, water fills up
the macropores of soil (gravitational water) and strongly reduces the
reflectance. Cohesion and adhesion water, which can be held at high moisture
tension in resp. micropores and at the surfaces of soil particles, have
considerably less influence.
In fig. 3.6 it is striking that the dips at 1.4 u m and 1.9 u m become deeper
and broader with increasing moisture content. Relatively sharp absorption bands
are characteristic of low moisture contents and thus high soil moisture
tens ion.
Another remark may complete the discussion about these interesting curves. The
hydroxyl band at 2.2 um is most clear at low moisture contents (fig. 3.6); at
high moisture contents, it becomes vague. Therefore, its use in the detection
of layer-silicates may be restricted to relatively dry soils.
Texture of soils has got attention in soil reflectance measurements, too.
63
h
d?
E 6 0 - v
c m c,
u - a,
% 7
3,2 "
0,5 "
0,032 "
SMT
16 b a r - /--- ....... ...........
Fig. 3.7 Spectral reflectance in relation to soil moisture tension of a soil with a clay content of 9 . 3 X (after Damen, 1975).
Generally, fine textures show a higher reflectance than coarse textures. Leu
(1977) reports that the spectral response in the 0.43-0.47 !.I m and 0 . 5 1 - 0 . 5 3 ~
channels is correlated with the grain size of beach sands having variable
moisture contents.
A means to determine the average size of particles may be found through
application of high oblique illumination. The ratio of intenties at a forward
angle to that at a back angle can be used for this purpose. For the same mate-
rial (e.g. quartz sand), the scattered light becomes more concentrated in the
forward direction with increasing particle size (Meijer-Arendt, 1972). Besides
grain size, the reflectance of soils will also be influenced by aspects such as
sphericity, roundness (Brewer, 1964) and the micro-roughness at the surface of
the grains.
Several authors report about results of reflectance measurements in
relation to aggregate size. Orlov (1966) studied various soil samples with a
range of aggregate diameters. In general, he found for small sized aggregates a
decrease in reflectance with increasing diameter. Huwever, at large diameters
( > 2.5 mm) there was only a slight or no decrease in reflectance.
Damen (1975) has also studied the influence of aggregate size on reflectance.
Reflectance values of a loamy topsoil sample of Woudgrond with different
64
- - 2 8 6 0 - S
ru c 1 . u
aggregate sizes are given in fig. 3.8.
Furthermore, he studied soil roughness by creating fine and coarse rills on the
surfaces of samples (fig. 3 .9 ) and found the coarse rill pattern to show the
lowest reflectance.
It is evident, therefore, that the structural condition of the soil surface is
of great influence on reflectance e.g. soil surface crusts may cause high
reflectance values in the Visible (Cipra et al., 1971).
Some authors report about the variation of reflectance with the angle at
which the radiation is incident on the surface.
Coulson (1966) gives a summary of previous research and presents results on
directional reflectance of different mineral materials. Some of the curves are
shown in fig. 3.10 (angle of incidence 0 = 53") . The reflectance is measured
Woudgrond ( a i r d r y ) - c 0.3 m n ~ ............ 0.3-1 "
1 -2 " .......
Fig. 3.8 Spectral reflectance at different aggregate diameters of Woudgrond (with 7.4 % C and 12.0 % clay) after Damen (1975).
hemispherically in the principal plane, that is the plane containing the
source, the object and the measuring device.
Materials with a low absorption like gypsum sand and beach sand (quartz)
show a high reflectance and a strong forward maximum in scattering. Absorbent
materials like clay, limonite, grey limestone grit and loam show a back
scattering maximum (see also Fig. 2.10 with text).
Note that the antisource point (the point just behind the source) is indicated
in the figure by an arrow and by the break of data ( 8 of source is 53"). The
factor R in the ordinate is a normalization factor.
65
h
3 2 60- C Q CI u - a, -
Woudgrond (air d r y ) - small r i l l s medium r i l l s
0 ' I I I I
1000 2000
Wavelength (nm)
Fig. 3.9 Spectral reflectance of Woudgrond (with 7.4 %C and 12.0 X lutum) with fine and coarse rills after Damen (1975).
The magnesium oxide surface which is used as a standard reflector is-assumed to
be a perfect Lambertian reflector.
The reflectance of the standard surface,
and thus:
( pst ) is independent of direction
Ist -1 I = II ISt and p = - =
The directional reflegtance p ( 8 ,0) is given by: I "
where
p = reflectance dependent on viewed nadir angle 0 of the reflectometer and
position 0 of the reflectometer with respect to the azimuth 0, = 180"
(principal plane) of the source;
IO = intensity of the source; I and ISt are intensities of the radiation
66
Loam
t
60-
40-
20-
7
+ 80
Red clay
D' ?
80 40 0 40 80 Nadir angle (O) @=OO 4=180°
Fig. 3.10 Directional reflectance of various types of mineral surfaces (principal plane, h 643 nm, 0 = 53" ) after Coulson (1966).
Gypsum sand: translucent grains 0.1-0.5 mm Reach sand: translucent quartz grains 0.1-0.3 m Red clay: 1 wn, aggregates 1-2 mm Limonite: mean diameter 14 urn, range 3-40 um Limestone: grey coloured rock crushed and graded to 1.2 cm size Loam: 1-5 pm, aggregates 50-1000 m.
reflected from the sample and from the standard surface respectively.
Fig. 3.11 shows the directional reflectance of desert sand for radiation of
different wavelengths and for different angles of incidence. There appears to
be a strong increase of overall reflectance with increasing wavelength from 406
to 796 nm (fig. 3.11a), which is in accord with the reddish COlOUK of the
desert sand under consideration.
The broad minimum reflectance near the nadir is a general characteristic of
many surfaces. Apparently, the Lambert's cosine law (2-22), which indicates a
hemispherical distribution is not valid for granular surfaces. Furthermore, the
non-specular behaviour is evident at least in the forward direction, since the
forward maximum is found at 0 > e0 ( 0 = e0 specular point).
The backscattering maximum will be due to surface reflection being composed of
a diffuse component and a specular component. The latter component will be due
67
100
80
60
40
20
a, V c fu
(a)
4J ; 80 40 0 40 80 7
% I$=o" @= 180" CL
, ?
,
d
\'"" I
I I I I I
80 40 0 40 80
O=O" 0=l8Oo
N a d i r ang le ( " 1 Nad i r ang le ( "1 I=
Fig. 3.11 Directional reflectance from desert sand after Coulson (1966): a) of five different wavelengths (principal plane, 0 = 53"); b) for three different angles of incidence (principa? plane, A = 643
nm) . to the presence of facets which are more OK less oriented normal to the
direction of the incident radiation.
The forward maximum for wavelengths between 492 nm and 1025 nm is more
pronounced than the backscattering maximum (fig. 3.11a). The opposite is true
for radiation with A = 405 nm. A possible explanation may be found in the
presence of Fe (III), which causes absorption and strong external
backscattering in this range. However, the same should apply to the radiation
at 492 nm, which is not the case (for absorption, see Fig. 2.18). Therefore,
the phenomenon is not completely understood.
Both the total reflectance and the directional reflectance vary with the
angle 0 at which the radiation is incident, as can be seen from fig. 3.11.b.
The variance is particularly pronounced at grazing angles. In having the
highest reflectance at a grazing angle of 78,5", the surface acts in a non-
68
Lambertian way.
The degree of polarization of radiation reflected by desert sand in the
principal plane is shown in fig. 3.12. A maximum positive polarization (normal
to the principal plane) was found at 120" to 130" from the antisource
direction, while vertical or negative polarization (parallel to the principal
plane) occurred in the region surrounding the antisource direction.
Furthermore, a considerable change of the degree of polarization with
wavelength is evident, the shorter wavelengths showing a higher degree (fig.
3.17.a).
40
30
20
10
0
-5
(a)
I I 1
.r 5 80 40 0 40 80 + c c , 0 2 @=oO @=180°
Nadir angle ("1
(b)
80 40 0 40 80 4.0" 0=180°
Nadir angle ( " )
Fig. 3.12 Degree of polarization of radiation reflected from desert sand after Coulson (1966) : a) for five different wavelengths (principal plane, 8 b) for three different angles of incidente (principal
= 53" );
plane, X = 492 nm) Degree of polarization = (Ih -
\/It, + $) X 100 (%)
It appears that strongly reflected wavelengths are only weakly polarized, but
high polarization is observed at wavelengths for which the reflectance is low
69
(compare wi th f i g . 3.11a). P a r t i c l e s which show a h igh r e f l e c t a n c e f o r
r a d i a t i o n of a p a r t i c u l a r wavelength, a r e g e n e r a l l y t r a n s l u c e n t f o r t h a t
r a d i a t i o n and consequent ly have a h igh c o n t r i b u t i o n of t h e i n t e r n a l component
t o t h e t o t a l r e f l e c t a n c e . Thus any p r e f e r r e d o r i e n t a t i o n of t h e e l e c t r i c v e c t o r
i s des t royed by t h e i n t e r n a l ( m u l t i p l e ) r e f l e c t i o n . On t h e c o n t r a r y , absorbent
m a t e r i a l s have no or only a smal l i n t e r n a l component and t h e r e f l e c t a n c e i s
formed f o r t h e g r e a t e r p a r t by t h e c o n t r i b u t i o n of t h e e x t e r n a l component.
Some f a c e t s a t t h e s u r f a c e w i l l produce t r u e s u r f a c e r e f l e c t i o n , which i s an
e f f i c i e n t p o l a r i z i n g agen t . Consequently p o l a r i z a t i o n i s h igh when a b s o r p t i o n
i s high ( s e e a l s o f i g . 2 . 7 ) .
In f i g . '3.12b, t h e e f f e c t of ang le of i nc idence on p o l a r i z a t i o n i s shown. The
p a t t e r n s h i f t s wi th sou rce p o s i t i o n and always shows v e r t i c a l o r nega t ive
p o l a r i z a t i o n i n t h e a n t i s o u r c e - d i r e c t i o n . Furthermore, t h e degree of po la r i za -
t i o n i n c r e a s e s wi th t h e ang le of i nc idence .
Black loam s o i l (w i th a r e l a t i v e l y high con ten t of o rgan ic ma t t e r ) shows a low
o v e r a l l r e f l e c t a n c e wi th i n c r e a s i n g wavelength and a h a c k s c a t t e r i n g maximum
( f i g . 3.13.a). A comple te ly o t h e r p a t t e r n a s conpared wi th f i g . '3.11h. i s shown
i n Fig. 3.13.h. Although t h e t o t a l r e f l e c t a n c e appears t o he lower , t h e
b a c k s c a t t e r i n g maximum a t 8 = 53" and 8 = 7 8 , 5 " i s more pronounced than i t
i s f o r d e s e r t sand , whi le t h e forward maximum i s a lmost absen t . Fig. 3.14.a
shows a s t r o n g wavelength dependence and h igh p o l a r i z a t i o n a t t h e s h o r t e r
wavelengths f o r b l ack loam s o i l . The e f f e c t of changing 8 i s shown i n f i g .
3.14.b. A s l i g h t s h i f t i n t h e n e u t r a l p o i n t s of p o l a r i z a t i o n toward t h e a n t i -
sou rce -d i r ec t ion may be noted f o r t h e b l ack loam a s compared wi th t h e d e s e r t
sand.
It w i l l be ev iden t from t h e fo rego ing t e x t t h a t t h e r e a r e e x c e l l e n t
o p p o r t u n i t i e s t o d i s c r i m i n a t e v a r i o u s s o i l s on t h e b a s i s of r e f l e c t a n c e ( a t
l e a s t under l a b o r a t o r y c o n d i t i o n s ) a l though t h e exp lana t ion of s p e c t r a l
f e a t u r e s may be compl ica ted .
Thermal d a t a
The tempera ture of a s o i l i s one of i t s impor tan t p r o p e r t i e s i n c o n t r o l l i n g
germina t ion of s e e d s , p l a n t growth and a number of s o i l forming p rocesses . Its
importance i s expressed i n t h e U.S. S o i l Taxonomy by in t roduc ing s o i l
t empera ture regimes i n t h e c l a s s i f i c a t i o n of s o i l s ( S o i l Survey S t a f f , 1975).
The t r a n s f e r of h e a t i n t h e s o i l t a k e s p l a c e by conduct ion through t h e s o l i d
m a t e r i a l s and a c r o s s t h e pores by conduct ion , convec t ion and r a d i a t i o n
---_------__
70
100
80
60
40
796ni 'I
' t
L
c,
al
m J 1 1 1 1 I
u 80 - + I&$ @=180° 40 0 40 80
ar CL
(b)
J I I I I
80 40 0 40 80
Q=O" @= 180'
N a d i r ang le ('1 N a d i r ang le ('1 k
Fig. 3.13 Directional reflectance of black loam soil after Coulson ( 1 9 6 6 ) : a) for four different wavelengths (principal plane, eo = 7 8 , 5 " ) ; b) for three different angles of incidence (principal
plane, X = 643 nm)
together, as well as by latent heat transport (water vapour). The effect of
soil mineralogical composition on the thermal behaviour may be evaluated from
the emissivity values. In table 2.3, a number of absorption bands are given,
which, in the 8-14 pm region, are due to the presence of silicates,
carbonates, sulphates OK phosphates. The effect of the composition of igneous
rocks on the emissivity ( E ) may be evaluated from Fig. 3.4. Difference in
composition may lead to difference in E of 0.15, while the emissivlty minimum
differs from the maximum by values of 0.15-0.3.
E values of soil materials for the spectra- region between 5 mn and 15 WI
are reported (by Idso e.a., 1969) to be from 0.95 for sand up to 0.97 for silty
clay and loam.
Quartz sand shows a relatively low emissivity. Fuchs et al., ( 1 9 6 8 ) report fOt
the socalled Plainfield sand the following values for three different moisture
contents: moisture content 0.7% 5.8% 8.4%
E (emissivity) 0.90 0.92 0.94
4[
3c
2c
10
0
-5
0'
.l I I I I
71
I
I I I I 1
0 40 80 @=180°
Q) 'r Q ) L s - m N a d i r a n g l e ( " ) N a d i r a n g l e ( " ) Ez-,g n a-
Fig. 3.14 Degree of polarization of radiation reflected from black loam soil after Coulson (1966) : a) for four different wavelengths (principal plane, 8 = 78,5"); b) for three different angles of inciden2e (principal
plane, b = 492 nm)
Monteith (1973) describes the thermal properties of soil as follows. If
the volume fraction x of each component is expressed per unit volume of soil,
one can write:
where s stands for solid, 1 for liquid and g for gaseous components of soil.
The bulk density of a soil p ' is found by adding the weight of each component
i.e. p ' = pSxs + plxl + P x
where p x can be neglected. g g
g g
( 3-3)
12
bulk specific heat C'. It can be found by adding the specific heat (C) of the
soil components, as follows:
Van Wijk and de Vries (1963) present values on thermal properties of soils
(which are also discussed by Monteith, 1973). They are given in table 3.1 (for
definitions, the reader is referred to par. 2.7).
The effect of soil composition on thermal properties can be evaluated to some
Table 3.1 Thermal properties of soils and their components (after Van Wijk and De Vries, 1963)
Density Specific Thermal The r ma 1 heat conductivity diffusivity
Soil components Quartz 2.66 0.80 8.80 4.18 Clay minerals 2.65 0.90 2.92 1.22 Organic matter 1.30 1.92 0.25 1 .oo Water 1 .oo 4.18 0.57 0.14 Air (20'C) 1 .20~10-3 1 .O 1 0.025 20.50
Soils Water content g 0 - 3
Sandy soil 0.0 1.60 0.80 0.30 0.24 (40% pore space) 0.2 1.80 1.18 1 .80 0.85
0.4 2.00 1.48 2.20 0.74
(40% pore space) 0.2 1.80 1.25 1.58 0.53 0.4 2.00 1.55 1.58 0.51
Peat soil 0.0 0.30 1.92 0.06 0.10 (80% pore space) 0.4 0.70 3.30 0.29 0.13
0.8 1.10 3.65 0.50 0.12
Clay soil 0.0 1.60 0.89 0.25 0. i a
extend from these data. Quartz and clay minerals show similar density and
specific heat. Quartz sands tend to have larger thermal diffusivities than
other soil types due to the high conductivity of quartz. Organic matter shows
about half the density and more than twice the specific heat of quartz and
clay. Peat soils have the smallest thermal diffusivity, because the
conductivity of organic matter is relatively small.
73
Soil moisture is one of the most important factors influencing the thermal
characteristics of soil. The thermal conductivity increases with increasing
moisture content, but the increase becomes less marked with high moisture
contents. This can be understood if one compares the data of the soil
components in table 3.1. The thermal conductivity of air is much lower than
that of water. Therefore, dry soils, in which air is filling the pores, have
relatively low thermal conductivities. Raising moisture content will first
result in much higher values due to the presence of thin waterfilms conducting
the thermal energy. High moisture contents with a consequent almost complete
filling of pores with water, only produces a slight increase in conductivity.
In dry soils, high porosity will lead to low thermal conductivity. The relation
! ! I I ! 20 30 40 50 60 70 80
P o r o s i t y (%I
Fig. 3.15 Relation between soil porosity and thermal conductivity of dry soils after Chudnovski (1962).
Normally, the porosity of non-cultivated soils is at 30-40 %, while in
cultivated soils values of 40-60 % OK more are reached. Therefore, it may be
concluded that the increase of porosity by cultivation practices will lead to a
decrease in thermal conductivity.
The soil heat-flux shows seasonal and diurnal cyclic patterns. At mid
latitudes, the greatest positive heat-flux OCCUKS in spring and early summer;
the greatest negative heat-flux OCCUKS in early winter.
At low latitudes, the seasonal fluctuations are relatively small. Minor
74
fluctuations are illustrated in fig. 3.16 for Yangambi (Zaire) at a latitude of
0,47"N and an altitude of 365 m above mean sea level. The curves show that the
60
2 50 W V
L a, n
40
20
Fig. 3.16 Mean monthly soil temperature at a depth of 50 cm for the year 1952 at Yangambi, Zaire, and major climatic factors that affect it (Soil Survey Staff, 1975 after I.N.E.A.C., 1953).
mean monthly soil temperature at a depth of 50 cm below the s o i l surface
fluctuates with rainfall and amount of sunshine (dependent on cloud cover).
Apart form seasonal fluctuations, the diurnal fluctuations are of great
importance for the process of heat exchange. Fig. 3.17 shows temperature
profiles of s o i l and air near the ground for a clear midsummer day and night at
mid-latitudes. Several features can be deduced in the diurnal temperature
profiles of this figure, such as:
- the positive heat-flux with regard to the topsoil after sunrise; - the strong positive heat-flux during the early afternoon; - the negative heat-flux after sunset; there is an upward movement of heat; - the strong negative heat-flux before sunrise; during the night the
temperature of the subsoil is raised at the cost of the topsoil;
- the diurnal amplitude of soil temperature oscillations is retarded with soil depth.
15
Fig. 3.17 illustrates a specific case of radiation and soil profile; there are
no general features as far as numerical values are concerned; the depths
indicated depend on thermal inertia.
h
E U
U S 2 0 L 01
W > 0
m c, r 01
W 1
v
n
.r
- E V
U S 2 0 L rn x 0
a,
r c, P W
v
7
n
n
140
120
100
80
60
40
20
0
-20
-40
-60
-80
-100 10 20 30 40
Temperature ("C)
Fig. 3.17 Temperature profiles of soil and air near the ground for a clear midsummer day and night at midlatitude (Fitzgerald, 1974 after Gates, 1970).
3.3. Interaction of short wave radiation with plants
Spectral reflectance .................... The reflectance characteristics and thermal emission of plants are
extensively discussed a.0. by Fitzgerald (1974). In this text only a summary
is given.
A cross section of a typical leaf is shown in fig. 3.18. The upper and
76
lower epidermis have a mainly protective function with regard to the
interaction with electromagnetic radiation, the mesophyll region i s the most
important part. The mesophyll contains the plastid and vacuolar pigments.
The plastid pigments are concentrated near the cell walls, while the vacuolar
pigments are distributed uniformly throughout the cellular protoplasm.
The most important plastids are the chloroplasts (disc-shaped, 5-8 !J m in
Chloroplasts Air cavity Guard ce l l s Upper epidermis
Air ca'vity Lower epidermis
Fig. 3.18 Scheme of morphological structure of a plant leaf after Fitzgerald ( 1 9 7 4 ) .
diameter and 1 !J m thick). Within the chloroplasts are grana, in which
chlorophyll is located (these grana are 0.5 !J m long and 0.054 !J m in
diameter). Chlorophylls form about 65 X of the leaf pigments. The other most
common plastlds are the carotenoids, which are yellow to orange red in colour,
and are the chief colourants in plant leaves in the absence of chlorophyll.
The main vacuolar pigments are anthocyanines and anthoxanthlns, which are
normally red and blue In colour. The colour of leaves in autumn I s due to
71
carotenoids, whether OK not in combination with anthocyanines and
anthoxanthins.
The upper portion of the mesophyll, the palisade layer, consists of closely
packed elongated cells with their long axis perpendicular to the leaf surface.
It shows a concentration of chloroplasts, which strongly absorb the Visible
radiation.
The lower mesophyll, the spongy mesophyll, has a less compact cellular
arrangement and the intercellular spaces are larger as compared with the
palisade layer. This is the main transpiring tissue of the leaf, which shows a
low concentration of chloroplasts and has a light green colour.
Fig. 3.19 shows a typical reflectance spectrum of a normal healthy plant
leaf together with the absorption spectrum of water.
Wavelength (pm)
Fig. 3.19.Reflectance spectrum of a typical green leaf and the absorption spectrum of water in the spectral range of wavelengths 0.4-2.6 LI m after LARS (1968).
78
The spectrum of a plant leaf can be divided into the following ranges:
- the range between 0.4 !J m and 0.7 p m, which is characterized by
very low reflectance due to intense absorption of the incident
radiation by pigments in the plant;
- the range between 0.7 u m and 1.3 u m, which is characterized by
- the range between 1.3 u m and 2.6 u m, which is characterized by very little absorption and high reflectance;
pronounced minima.
The reflectance and absorptance of plant leaves is mainly determined by:
- the pigmentation; absorptions are caused by electron transitions
within the pigment molecular complexes (Fitzgerald, 1 9 7 4 ) ; all
pigments absorb at 0.43 - 0.44 IJ m, but chlorophyl has an additional
band at about 0.66 !J m; reflection of green radiation is produced by
the chloroplasts;
the mesophyl structure, which causes multiple reflection of near
Infrared radiation at cell walls;
the water content; the most intense absorption bands occur at
1.4 IJ m and 1.9 IJ m;
the surface properties of the leaf; a matt surface approximates a
perfect Lambertian diffuser more closely than a glossy surface does;
the latter shows a prominent specular component in the reflected
radiation.
Normally, the energy absorbed is converted by photosynthesis into heat and
stored energy. However, chlorophyll is capable of releasing some of the
absorbed energy by fluorescence. There are two types of chlorophyll:
chlorophyll-a and -b. Chlorophyll-a shows strong absorption maxima at 0.43 IJ m
and 0.66 IJ m. Chlorophyll-b shows a strong absorption maximum at 0.64 IJ m. I n
most plants the content of chlorophyll a : b is 3 : 1, so chlorophyll-a largely
determines the absorption. Both types of chlorophyll show typical fluorescence
spectra, namely:
chlorophyll (a) with maxima at 668 nm and 723 nm;
chlorophyll (b) with maxima at 648.5 nm, 672 nm and 705 nm.
The spectral reflectance of leaves undergoes strong changes both early and
late in the growing season. Gates ( 1 9 7 0 ) provides data on these changes for
Quercus Alba (white oak). The data are presented in Fig. 3.20.
79
- 100 2 aJ V E
c, V
m
60
40
20
h
J
I I
I I I 1 ! I I 0.4 0.5 0.6 0.7 0.8 0.9 1 . a 1.1
40
20
1 I I I I I r I L
- 19 June 20 July 18 August 18 September
21 October
-- -_-__ . . . . . . . . . .
I 7 October ,
28 October 2 November t -.-
0 1 I I I I I I 0.4 0.5 0.6 0.7 0.8 0.9 1 .o 1.1
Wavelength (pm)
Fig. 3.20 Changes in spectral reflectance throughout the growing season of leaves of Quercus Alba after Gates (1970) .
The juvenile leaf has a dense covering of pubescence and shows a relatively
high reflectance in yellow and red, and a very high reflectance in near
Infrared. As the leaf grows and expands, the hairs spread out, the near
80
Infrared reflectance drops, some absorption takes place by chlorophyll and the
green reflectance increases. Later on a further increase in blue and red
absorption accompanies a slight reduction in green reflectance and a visible
darkening of the leaf (May 11 and 18). At this time, the number of reflecting
surfaces has increased, resulting in an increase of the near Infrared
reflectance.
During the growing season from May 18 to October 21, the spectral reflectance
curves remain nearly constant. On October 28, the end of the growing season
presents itself by a break-down of chlorophyll, as is illustrated by the shift
of the green peak towards yellow and orange wavelengths (Anthocyanins are
formed which absorb blue and green). Furthermore, there is a reduction in
reflectance at 0.8 u m upon pronounced drying. However, the reflectance at
1.0 u m remains constant. The curves of fig. 3.20 give a good impression of
these changes in leaf reflectance throughout the growing season.
In remote sensing, however, we have to deal with the reflectance of a plant
canopy, which is determined by plant variables such as leaf area and
orientation of leaves and stems.
It is obvious that there are often differences in spectral response
between plant canopies. Fig. 3.21 illustrates this in showing spectra of grass,
birch, pine and fir canopies.
Murtha (1978) describes the damaging agents which may be active in a forest,
and the manifestation of the damage itself. The following damaging agents are
mentioned: insects, disease, fire, water deficits, flooding, air pollution,
storms, activities of recreationists and beavers.
The manifestation of damage may be:
- a change in morphology (e.g. growth reduction, defoliation, loss of
branches, cellular collapse or wilted look);
- a change in physiology (e.g. decrease in photosynthates, deterioration of
chloroplasts, interruption of translocates including water);
- OK both.
It can be concluded that the effects of damage on spectral reflectance will be
one OK both of the following:
- in case of a change in morphology, a decrease in overall reflectance of
the plant especially in the near Infrared;
- in case of a change in physiology (chronic damage over a l o n g period), a
shift of the green peak towards yellow wavelengths due to a deteroriation
of chloroplasts and finally a shift towards red wavelengths.
Grass
B i r c h
100 600 800
81
Wavelength (nm)
Fig. 3.21 Reflectance spectra of four types of plant canopies after Krinov (1953; also given by H o l z , 1973).
Coulson (1966) has studied the directional reflectance of grass; a brief
discussion is given below.
The directional reflectance of green grass is shown in fig. 3.22.a. One of the
features is the low reflectance of radiation with wavelengths of 492 nm and 643
nm, which is in accord with the data presented above (fig. 3.19-3.21). The
broad minimum reflectance of 796 nm and 1025 nm radiation near the nadir and
the asymmetric shape due to forward scattering are further characteristics.
Note that the asymmetry is much less than for a number of soil materials e.g.
gypsum (fig. 3.11).
Fig. 3.22.b shows the directional reflectance of green grass at different
angles of incidence of light at a wavelength of 643 nm. At Bo = 78.5", a
backscattering maximum is observed, which is in accord with the absorbent
nature of plant leaves for radiation of this particular wavelength.
Curves of the polarization of radiation reflected from green grass are given in
fig. 3.23. The radiation that is strongly reflected by the cell walls of the
82
100
(a)
80 -
6 0 -
40 -
20 -
,? i
(b )
$,,=78.5 O c
t ,
I
f 0'
80 40 0 40 80 @=OO @=180°
k N a d i r a n g l e ( " ) N a d i r a n g l e ( " 1
Fig. 3.22 Directional reflectance of green grass (grass stands thick, height of grass 4-5 cm) after Coulson (1966): a) at four different wavelengths (principal plane, 0, = 53"); b) at three different angles of incidence (principal plane, A =
Note: for explanation see par. 3.2. 643 nm).
palisade tissue (A = 796 nm and A = 1025 nm) shows little polarization,
but the radiation reflected by the chlorophyll (A = 492 nm and A = 643 nm)
shows a high degree of polarization. Radiation with a horizontal polarization
is not absorbed so strongly by the chlorophyll as radiation with a vertical
polarization. Thus owing to preferential absorption, the reflected radiation is
polarized.
Fig. 3.23.b shows the degree of polarization at different angles of incidence.
The pattern shifts with the position of the source and shows a negative or a
vertical polarization in the antisource direction. The degree of polarization
increases with the angle of incidence. An anomalously high polarization appears
at O o = 78.5" . The maxima are located closer to the antisource direction than
in the curves of soil materials presented in fig. 3.12 and Fig. 3.14.
83
-5
40
20
0
.
I 0' '*. \
- 1025nm
Nad i r angle ( " )
(b )
I I I 1 I
80 40 0 40 80 @=O" @=180°
Nad i r angle ( " 1
Fig. 3.23 Degree of polarization of radiation reflected from green grass after Coulson (1966) : a) at four different wavelengths (principal plane, 9 = 53"); b) at three different angles of incidence (principaf plane, X * 492
Note: for explanation see par. 3.5. nm)
Looking at objects from the source direction means a simplification i n canopy
variables, since shadows are not visible.
This direction is called the "hot spot". Bunnik (1978) points to the value of
the "hot spot" for measurement of the canopy reflectance.
Thermal properties _____-__-_____--__ Beyond 2 u m, the reflectance of plant leaves is very low. The leaves
behave at longer wavelengths of the near Infrared almost as black bodies, the
emissivity being about 0.97. To prevent the plant from reaching high
84
temperatures, the leaves radiate efficiently at wavelengths longer than 2 u m. Healthy plants are in energy equilibrium with their environment. Their
temperature is adjusted when environmental parameters change so that the loss
of energy is equal to the gain of energy. In the formulae 2-31 and 2-32, the
energy budget equations are given. Some environmental parameters that influence
the energy budget are: the relative humidity of the air, the air temperature
and the wind speed. The characteristics of the plant that are important in this
connection are the width of leaf (or other characteristic dimensions) and the
diffusion resistance (in s m-'). These parameters may be used to formulate the
exchange of energy by convection between the leaves and the air, and the
transpiration rate of water from the leaves (see Gates, 1970). The plant
moisture condition has a pronounced influence on the leaf temperature at a
specified intensity of solar radiation.
The moisture condition of the plants may be expressed in the relative turgidity
(RT), which is defined by (Namken, 1 9 6 4 ) :
RT = 100 (FW - DW/TW - DW) ( 3 - 5 )
where FW is the field condition weight of leaf samples, DW is the weight of the
leaf samples after drying at 60°C and TW is the turgid weight achieved by
floating the leaf samples on distilled water overnight under illumination.
In fig. 3 .24 , the air temperature at the time of the measurements ( 2 : 3 0 -
3.:00 pm) on the two dates differed by 3.5 K and the relative turgidity of the
cotton leaves equilibrated with a change in radiation intensity in about 45
sec. The data show that the thermal response of the leaves to changing
radiation is linear; the standard errors of estimate (Sy.x) indicate that leaf
temperatures could be estimated within 0.9 K, two thirds of the time.
The variable plant moisture conditions in Fig. 3.25 were achieved by
timing of irrigation during a rainless period. At the mid-afternoon measuring
time, the cotton-plant leaves exhibited wilting symptoms at about 70 percent
RT; at 60 percent RT, the leaves were extremely flaccid. The data in Fig. 3.25
indicate that cotton-leaf temperature under the specified conditions can vary
about 3.5 K from RT = 6 0 X to RT = 8 2 X around the wilting point.
The difference between bare soils and plants is pronounced in the diurnal
changes in temperature. In general, plants are cooler than soil during day
time, and warmer during night time. A strong difference between plant and soil
will occur around noon on a clear day.
85
V
O" 4( k 7
W L 3 c,
m L
g 3E W +J Ic 5 W J
36
34
32
30
28
6/1/65
I I
0
TA = 31.8k.4 C
RT = 67.9*2.5%
b = 9.08 C(ly/min)-'
r2 = .898
0
6/1,2,3/64
TA = 28.3k1.3
RT = 77.7k1.7
b = 9.9
r2 = .go6
/ sy+ = .91
0 I I I I I
0.6 0.8 1 .o 1.2 1.4 1.6 S o l a r radiation, Rs(ly/min)
Fig. 3.24 Influence of solar radiation on cotton-leaf temperature (Namken, 1 9 6 5 ) . (Permission Am. S O C . of Agronomy, I n c . )
Some remarks are made in conclusion. Gates ( 1 9 6 4 ) reports about the difference
between conifers and broad-leafed deciduous plants. Conifers are cooler than
broad leaves during day time and warmer during night time under similar
conditions. The reason is that the fine needle structure of conifers increases
the convection efficiency and couples the conifers tightly to the air
temperature. At night, deciduous leaves will cool down to several degrees
below the air temperature by radiation. Pronounced thermal contrasts occur
between deciduous and evergreen trees in the autumn season.
Seasonal variations in plant temperature have been found to depend largely
86
v 41
t.
3 40
a
- aJ L
rn L aJ E aJ * % 39 aJ -I
38
37
36 58 62 66 70 74 78 82 86
1 I I I
A TA = 33.9k.7
RS = 1.32k.04
r2 = .864
b = -.15
I I 1 I I I
Fig. 3.25 The effect of relative turgidity on leaf temperature (Namken, 1965)(Permission Am. SOC. of Agronomy, Inc.)
on the seasonal variations in moisture availability.
For a discussion on the variation in plant temperature with external
factors, the reader is referred to Fitzgerald (1974). Both the absolute
temperature of leaves and plant canopies and the temperature differences
between leaves and the ambient air are of interest (Gates, 1970). The former is
of interest for the rate of biochemical reaction and the moisture condition of
plants, the latter may be used in comparing effects of treatment.
3.4. Implications for remote sensing
The reflectance data of minerals (par. 3.1.) are essentially obtained
under laboratory conditions. In rocks and soils we are normally concerned with
assemblages of minerals and consequently the discrimination potential with
regard to mineralogy is lower. Therefore, only rough estimates may be obtained,
but this can be sufficient for the detection of concentrated mineral
occurrences .
The t e x t s on s o i l s and v e g e t a t i o n pay a t t e n t i o n t o p r o p e r t i e s such a s o rgan ic
ma t t e r c o n t e n t , ano rgan ic composi t ion , mois ture c o n t e n t , roughness of s o i l s and
composi t ion as w e l l as s t r u c t u r e of p l a n t l eaves . However, remote sens ing
p rov ides d a t a on s o i l s and rocks a s a whole, and p l a n t s a s cove r types , r a t h e r
t han t h e i n d i v i d u a l c o n s t i t u e n t s . From remote d i s t a n c e s one cannot expec t t o
o b t a i n d e t a i l e d in fo rma t ion on i n d i v i d u a l c o n s t i t u e n t s , a l t hough l a s e r -
t echn iques o p e r a t i n g wi th cohe ren t h igh i n t e n s i t y EMR may form a n excep t ion t o
t h i s s t a t emen t . The rough remote s e n s i n g d a t a , .however, have t h e advantage t h a t
they o f f e r average f i g u r e s f o r a n assemblage of a s p e c t s over a r e l a t i v e l y l a r g e
s u r f a c e a r e a . These f i g u r e s a r e d i f f i c u l t t o o b t a i n on t h e ground s i n c e they
r e q u i r e a tremendous amount of obse rva t ions and samples. An example of a rough
estimate i s t h e so -ca l l ed a lbedo , which r e p r e s e n t s t h e t o t a l r a d i a n t
- r e f l e c t a n c e of n a t u r a l o b j e c t s . R a r r e t t and C u r t i s p r e s e n t s e v e r a l va lues ; some
of t h e s e a r e g iven i n t a b l e 3.2.
Table 3.2 Albedo v a l u e s of v a r i o u s n a t u r a l s u r f a c e s ( R a r r e t t and C u r t i s , 1976) .
~~- t ype of s u r f a c e a lbedo , r e f l e c t e d r a d i a t i o n a s
X of i n c i d e n t r a d i a t i o n
s o i l s f i n e sand dry b lack s o i l moist ploughed f i e l d mois t b l ack s o i l
snow dense c l e a n snow v e g e t a t i o n d e s e r t shrub l and
win te r wheat oaks dec iduous f o r e s t p ine f o r e s t p r a i r i e swamp v e g e t a t i o n h e a t h e r
37 14 1 4
8 86-95 20-29 16-23 18 17 1 4 12-13 10-14 1 0
3.5. Conclusions
The s p e c t r a l r e f l e c t a n c e f e a t u r e s a r e e i t h e r of e l e c t r o n i c o r of
v i b r a t i o n a l o r i g i n . An example of t h e former i s a broad i r o n hand a t 1.1 u m.
The l a t t e r i s r ep resen ted by a band a t 1.4 IJ m f o r O H ' , bands hetween 1.6 u m
and 2.5 u m f o r C03". and t h e water a b s o r p t i o n hands a t 1.4
S o i l s may show t h e s e r e f l e c t a n c e c h a r a c t e r i s t i c s , but i n a d d i t i o n p r e s e n t
v a r i a b i l i t y due t o s u r f a c e roughness a s i n f luenced by s o i l t e x t u r e , s t r u c t u r e
m and 1.9 m.
88
and tillage. Furthermore, the organic matter content strongly influences the
spectral reflectance e.g. a high organic matter content results in an overall
low reflectance.
Plants show a typical reflectance spectrum as influenced by canopy structure,
pigmentation, mesophyll Structure, water content and surface properties of the
leaf. A l l pigments absorb at 0.44 !J m (blue), but chlorophyll also shows an
absorption band at 0.66 IJ m (red). Normally, green is reflected more strongly
than blue and red.
The palisade tissue of the mesophyll with its large area of cell walls is
mainly responsible for the high reflectance of near Infrared by plant leaves.
Furthermore, the surface properties of the leaf have great influence on the
reflectance as is illustrated a.0. by white oak leaves in their juvenile stage
(pubescence).
The work of Coulson (1966) with regard to the directional reflectance of
natural surfaces reveals interesting features, such as the following: highly
absorbent materials (e.g. plant leaves, and soils rich in organic matter)
deviate from low absorbent materials (which show a forward peak in scattering)
in having a backscattering maximum.
With regard to emission, the following can be stated: rocks show
emissivity minima between 9.0 !J m (acid rocks) and 10.5 !J m (ultrabasic rocks).
For rocks as well as for soils, the diurnal temperature change is the most
significant short-term variation that is usable in remote sensing.
The transfer of heat in the soil takes place by conduction, convection and
radiation together, and by latent heat transport (water vapour). Soil moisture
is one of the most important factors influencing the thermal hehaviour of soil.
The difference between soils and plants is most pronounced in the diurnal
changes in temperature. In general, plants are cooler than soil during day time
and warmer during night time. Seasonal variations in plant temperature largely
depend on the seasonal variation in moisture availability.
3.6. References
Barrett, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and H a l l : 336 pp.
Bowers, S.A. and Hanks, R.J . , 1965. Reflection of Radiant Energy from Soils. Soil Science, Vol. 100, No 2. The Williams & Wilkins Co, U.S.A.: pp. 130-1 38.
Bunnik, N.J.J., 1978. The multispectral Reflectance of Shortwave Radiation by Agricultural Crops in relation with their Morphological and Optical Properties. Thesis Agric. Univ., Wageningen, The Netherlands: 176 pp.
89
Chudnovski, A.F., 1962. Heat Transfer in the Soil. Israel Program for Scient. Transl. (Transl. from Russian), Oldbourne Press, London.
Cipra, J.E., Baumgardner, M.F., Stoner, E.R. and MacDonald, R.B., 1971. Measuring Radiance Characteristics of Soil with a Field Spectroradiometer. Soil Sci. SOC. Amer. Proc., vol 35: pp. 1014- 1017.
Condit, H.R., 1972. Application of Characteristic Vector Analysis to the Spectral Energy Distribution of Daylight and the Spectral Reflectance of American Soils. Applied Optics, Vol. 11, No 1: pp. 74-86.
Coulson, K.L., 1966. Effects of Reflection Properties of Natural Surfaces in Aerial Reconnaissance. Applied Optics, Vol. 5, No 6: pp. 905-917.
Damen, J.P.N., 1975. Poging tot verklaring van Reflectiespectra van een serie Bodemmonsters, gemeten met de Niwars-spectrometer. Niwars-publ. NK. 25: 56 pp.
Fitzgerald, E., 1974. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Spectral Properties of Materials. ESRO CR-232, Neuilly, France: 231 pp.
Fuchs, M. and Tanner, C.B., 1968. Surface Temperature Measurements of Bare Soils. Journal of Appl. Meteor., Vol. 7.
Gates, D.M., 1964. Characteristics of Soil and Vegetated Surfaces to Reflected and Emitted Radiation. Proc. of the 3rd Int. Symp. on Remote Sensing of Environment, Univ. of Michigan, Ann Arbor: pp. 573-600.
Gates, D.M., 1970. Physical and Physiological Properties of Plants. Chapter 5 , Remote Sensing, pp. 224-252; produced by the Committee on Remote Sensing for Agricultural Purposes. Publ. Nat. Acad. of Scces.
Girard, M.C. and Girard, C.M., 1977. T616d6tection de la Surface du Sol. ler Colloque P6dologie T616d6tection, Rome: pp. 55-64.
Gold, A. and Asher, J.B., 1976. Soil Reflectance Measurement using a Photo- graphic Method. Soil Sci SOC of Amer. Journal, Vol. 40, No 3: pp. 337-34 1.
Higham, A.D., Wilkinson, B. and Kahn, D., 1973. Multispectral Scanning Systems and their Potential Application to Earth-Resources Surveys. Basic Physics & Technology ESRO (European Space Research Organisation): 186 pp.
Holz, R.K(ed), 1973. The Surveillant Science. Remote Sensing of the Environment. Houghton Mifflin Cy, Boston: 391 pp.
Hunt, G.R., Salisbury, J.W. e.a., 1970-1976. Visible and Near Infrared Spectra of Minerals and Rocks I/XII. Modern Geology, Gordon and Breach, Science Publ. Ltd. Belfast, N-Ireland.
Idso, S.B. and Jackson, R., 1969. Comparison of Two Methods for Determining Infrared Emittances of Bare Soils. Journal of Appl. Meteor., Vol. 8.
Institut National pour l'Etude Agronomique du Congo Belge et du Ruanda-Urundi, Ann6e 1952. Bur. Climatol. Commun. 7: 144 pp.
Janse, A.R.P., Bunnik, N.J.J., 1974. Reflectiespectra van enige Nederlandse Bodemmonsters bepaald met de Niwars-veldspectrometer. Niwars publ. No 18: 31 pp.
Janse, A.R.P., Bunnik, N.J.J. en Damen, J.P., 1976. Reflectiespectra van enige Nederlandse Bodemoppervlakken. Landbk. Tijdschr. Jg 88, NK. 8: pp. 254-260.
Krinov, E.L., 1953. Spectral Reflectance Properties of Natural Formations. Acad. of Scces, USSR. Nat Res. Council of Canada. Techn. Transl., TT-439.
Lars, Laboratory for Agricultural Remote Sensing, 1968. Remote Multispectral Sensing in Agriculture. Purdue Univ, Agric. Exp. Stat., Res. Bull., Vol. No 3: 175 pp.
90
Lyon, R.J.P., 1965. Analysis of Rocks by Spectral Infrared Emission (8-25 u m) Economic Geology, Vol. 60: pp. 715-736.
Mathews, H.L., Cunningham, R.L. and Petersen, G.W., 1973. Spectral Reflectance of Selected Pennsylvania Soils. Soil Sci SOC. her. Proc., Vol. 37: pp. 421-424.
Meyer-Arendt, J.R., 1972. Introduction to Classical and Modern Optics. Prentice-Hall Inc., Englewood Cliffs, N.J.: 558 pp.
Monteith, J.L., 1973. Principles of Environmental Physics. Contemporary Biology. Edward Arnold (publ.) Ltd London: 241 pp.
Murtha, P.A., 19781. Remote Sensing and Vegetation Damage: A Theory for Detection and Assesment. Symp. on Remote Sensing for Vegetation Damage Assessment 1978. Publ. by Amer. SOC. of Photogrammetry: 32 PP.
Namken, L.N., 1964. 'Ihe influence of crop environment on the internal water balance of cotton. Soil Sci. SOC. Amer. Proc. 28: pp. 12-15.
Namken, L.N., 1965. Relative turgidity technique for scheduling cotton irrigation. Agron. J. 47: pp. 38-41.
Obukhov, A.I. and Orlov, D.S., 1964. Spectral Reflectivity of the Major Soil Groups and Possibility of using Diffuse Reflection in Soil Investigations. Soviet Soil Sci. 1964: pp. 174-184.
Orlov, D.S., 1966. Quantitative Patterns of Light Reflection by Soils. I. Influence of Particle (aggregate) Size on Reflectivity. Soviet Soil Sci. 1966: pp. 1495-1498.
Planet, W.G., 1969-1970. Some Comments on Reflectance Measurements of Wet Soils. Remote Sensing of Environment 1, Elsevier N-Holland: pp. 127- 129.
Skidmore, E.L., Dickerson, J.D. and Schimmelpfennig, H., 1975. Evaluating Surface-Soil Water Content by measuring Reflectance. Soil Sci. SOC. Amer. Proc., Vol 39: pp. 238-242.
Soil Survey Staff, 1975. Soil Taxonomy. A Basic System of Soil Classification for making and interpreting Soil Surveys. U . S . Dept of Agric. Handbook No 436: 754 pp.
Stoner, E.R., Baumgardner, M.F., Biehl, L.L. and Robinson, B.F., 1980. Atlas of Soil Reflectance Properties. Agric. Exp. Stat. Purdue Univ., West Lafayette, Indiana, Res. Bull. 962: 74 pp.
Wijk, W.R. van, Vries, D.A. de, 1963. Periodic Temperature Variations. In: Physics of Plant Environment, ed. van Wijk, North Holland Publ. Co., Amsterdam.
3.7. Additional Reading
Bunnik, N.J.J. and Verhoef, W., 1974. The Spectral Directional Reflectance of Agricultural Crops. Niwars Publ. No 23.
Colwell, J.E., 1974. Vegetation Canopy Reflectance. her. Elsevier Publ. Cy. Remote Sensing of Environment 3: pp. 175-183.
Gausman, H.W. and Cardenas, R., 1968. Effect of Pubescence on Reflectance of Light. Proc. of 5th Symp. on Remote Sensing of Environment. Univ. of Michigan, Ann Arbor: pp. 291-297.
Hoffer, R.M., Johannsen, C.J., 1969. Ecological Potentials in Spectral Signature Analysis. In: Remote Sensing in Ecology. Unlv. of Georgia Press, Athens: pp. 1-16.
Karmanov, I.I., Rozhkov, V.A., 1972. Experimental Determination of Quantitative Relationships between the Color Characteristics of Soils and Soil Constituents. Soviet Soil Sci. 1972: pp. 666-674.
Knipling, E.B., 1970. Physical and Physiological Basis for the Reflectance of Visible and Near Infrared Radiation from Vegetation. her. Elsevier
91
Publ. Cy, Remote Sensing of Environment 1: pp. 155-159. Koolen, A.J., 1979. Temperatuurbeelden van Onbegroeide Grond op weg naar
Landbouwpraktijk? Landbk. Tijdschr. pt. 91, Nr 9: pp. 258-264. Leu, D.J., 1977. Visible and Near Infrared Reflectance of Beach Sands: A Study
on the Spectral Reflectance/Grain Size Relationship. Remote Sensing of Environment 6 , Elsevier N-Holland: pp. 169-182.
Scharringa, M., 1976. Temperatuurklimaat van de Bodem. Landbk. Tijdschr. pt. 88, Nr. 8: pp. 261-264.
Suits, G.H., 1972. The Calculation of the Directional Reflectance of a Vegetative Canopy. her. Elsevier Publ. Cy, Remote Sensing of Environment 2: pp. 117-125.
Suits, G.H., 1972. The Cause of Azimuthal Variations in Directional Reflectance of Vegetative Canopies. Amer. Elsevier Publ. Cy, Remote Sensing of Environment 2: pp. 175-182.
Torres, 1973. La Thermographie Questions Techniques et Problemes de 1'InterprGtation. Revue Photo-InterprGtation 1973-2: pp. 48-73.
Verhoef, W. and Bunnik, N.J.J., 1974. Spectral Reflectance Measurements on Agricultural Field Crops during the growing season. Niwars publ. No 31: 72 pp.
Verhoef, W. and Bunnik, N.J.J., 1975. A Model Study on the Relations between Crop Characteristics and Canopy Spectral Reflectance. Niwars publ. No 33: 89 pp.
Verhoef, W. and Bunnik, N.J.J., 1976. The Spectral Directional Reflectance of Row Crops. Niwars publ. No 35: 134 pp.
Vincent, R.K., Rowan, L.C., Gillespie, R.E. and Knapp, C., 1975. Thermal Infrared Spectra and Chemical Analysis of Twenty-six Igneous Rock Samples. Remote Sensing of Environment. Amer. Elsevier Publ. Cy: pp. 199- 209.
Watson, R.D., 1972. Spectral Reflectance and Photometric Properties of Selected Rocks. Remote Sensing of Environment 2: pp. 95-100.
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93
4. DETECTION OF ELECTROMAGNETIC RADIATION
Life on earth is dependent on solar radiation and has developed systems
that use solar radiation as an energy source (e.g. plants) and as a means of
visual perception (man and a great number of animals). Two of our five senses
are capable to detect EMR these being the eye and the nerve endings. The latter
sense heat. The eye enables vision and is of primary interest to our purpose,
since it is difficult to think about methods for remote inventory and
monitoring of the natural environment that do not depend on the human eye in
some phase of the processing or interpretation. The only alternative is
braille!
Some methods of image interpretation require a certain ability of human vision.
One of these, the ability to get a stereoscopic impression of overlapping
images is normally present. Another requirement connected with the study of
coloured images is correct colour vision. The different aspects of human vision
are discussed in par. 4.1.
To expand o u r view, that is to make visible, radiation to which the eye is
not sensitive, may be done by photographic as well as non-photographic
techniques with detection capability in the zones of the EM spectrum outside
the Visible (see par. 4.2 and 4 . 3 ) .
After this first subdivision in photographic and non-photographic methods
of detection, attention is given in par. 4.4. to the different types of
platforms on which detectors may be mounted. Finally in par. 4.5, a discussion
is presented on ground-investigations. The latter have to be directed to the
remote sensing tool and therefore deviate partly from conventional
investigations.
4.1.Human vision
The eye is capable of sensing radiation of wavelengths between 0.4 and
0.7 m (or more precisely 380-760 nm), the so-called Visible zone of the EMS.
As is stated above, human vision has to be used in one or more steps of
processing or interpretation, so that some understanding of it is necessary.
There are a number of aspects connected with vision that have to be dealt with
in this context, namely:
- colour perception;
- stereopsis or depth perception,
94
- resolving power.
The construction of the eye is to some extent comparable with the
photographic camera, since one as well as the other possess a diaphragm, a lens
and a sensitive layer. The light enters the eye through the cornea, which is
separated from the l e n s by fluid; the maximum light refraction occurs at the
cornea.
The iris is the pigmented part of the eye that controls the aperture
(pupil), which can be varied over a ratio 16:l.
The lens is active in accomodating or focusing for near and far vision. For
this, the shape of the l ens can be modified by varying the tension on the
membrane attached to its margin. For nearby vision, the tension is released and
the lens gets a more convex shape as compared with its shape for far vision.
The image is focused on the retina, which contains the light receptors, the so
called rods and cones. The rods and cones differ in threshold as is indicated
in Fig. 4.1 and serve under low illumination (e.g. twilight) and under high
illumination (e.g. daylight) respectively.
000 - \ \
I
400 500 600 700 Wavelength (nm)
Fig. 4.1 Threshold responses of retinal receptors (after Land, 1977)
95
The spectral sensitivities of rods and cones are presented in Fig. 4.2.
The curve that peaks at about 500 rn corresponds to the sensitivity of rod
pigment. The other three curves correspond to the cone pigments and show peaks
respectively at 435 nm, 520-550 nm and 550-595 nm. The latter extends into the
long wavelengths up to about 650 nm, thus enclosing orange as a whole. Note
that the sensitivity ranges of the cones are overlapping each other.
The maximum concentration of receptor cells is found in the fovea. Close
to the fovea is the so-called blind spot. At this place, the optic nerve joins
the eye and there are no receptor cells.
h 1 0 0 - W N .r 7
m 8 0 - E 0 E
>, 4 2
v)
v
6 0 - .r
2 4 0 - I-’ E .r
% 2 0 - .r c,
W a
m 7
0 400 500 600 700
Wave1 ength (nm)
Fig. 4.2 Normalized spectral sensitivities of four visual pigments (after Land, 1 9 7 7 ; adapted from work of Brown and Wald of Harvard Univ.)
The so-called retinex theory (Land, 1977) helps to explain COlOUK vision.
Retinex is used for the ensemble of biological mechanisms that convert flux
into a pattern of lightnesses. The experiments of Land show that objects are
observed in the same colour even under a great variation of illumination
intensity. Therefore, flux does not appear to be the defining factor. In human
vision, the COlOUK sensation is made less dependent OK even independent on
flux, since a comparison is made in the retinex system of lightness of a
specific area with respect to the lightnesses of its surroundings.
Although the activation of two retinex systems has been found to be sufficient
for COlOUK sensation, normally three retinex systems will be active. A t
96
daylight, the three cone pigments act and determine individually the lightness
of an object or area. The colour of the object or area is a result of the
report on the three specific lightnesses and as stated above of the comparison
of these with the lightnesses of its surroundings.
The visual pathways (see Kaufman, 1 9 7 4 ) , that is the pathways from the
eyes to the central nervous systems, are given in fig. 4 . 3 . The fibers
comprising the optic nerve may be thought of as divided into two intermixed
bundles. One bundle of the optic nerve contains fibers originating from cells
at the temporal side of the eye, and the other bundle contains fibers
originating at the nasal side of the eye. The fibers that originate from the
temporal sides go to the hemisphere of the brains at the same side of the head
as the eye in which the fibers originate. The nasal fibers cross over, that is
they go to the opposite hemisphere of the brains.
l e f t r i g h t object / \ / I
LH RH brains
Fig. 4 . 3 Pathways from the optic nerves to the central nervous system.
L E , RE = resp. left and right eye LH, RH = resp. left and right cerebral hemisphere
The eye produces, images that are upside down. The left side of an object
will be at the right side of the image on the retina, and the right side of an
object at the left side of that image. In other words: the left side of an
object is projected nasal for the left eye and temporal for the right eye.
Consequently, points to the left of the scene produce signals in the right
cerebral hemisphere and those of the right side of the scene in the left
cerebral hemisphere (see fig. 4 . 3 ) . The crossing of signals to contralateral
hemispheres plays an important part in binocular depth perception, since it
enables fusion of double images in the binocular field of view.
It has been known for many years, that fusion is not really a necessary
97
condition for stereopsis (Kaufman, 1974); there are several cues. The so-
called pictorial cues involve light and shade, texture, interposition,
perspective and relative size. Others are:
- kinetic cues, the motion parallax OK the difference in imaging between far- away objects and nearby objects when the head is moved, and the kinetic depth
effect that is the systematic transformation of retinal images by movement with
respect to the object;
- physiological cues, being the accomodation of the lens and the convergence
and divergence of the eye axes.
For stereoscopic observation of airphotos using parallax differences of image
objects, however, fusion is a must.
The eye shows normal aberrations (Davson, 1962), namely:
- spherical aberrations, that is the rays from an object-point entering the eye at different points of the cornea are not bent to converge at a unique point
on the retina;
- chromatic aberrations, that is the focus for blue rays is before the retina, and for red rays behind it, while yellow rays are in focus.
Furthermore, there are the individual aberrations and deficiencies with respect
to perception of CO~OUK, texture and pattern (see Julesz, 1975 and Young,
1964).
The resolving power of the eye is determined by the largest diameter of
its receptor cells (Sabins, 1978). The maximum diameter, which mounts 3 u m,
has to be multiplied by the refractive index of the vitreous humor (n = 1.3) to
obtain the effective diameter as expressed by a' (= the angle or radian
measure of the outer rays in the eye that compose the retinal image). The image
distance from the retina to the lens is about 20 nun. The effective width of the
receptors therefore is approximately 4f20.000 or 1/5.000 of the image distance.
Since a' is proportional to a (= the angle between the outer rays coming from
the margins of the scene into the eye (Davson ed., 1962), the effective width
can be placed upon 1f5.000 of the object distance as well. Therefore, adjacent
objects must be separated by l/5.000 of the object distance in order to fall on
alternate receptors.
However, the detection capability of the eye is influenced not only by the size
of the objects but also by their shape, contrast and orientation (Sabins,
1978).
The fibers going from the retina to the brains have to carry information
98
about position, shape, size, texture, brightness and colour. This is only
possible by unique codes. According to Kaufman (1977), the theories concerning
the natures of the codes are not conclusive OK even fully convincing.
Therefore, we will only discuss one of these sensations in a rather simple hut
practical way, namely: colour vision.
The colour sensations blue, green and red are called the primary colours.
Combination of green and red light produces yellow; blue and red light produce
magenta, while blue and green light produce cyan. Yellow, magenta and cyan are
the so-called secondary colours.
Considering the properties of secondary colour dyes: the observation of yellow
(ye), magenta (ma) and blue-green or cyan (cy) means specific absorption of
respectively blue (bl),
of respectively green + expressed in the colour
(fig. 4 . 4 ) .
green (gr) and red (re).; the dyes show transmittance
red, blue + red and blue + green. The properties are circle and can be used for the composition of colours
a b C
Fig. 4 . 4 The Colour circle: a) basic division (after Gerritsen, 1972); b) mixing of primary colours; c) mixing of secondary colours (b and c after Smith, 1968); For abbreviations: see text.
(Used by permission of Am. SOC. for Photogrammetry and Remote Sensing.)
White is produced by mixture of the three primary colours. The super-position
of three secondary colour dyes produces grey to black, since blue, green and
red are absorbed.
Colour is a composite three-dimensional characteristic consisting of a
lightness attribute and two chromatic attributes, being hue and saturation
(Hunter, 1975). Hue is the colour sensation associated with different parts of
the spectrum denoted by blue, green, red, cyan, yellow (,orange) and magenta.
99
Saturation or chroma is the colour sensation which corresponds to the degree
of hue in a colour.
The arrangement of colours in a hue and saturation surface is given in fig.
4.5a. Full saturation and complete absorption by the secondary COlOUKS (as
meant in fig. 4.4~) is found on the outer circle.
WH!TE
BLACK
(a) (b)
Fig. 4.5 Arrangement of colours (Hunter, 1975) a) Hue and saturation surface; b) Three-dimensional COlOUK space. (Reprinted by permission of John Wiley & Sons, Inc.)
Lightness or value is equivalent to some member of the series of achromatic
colour perceptions ranging for light diffusing objects from black to white,
and for regularly transmitting objects from black to perfectly clear and
colourless (Wyszecki e.a. 1967). A three-dimensional colour space is given in
fig. 4.5b. The lightness dimension provides an achromatic center axis, on
which the hue circle can be positioned at varying lightness levels.
Using the absorption characteristics of the secondary COlOUK dyes, that
is subtraction of light of specific wavelength range, is known as the
subtractive way of colour formation (fig. 4.4.~). this in contrast to the
additive way being the addition of light of specific wavelength (fig. 4.4.b).
Actually, the eye can only operate on an additive way. Suppose blue is
subtracted from white light by passing through a filter. Thus green and red
light are transmitted, which produce the same effect as the addition of green
and red light would do, that is they add to yellow.
Often it is found difficult to understand colour formation both in a
subtractive and an additive way. However, both ways are essential to the
production of colours by photography.
The effect of different quantities of the secondary colours yellow,
magenta and cyan dotted over a white reflective surface is illustrated in the
100
ITC Colour Chart (plate 3 ) . The pigments dotted on the white paper surface
subtract light from the incident radiation. Yellow pigments subtract blue
light, magenta pigments subtract green light etc.
The transmitted light is reflected by the paper surface. Representing
this light by vectors, as is done in fig. 4.6, enables a schematic
presentation of subsequent additive colour formation.
For more information on Colour Science, one is referred to text books such as
Judd and Nyszecki ( 1 9 6 3 ) and Wyszecki and Stiles ( 1 9 6 7 ) .
4.2. Photographic techniques
Photographic techniques may be used for detection of a portion of the
Ultraviolet (0 .3-0.4 p m), of Visible radiation (0 .4-0.7 !J m) and of a portion
of the near Infrared range (0 .7-0.9 !.I m). Filters and specific films are used
to obtain information in broad wavelength zones or in relatively narrow bands.
There are three categories of filters (Slater, 1 9 7 5 ) :
- antivignetting filters;
- spectral filters;
- polarization filters.
Antivignetting filters are usually produced by depositing a metal alloy
on glass in such a way that the central area of the filter is absorbent and
the circumferential region is transmittent. They are used to improve
uniformity of image-plane irradiance (Slater, 1 9 7 5 ) .
Spectral filters are divided into absorption and interference filters.
Absorption filters can be produced by cementing gelatin between planeparallel
plates of optical quality glass. The gelatin has an admixture of organic dyes.
Resides gelatin filters, filters of coloured glass are available. As an
example, absorption curves of the Kodak Wratten filters 1A and 2A are
presented in fig. 4.7. The 2A filter is a complete absorber for radiation of
200-400 nm, while 1A shows 1 X transmittance over the 310-380 nm wavelength
zone. Furthermore, the large variety of Kodak Wratten filters is demonstrated
in fig. 4.8.
Interference filters comprise quarterwave optical-path- thickness layers
of alternating high and low refractive-index materials. Unwanted radiation is
to be reflected and canceled, while the required radiation is to be
transmitted.
Polarization filters consist of a coating of polarization film on
(optical quality) glass. The position of the filter can be such that only the
101
B1 Gr I Re I
B1
\ \ \ \
G r
i I I
\ ; \ I B? I
\ I \ \
\
Abbreviations :
u = unsaturated d = dark 1 = light
ye = yellow Ma = magenta Cy = cyan B1 = blue Gr = green Re = red
\ \ \ \
0
I / / / I
/
uGr / YeGr’
I ’ \ I . cr Re/ e.g. ReMa = reddish
magenta.
/ / / /
/ / /
/ /
Fig. 4 .6 Additive Colour formation schematically.
102
component parallel to the principal plane is transmitted. The principal plane
is the vertical plane containing the sun, the ground target and the observer
straight ahead (plane of incidence; see also fig. 2.5). Polarization filters
may be used to enhance image quality in the presence of haze.
Haze produces multiple reflection at randomly oriented particulates. The
. I
100
. I
W U S
3 1 c, .r
E u)
L k-
5 10
i
200 300 400 500 600 700 800 900 Wavelength (nm)
100 300 400 500 600 700 800 900
1 A
2A
Wavelength (nm)
Fig. 4.7 Spectrophotometric transmittance curves of Wratten filters 1A and 2A (Eastman Kodak Cy, 1970).(Reprinted courtesy of Eastman Kodak Company.)
scattered light shows polarization dominantly horizontal, that is perpendicular
to the plane of incidence. By transmitting only the component parallel to the
plane of incidence the effect of haze will be reduced and the image contrast
will be enhanced.
Filters require a correction on exposure time in order to compensate for
the radiation removed by the filter. The factor, by which the exposure with
filter has to be greater than the exposure without filter, is called the filter
factor.
The main photographic film-types are:
- panchromatic or black and white films sensitive for the wavelength range
103
from 360 to 720 nm;
- Infrared black and white films recording Visible and near Infrared
radiation (up to 900 nm);
Fig. 4.8 Spectral-transmittance bar charts for Selected Kodak Wratten Filters (Eastman Kodak Cy, 1970).(Reprinted courtesy of Eastman Kodak Company.)
104
- true colour films sensitive for blue, green and red light;
- false colour films recording green, red and near Infrared radiation (up to
900 nm).
All the films mentioned when applied from airborne or spaceborne platforms
require filters to remove unwanted radiation and to improve image-plane
irradiance.
In table 4.1 some film-filter combinations are given. To produce Infrared
black-and-white photography, a large part of the Visible is often excluded from
reaching the film. This may be done by application of light-red OK dark-red
filters. A yellow filter is applied to obtain false colour photography.
Table 4.1 Examples of film-filter combinations
Wratten filter no Excluding wave- Film Eliminating effect of length (nm) below”
1A (sky light) 3 10-386 true colour weak haze, flying alti- film tude up to about 3000 m
2A (pale yellow) 406-413 true colour moderate to strong haze, film flying altitude more than
3000 m G12 (yellow OK 492-508 panchromatic strong haze minus blue) film and false
colour film
and white film 15G (dark yellow) 508-520 Infrared black strong haze
25A (light red) 580-590 item item 89B (dark red) 680-703 item item
* first figure 0.1 %, second figure 10 % transmittance according to transmittance curves Eastman Kodak Cy (1970).
Photographic films consist of a flexible transparent base (film base)
coated with one or more emulsion layers of which each has a thickness of
approximately 100 !J m. The emulsion is a suspension of silver halide grains in
solidified gelatin.
The panchromatic and Infrared black-and-white-films consist of one
emulsion layer, while the true colour and false colour-films have three
emulsion layers. The grains of the emulsions are a few micrometers in diameter
(Sabins, 1978) and have an irregular shape. They have been processed to
increase their sensitivity to light. On exposure, when a proton strikes one of
the grains, an electron is trapped at an imperfection of a grain, it may
105
convert a silver ion into a neutral silver atom. If more than one photon is
received by a silver halide grain within about a second, combinations of four
atoms of silver are formed, which are stable. Thus by interaction of light
with silver halide grains a latent silver image is formed.
By the reduction process in developing panchromatic films, the exposed grains
are converted into opaque grains and unexposed grains are removed leaving
clear areas in the emulsion. The parts of the scene with low reflection will
show up bright, the parts with high reflection dark and moderate reflecting
areas grey; it is a negative image. When such a film is printed onto photo-
graphic paper, the signatures are reversed and a positive image is the result.
Recently a new film type has been introduced in which during the
developing process, silver is replaced by a black dye. The resultant product
is less granular when compared with the silver image and enables therefore
high enlargement factors. However, no application in aerial photography of
this new type of film is known t o the author.
The characteristics of the emulsion layers in true COlOUK and false
colour-films are similar to those of panchromatic film with the following
additions:
- each layer has a maximum sensitivity, this being for true colour film in the blue, green and red bands, and for false colour film in the green, red and
near Infrared bands,
- during developing each emulsion layer forms a COlOUK dye, that is for true colour-film complementary to the blue, green and red radiation that
exposed the layers being yellow, magenta and cyan, for false colour-film
yellow in the green sensitive layer, magenta in the red sensitive layer
and cyan in the near Infrared sensitive layer.
The false COlOUK-fih is described in table 4.2 by comparing it with the true
colour-film.
In true colour-film, a yellow filter between the blue and green sensitive
layers prevents blue from reaching the underlying layers, which are also
sensitive to blue radiation. Blue is eliminated from the false colour-film by
the use of a yellow filter on the camera. The blue sensitive (yellow forming)
layer of the true colour film is replaced by a near Infrared sensitive layer
in the false colour film, and the dyes to be produced are shifted one
position, tnat is yellow for the green sensitive layer, magenta for the red
sensitive layer and cyan for the near Infrared sensitive layer. So do the
106
Table 4.2 Comparison between true colour-film and false colour-film.
layers true colour-film false colour-film (with yellow filter on camera)
sensitive dY e sensitive dye resulting f OK for colour
1st layer blue yellow near Infrared cyan red --------- yellow filter 2nd layer green magenta green yellow blue 3rd layer red cyan red magenta green
resulting colours in the false colour photograph, respectively blue for green,
green for red and red for near Infrared reflecting objects.
By developing a true colour film, a yellow image is formed at the exposed
places in the blue sensitive layer, the green sensitive layer forms a magenta
image etc. These images are negative images, because the original radiation
intensity is transformed in dye. For instance, much blue results in much yellow
dye, which transmits little blue. When the negative film i s projected onto
photographic paper, a positive colour print is produced. In this example: the
negative shows much yellow, which transmits little blue, producing little
yellow on the positive, which transmits much blue (that is the original
intensity). In fig. 4 . 9 , a schematic presentation is given of the colour
negative process and the production of colour positives of true colour, as well
as false colour-film. Grass is taken as an example; for the reflectance of
grass, the reader is referred to fig. 3.21. The incident radiation and the
radiation transmitted by the film positives are indicated by vectors. Since
blue is not included in the false colour-film and replaced by near Infrared,
which is not visible to the eye, false colours are produced. The amount of dye
formed in the positive products is proportional to the incident radiation in
such a way that much radiation produces little dye.
Aerial colour films are often of the reversal type, since these films produce a
high contrast. Therefore, some attention is given below to the processing of
these films (Slater, 1975).
The first step in processing of colour reversal film is the development
in a black and white developer. A negative image is formed in each layer.
Fogging exposes the remaining silver halide. This is normally accomplished
t r u e c o l o u r f i l m
1 1 1 r a d i a t i o n qrass
i 11 u m i n a t i on o f f i l m
N I R
4 r.
r e
- i l l u m . w i t h w h i t e 1 i g h t B B
f a l s e c o l o u r f i l m
7 1 minus b l 1 grass 1 - N I R g r 4 r e
b l g r r e - dark green c o l o u r
s t r o n g a b s o r p t i o n
b l + r e
moderate a b s o r p t i o n g r
p o s i t i ve
p o s i t i v e
r e b l g r - magenta - r e d c o l o u r
v e r y much r e
moderate a b s o r p t i o n b l
s t r o n g a b s o r p t i o n g r
b l + r e combine t o ma
Fig.4.9 Schematic presentation of colour formation in true and false colour films using grass as an example
108
chemica l ly i n r e v e r s a l p rocess ing . The fo l lowing s t e p is t h e development of
t h e f i l m i n a co lou r deve loper r e s u l t i n g i n t h e product ion of dye i n t h e areas
where t h e remaining s i l v e r h a l i d e i s reduced. A t t h i s s t a g e , a p o s i t i v e co lou r
image and a nega t ive s i l v e r image a r e produced. The f i l m is then bleached t o
remove t h e s i l v e r images but l e a v i n g t h e dyes una f fec t ed . A g reen s u b j e c t w i l l
show up b lue when viewed i n t r a n s m i t t e d l i g h t because magenta and cyan dyes
are formed, which abso rb green and red l i g h t .
The s p e c t r a l s e n s i t i v i t y cu rves of two types of Aerochrome I n f r a r e d f i l m
are g iven i n f i g . 4.10. It can be noted t h a t t h e cyan-forming-layer i n t h e
f i l m s is slower a s compared wi th t h e o t h e r l a y e r s . This has been done t o
o b t a i n a lower response t o nea r I n f r a r e d r a d i a t i o n . The nea r I n f r a r e d
s e n s i t i v e l a y e r is t h e upper l a y e r i n t h e f a l s e co lou r f i l m and shows a 2 s e n s i t i v i t y of about 0 (= 1 e r g / c m ) i n a r e l a t i v e l y broad zone of nea r
I n f r a r e d r a d i a t i o n , be ing ve ry low when compared t o t h e green and r ed
s e n s i t i v e l a y e r s (ye l low and magenta forming l a y e r s ) .
3 2.0
2 1.0
u l o
#& -1.0
,” -2.0
.r > .r
ul c a,
4J W c
0
cn
yellow forming layer
f l j \ magenta forming layer
cyan forming layer
I I I I I
0.4 0.6 0.8 1.0 1.2 Wavelength (pm)
x
w .r 4J 2.0
yellow forming layer .- .r
cyan forming layer W ul \
magenta forming layer
0
S -4.0 0.4 0.6 0.8 1.0 1.2
Wave1 ength (pm)
Fig. 4.10 S p e c t r a l s e n s i t i v i t y curves f o r Aerochrome I n f r a r e d f i l m 2443 ( a ) and f o r High D e f i n i t i o n Aerochrome I n f r a r e d f i l m SO-127 (b ) a f t e r S l a t e r ( 1 9 7 5 ) . The s e n s i t i v i t y is the r e c i p r o c a l of t h e energy i n ergs/cm2 ( 1 e r g = 100 n J) of monochromatic r a d i a t i o n t o produce i n t h e i n d i v i d u a l l a y e r an equ iva len t n e u t r a l d e n s i t y of 1.0 when the f i l m i s g iven nega t ive process ing .
(Used by pe rmis s ion of Am. SOC. f o r Photogrammetry and Remote Sens ing . )
The nea r In fa red l a y e r i s a l s o s e n s i t i v e t o V i s i b l e r a d i a t i o n . However,
t h e q u a n t i t y of V i s i b l e r a d i a t i o n t h a t can be captured by t h i s f i r s t l a y e r i s
ignorab le when compared wi th t h e q u a n t i t i e s t h a t can be absorbed by t h e
fo l lowing l a y e r s of t h e f i l m , which show h igh s e n s i t i v i t i e s t o green and r e d
r a d i a t i o n . S ince much of t h e green is cap tu red by t h e second l a y e r , t h e
109
overlapping in sensitivity of the red sensitive (third) layer with the green
sensitive (second) layer is of minor influence. Therefore, owing to the
ordering of the layers in the false colour-film, a rather accurate
registration of red radiation (in the magenta forming layer) can take place.
The reduced effect of near Infrared radiation in the false colour-film results
in a better registration of natural objects, of which many are strong
reflectors of near Infrared, especially vegetation. At normal sensitivity, red
would predominate in most cases over the whole photographic scene (objects
with high near Infrared reflectance produce no or little cyan, therefore the
film transmits much red).
Because of strong scattering of Ultraviolet (UV) by the atmosphere,
little application is found in remote sensing of W photography. However, a
typical film-filter combination for UV photography may be mentioned, being the
Kodak Plus-X Aerographic film 2402 with the Kodak Wratten 18A filter. The
latter transmits the energy of the spectral range between 0.3 and 0.4 l~ m.
Special quartz lenses have to be used in order to transmit UV radiation also
below the critical wavelength (0 .35 II m) for glass of most cameralenses.
4.3. Non-photographic techniques
Other remote sensing techniques than aerial photography are required for
detection in the wavelength range of the Infrared larger than 0.9 p m. This
range covers solar radiation in the near and middle Infrared and earth
emission in the middle and far Infrared (see fig. 2 .2 ) . Alternative ways of
detection are needed, because lens systems cannot be used for focusing the
relatively broad spectral regions which are required for remote sensing in
these low energy regions.
An alternative way for detection of long wavelength radiation (as well as
for short wavelength radiation) was found in the so-called airborne line
scanner.
The multispectral airborne line-scanner (fig. 4.11) collects energy in
distinct wavelength ranges (channels or bands) of a scene below in a series of
scanlines each of which is perpendicular to the line of flight. The energy is
received by a rotating mirror. The rotation of the mirror is adjusted to the
velocity of the airplane in order to prohibit overlap or gaps between adjacent
scanlines.
110
The mirror reflects the energy into a collector; the energy is divided into
distinct bands and focused on a series of detectors. The scene is normally
built up of objects that vary in reflection or emission properties and can be
reconstructed when variations in signal strength get an address on the scan-
b) Scanner schematic
a ) Scanning procedure during flight
Fig. 4.11 The multispectral airborne optical mechanical scanner after Lillesand and Kiefer (1979). (Reprinted by permission of John Wiley & Sons, Inc.)
line. The signals can be stored on tape or displayed on a TV screen (or
cathode ray tube) as dark or light tones. When a photographic film is
transported at the same speed as the repetitive lines pictured on the TV
screen, a one-band photographic image can be derived as well (Rudd, 1974). The
technique is called multispectral scanning, OK MSS.
Detectors can be classified according to Baker et al., (1975) into:
- thermal detectors, based on increase of the temperature of heat-sensitive
materials; the signal is a result of the absorption of radiation, which
produces a variation in the detector material that is monitored
electrically;
111
- quantum-type detectors, based on the direct interaction of the incident
photon with the electronic energy levels within the detector material.
The quantum-type detectors can further be classified into (Baker et al., 1975) :
- photoemissive detectors, in which the absorption of photons from incident
radiation exites electrons within the sensitive material in such a way
that they are emitted through a Surface barrier; these detectors operate
in the Visible and Near Infrared up to about 1 u m wavelength;
- photoconductive and photodiode detectors; incident photons with an energy
greater than the energy gap of the detector material produce free-charge
carriers, which cause the resistance of the photosensitive material to
vary in an inversely proportional ratio to the number of incident
photons; these detectors are sensitive to wavelengths up to several 10's
of micrometres; they may be composed of lead salts (PbS and PbSe).
Next to the airborne line-scanner some other non-photographic techniques
have been developed. In image cameras OK TV-tubes like the Image Orthicon, the
scene is focused by a lens on a photoemissive cathode. This TV tube was
developed in the late 1930 's .
The so-called Vidicon tube, based on photoconductivity, is the most
widely used camera tube today. It is relatively small, low in cost and has a
long life-time. There are also modifications of Vidicon, such as: the Return
Beam Vidicon (RBV), Plumbicon and Silicon diode array camera tube. For more
information, one is referred to Baker et al.
Recently, a new concept has been developed, by which sensing, storage and
transfer can be done in a simple structure: the charge-coupled device (CCD)
and more specific the charge-coupled imager (CCI). A CCD consists of a linear
array of closely spaced MOS (= metal-oxide semi-conductor) capacitors formed
by depositing metal electrodes over an oxidized silicon substrate. The CCD
operates by storing information in the form of carrier charge packets, in the
capacitors at the Si-Si02 interface. These charge packets, which are generated
by absorption of the incident photon flux, are transferred serially to the
output element by a multiphase clock. A serial output is produced representing
the variation of the incident flux across a line (Baker et al., 1975). In
addition the CCI has an imaging device and seems to offer good prospects for
use as a multispectral strip camera.
Both the Vidicon and CCI are imaging sensors. A non-imaging sensor is the
112
radiometer, which measures the intensity of EMR emanating from objects within
its field of view and sensitivity range. Radiometers operate in the Infrared
spectrum at wavelengths larger than 1 IJ m and in the Microwave region
(photometers operate at shorter wavelengths). The radiometer for measurement
of the Infrared requires a stable internal reference, since errors may result
from the often variable radiation derived from components of the radiometer
itself. The output of the detector in a radiometer is an electrical signal
that is related to the radiance difference between the target and the
reference radiation.
A so-called spectrometer is a radiometer which has a dispersing element that
enables measurement as a function of wavelength. A n example is the NIWARS-
spectrometer. This spectrometer, designed for research and constructed by the
Institute of Applied Physics (TNO, Delft, The Netherlands), is based on the
simultaneous measurement of the radiant intensity of a standard reflector and
of the object (Bunnik, 1978). The spectral range of this spectrometer is
between 361 nm and 2360 nm. The bandwidth for the spectral ranges 361-753 nm,
629-1226 nm and 1165-2360 nm is resp. 17 nm, 25 nm and 42 nm. The detectors
are respectively Si for the first two intervals, and PbS for the last
interval. A reflectance spectrum is determined by the object-reference ratio
and by means of wavelength calibration of the three spectral intervals for all
the grating positions. The final data are stored on magnetic tape and a hard
copy of each spectrum is presented by a table and plot print.
4.4. Remote sensing from various platforms
Remote sensing can be done from different platforms, these being:
a) ground-borne platforms, observation stations like towers and other high
buildings;
b) airborne platforms, being balloons, aircraft and rockets;
c) space-borne platforms including satellites and other spacecraft.
Ad. a) The groundborne platforms are generally used in specific studies that
intend later application in airborne or space-borne missions.
Ad. b) Free-floating balloons may be used that have an attractive stability.
The balloon's altitude can be controlled by using ballast drops and gas
valving, while a trajectory control can be fullfilled to some degree by
knowledge of wind pattern.
113
Tethered balloons may be used for particular operations e.g. in archeology or
in forestry. Different payloads can be applied that may be controlled by radio
from the ground.Blimps, or observation balloons, are dirigable lighter-than-
air craft, mainly used by the news media as aerial television camera plat-
forms. Aircraft present a common type of remote sensing tool. Some convential
aircraft used for remote sensing are: Cessna 337, Beechcraft Bonanza A36 and
Lockheed YO-3A (see Colvocoresses et al., 1975). But also unconvential types
may be used such as helicopters, drones (unmanned aircraft) and sail planes.
In the atmosphere, the aircraft are subject to vibration created by the engi-
nes or other parts of the aircraft, and distortions due to both the dynamics
of the aircraft and the atmosphere. For this, corrections may be necessary in
preprocessing the remote sensing data. Upwards the atmosphere becomes more
stable, a high stability being reached at an altitude higher than about 150 km.
Ad. c) The history of rockets dates back as far as the year 1891
(Colvocoresses et al., 1975). The development of V-2 rockets in the Second
World War gave rise to a renewed interest, which resulted in the development
of spacecraft.
The launch of Sputnik in the year 1957 marked the definite start of remote
sensing from space, although already in 1946 space pictures were taken by a
photographic camera mounted on a V-2 rocket.
Several NASA-missions into space have been performed:
- unmanned spacecraft Nimbus program 1958 up to now,
TIROS satellites 1960-1965,
ERTS satellites (Landsat) 1972 up to now,
ATS satellite 1974,
SMS satellite 1974;
- manned spacecraft e.g. Skylab 1973.
Other programs of NASA e.g. the Apollo flights were mainly directed to the
observation of other planets and the earth's moon. Remote sensing of the
earth's surface was incidental in these programs, yet often of great
importance to the development of remote sensing.
Specifications of a number of satellites are presented in table 4.3. The
specifications comprise the name, country, operational period, altitude,
inclination, repetition period, wavelength bands, spatial resolution and the
hour of daytime coverage.
114
m m
3
01
m 3
T1
m
E
E2
m
0.
O
N
-I
1
-
3.
mc
m
-
-- m
- E
m
I m
0
B N
N
x
n
.9
N I
0
N
I .. x
m
D
'0 I
I
UY
..
.4
n
01
01
II
Y
Y
-. .A
m
u 0
d J
m
h
d 0
YI
OI
EE
a
01
Y
Y
.4
3
m
h .
3 4
m
.m
h
U
J0
1
3
N
m
m 4
<
115
Although photography of the earth is possible from space, it is normally
limited to manned space-missions. Unmanned satellites operate with MSS,
radiometric devices or radar. However, also RBV has been applied and future
application of CCD is likely.
The space programme of the USSR has to be mentioned. The Intercosmos
programme (1969-1976) and the rocket programme for geophysical research
(Vertical 1-5, 1970-1977) were directed to research the solar UV. The
Intercosmos programme has led to meteorological satellite programmes using the
Infrared (5-25 !J m) . Environmental research by remote sensing in the socialistic countries was
stimulated in 1975 by the foundation of a working group.
In 1976 the application of a multispectral camera (the MKF-6) in the manned
space flight Sojus-22 forms a remarkable event. Three filmtypes were used in
the MKF-6 together with filters covering six channels centred on: 480 nm, 540
nm, 600 nm, 660 nm, 740 nm and 840 nm. The first four channels obtain a ground
resolution of 20 m; the last two channels show a ground resolution of 40-50 m.
For more information, one is referred to Akademie der Wissenschaften der DDR
et al. (1980).
The problems encountered in achieving and maintaining the proper orbit and
providing the power for remote sensing, as well as the data transmission are
considered to be beyond the scope of this book. An advantage of the use of
spacecraft is that it operates outside the atmospheric influence and therefore
forms a relatively stable platform. However, onboard mechanisms provide
oscillations and there has to be a control on dampening of these oscillations
and maintainance of the proper attitude.
4.5. The nature of remote sensing data
The EMR coming from the sun OK other remote source interacts with the
atmosphere ( s e e section 2.8) and the objects at the earth's surface (see
section 2.5 up to 2.7). The radiation is modified by this interaction.
The signal derived from reflected solar radiation, which is received by the
detector, contains the following components:
- radiation reflected by objects at the earth's surface minus radiation
absorbed by the atmosphere between sensor and object;
- radiation reflected and scattered by atmospheric constituents (the
contribution of the atmosphere).
Factors which influence the interaction are:
116
/ ' source \'. /
' /
\ '
\ . \ -. \ --.
\ /
7"- \ /
- the dielectric properties of the materials at the earth's surface;
- the roughness of the surface;
- the position of the surface (slope and direction of slope) in relation to
the incident solar radiation.
The position of the sensor has to be defined in altitude above the earth's
surface (h) and in other geometrical parameters such as radius (r), grazing
angle ( 6 ) and azimuthal angle (0) (see Fig. 4.12).
platform 5'\
\I ' r=radius r \ h
... \
1 ---- --.
Fig. 4.12 Remote sensing scheme. h = altitude of platform r = radius, distance from the detector to the point of interest 0 = angle from the vertical or nadir measured from the platform B = grazing angle, complement of 0 0 = azimuthal angle, angle measured about the nadir from a
reference axis (usually north)
The extent of the atmospheric influence in remote sensing is dependent on:
a) the density of the atmosphere and the dynamics of atmospheric conditions;
b) the path length of rays between target and sensor;
c) the wavelength of radiation to be sensed.
Ad. b) With regard to path length, it will be clear that vertical transmission
will suffer the fewest losses from atmospheric interaction.
Furthermore, if spacecraft and high-altitude aircraft are compared with low-
altitude aircraft, the former will show a more pronounced influence of the
atmosphere owing to the greater path length.
Ad. c) The transmission of short wavelength radiation ( < 0.3 u m) is largely
obstructed by O2 and O3 in the atmosphere (fig. 2.14), while 0.3-0.5 u m
wavelength radiation is strongly scattered by molecules and other tiny
particles. Therefore, most satellites start their detection in the wavelength
117
zone beyond t h a t l i m i t (0.5 LI m), a l though a.0. Nimbus 7 and Landsat 4 , form a n
except ion t o t h i s s t a t emen t ( s e e t a b l e 4 . 3 ) .
4 . 6 . Ground- inves t iga t ions
The s i g n a l s ob ta ined by a d e t e c t o r from a remote s e n s i n g p l a t fo rm can be
compared f o r c a l i b r a t i o n wi th s i g n a l s acqu i r ed from r e f e r e n c e o b j e c t s . However,
t h e c a l i b r a t i o n of m u l t i s p e c t r a l scanning s i g n a l s i n t h e V i s i b l e zone i s
g e n e r a l l y done whi le t h e scanne r i s running ( s e e Higham e t a l . , 1 9 7 3 ) .
The d a t a acqu i r ed by a i r b o r n e or spaceborne s e n s o r s can a l s o be compared
with ground-measurements. The ground equipment should p r e f e r a b l y have t h e same
bandwidth a s t h e remote senso r , and t h e a tmospher ic c o n d i t i o n s a t t h e t i m e of
ground-measurements and remote measurements have t o be t aken i n t o account .
T e s t - s i t e s a r e u s u a l l y r equ i r ed and have t o be s e l e c t e d c a r e f u l l y i n o r d e r
t o o b t a i n in fo rma t ion v a l i d f o r much l a r g e r a r e a s . Fig. 4.13 i n d i c a t e s t h e
procedures t h a t can be followed f o r t h e s e l e c t i o n of t e s t - s i t e s .
Study of envi ronmenta l maps and r e p o r t s
t Visua l i n t e r p r e t a t i o n of mono- and mul t i t empora l s a t e l l i t e MSS imagery
P rocess ing of d i g i t a l HSS d a t a i n s e l e c t e d a r e a s
Ai rpho to - in t e rp re t a t ion of s e l e c t e d a r e a s
S e l e c t i o n of t e s t - s i t e s f o r ground measurements
Fig. 4.13 Procedures f o r s e l e c t i o n of t e s t - s i t e s .
The l o c a t i o n and t h e number of t h e measurements depend on t h e v a r i a b i l i t y
i n t h e t e s t - s i t e s a s d e t e c t e d by remote s e n s i n g and by f i e ldwork .
Some q u e s t i o n s a r e :
a ) What a r e t h e parameters t h a t have a marked i n f l u e n c e on i n t e r a c t t o n wi th
118
t h e EMR?
b) What i s t h e s p a t i a l v a r i a b i l i t y of t h e s e parameters w i t h i n t h e mapping
u n i t ?
There a r e two s i t u a t i o n s i n t h e s e s t u d i e s :
- t h e open s i t u a t i o n , when t h e remote s e n s o r s t i l l can be s e l e c t e d ;
- t h e c losed s i t u a t i o n , when t h e remote s e n s o r h a s a l r eady been s e l e c t e d .
The s t e p s t h a t can be fo l lowed i n t h e open s i t u a t i o n a r e i n d i c a t e d below.
Phase 1 :de te rmine d i f f e r e n c e s between mapping u n i t s / l i s t s o i l - , rock- and
p l a n t p r o p e r t i e s .
Phase 2: de te rmine q u a n t i t a t i v e d i f f e r e n c e s between mapping u n i t s e.g. C O l O U K
(Munsell S o i l Colour Char t ) , a lbedo , s p e c t r a l c h a r a c t e r i s t i c s .
Phase 3: d e f i n e c o n t r a s t s between mapping u n i t s .
Phase 4 : s e l e c t remote s e n s o r ( s ) .
The measurements i n t h e f i e l d a r e p r e f e r a b l y c a r r i e d o u t on p l a c e s where much
in fo rma t ion of l a r g e r u n i t s can be expec ted . Repeated measurements a t d i f f e r e n t
p l a c e s w i t h i n t h e same u n i t a r e c a r r i e d o u t t o d e f i n e s p a t i a l v a r i a b i l i t y . When
d e v i a t i o n s of t h e mean a r e e s t a b l i s h e d they have t o h e s t u d i e d and e v a l u a t e d
f o r t h e i r s i g n i f i c a n c e .
S t a t i s t i c a l p rocess ing of t h e d a t a enab le s t h e d e f i n i t i o n of s p e c t r a l
p r o p e r t i e s over a r e a s equal t o o r l a r g e r t han t h e r e s o l u t i o n element of t h e
remote senso r , and c o r r e l a t i o n of s p e c t r a l p r o p e r t i e s w i th p a r t i c u l a r m a t e r i a l
p r o p e r t i e s .
Genera l measurements, a p p l i c a b l e t o remote s e n s i n g i n t h e V i s i b l e , nea r
I n f r a r e d , f a r I n f r a r e d a s w e l l as Radar may i n c l u d e t h e fo l lowing:
- t opography /pos i t i on , shape and e l e v a t i o n p l o t t e d t o s c a l e ;
- p a r t i c l e s i z e , s t r u c t u r e , s u r f a c e roughness (by co rd l e n g t h o r t empla t e
and photographs) ;
- mineralogy of f i n e e a r t h ( < 2 mm) and c o a r s e f r amen t s (> 2 mm); shape and
c o a t i n g s of p a r t i c l e s ;
- s o i l cover ( s t o n e s ; l i c h e n s , burned m a t e r i a l , dung, s t r a w ) ;
- s o i l mo i s tu re c o n t e n t and o r pF v a l u e , p l a n t water c o n t e n t ;
- p l a n t h e i g h t and d e n s i t y (4: of coverage) ;
- l e a f a r e a ;
- c o n d i t i o n of f o l i a g e (g reen , m o t t l e s , d i sco lou red a t edges).
119
The photographs for application in surface roughness have to reveal shadows at
oblique illumination. The photographs can be taken from a vertical position
and by preference the sun should be relatively low in order to obtain shade.
They appear to be useful in the determination of micro-roughness.
In addition, dielectric measurements can be carried out with an ellipsometer.
which consists of a transmitter system that produces a polarized wave incident
on a sample. It has a rotatable linearly polarized receiver system. By
measurement of the angle of rotation of the receiver system, the ratio of
maximum to minimum values of power reflected by the sample and the angle of
observation, the dielectric properties can be evaluated (Lee, 1975).
When the remote sensing aid is fixed, the measurements are generally more
specific and may include:
reflectance (in laboratory and field) of rocks, soils and plants by
spectral photometers or filterband photometers (Visible and Near Infrared
missions);
insolation X = 0.3-3.0 pm (Visible and Infrared missions) including
azimuth and elevation of the sun, sunrise, sunset, duration of twilight
(related to navigation aspects in thermal Infrared missions), cloud
cover, quantitative measurements with a pyranometer involving continuous
recording of total incident radiation 0.3-3.0 u m from the full
hemisphere above the instrument;
ground temperatures (thermal Infrared missions), including surface
temperature, subsurface temperature, radiometric temperature (thermal
Infrared radiometer);
micrometeorological measurements (thermal Infrared missions), including
air temperature, relative humidity, wind velocity and direction.
The surface temperature can be measured with a so-called thermistor, a semi-
conductor which changes its electrical resistance as a function of its
temperature.
The data obtained in thermal Infrared missions are also of importance to
passive microwave sensitometry.
An example of reflectance measurement is discussed below (Agricultural
University, 1980).
Field measurements have been carried out with an EG&G spectro-radiometer
(Type 550/585). The speed of measurement is approx. 2 min. and the applied
aperture 20". When the measurements are carried out from a height of 2 m, a
120
surface-area of 0.4 m2 is measured on the ground. The apparatus can be fastened
on a plate which is connected to a tube. The latter is mounted on top of a
landrover (see fig. 4.14). During transport the device has to be removed.
The spectral range of the EG&G spectrometer is 400-825 nm. A face-plate painted
with Kodak white reflectance paint (Bas041 is used as a reference. When
measured at regulat intervals, the reference enables to normalize the
measurements thus making mutual comparison possible.
Measurements were carried out around 09.30 a.m. to obtain illumination angles
close to the Landsat crossing.
Fig. 4.14.EG&G spectrometer mounted on a landrover for measurement in the field.
For comparison with Landsat CCT, the field measurements on reflectance are
converted to a linear scale 0-255 corresponding to the Landsat hands in the
0.5-0.8 p m range. The sensitivity of the spectroradiometer as well as the
wavelength range sensitivity of the remote sensor have t o be taken into account
in this conversion.
121
Other spectrometers are often used in Dutch research such as the biomass meter
operating in the channels: 0.565-0.569 pm , 0.615-0.675 ~nn and 0.834-
0.846 pm
It is constructed by TFDL (Technical and Physical Engineering Service,
blageningen, The Netherlands) and has a light-weight measuring unit connected
to a tube. This enables to perform measurements from a height of 1 , 5 m above
the surface in holding the tube and measuring unit by hand above the target.
For large-scale airborne missions, reference objects larger than the ground
resolution can be placed in the field to serve as a reference during
recording. In small-scale missions, this is not applicable, and natural or
cultural objects of known reflectance have to be used for calibration of the
remotely sensed data, instead of, OK together with internal references.
Mapping units which are relatively homogenous may be used, but also objects
such as roads, houses and concrete dams. Much attention has to be paid in the
field to the selection of such reference fields. If no reference fields are
available other normalisation procedures are needed in comparing multitemporal
data.
In the sequence laboratory-field-remote sensing data, the spectral resolution
that may be obtained is decreasing, and the atmospheric influence is
increasing. In other words, the study in laboratory and field may reveal
aspects that cannot be studied from a great distance. Often, it will only be
possible to study broad intervals from a great distance, and the effect of
certain properties can only be shown to a limited extend.
4.7 Conclusions
The eye is an instrument offering u s the capability for detection in the
Visible part of the EM spectrum. There are three cone pigments which show
sensitivity peaks at wavelengths of 435 nm, 520-550 nm and 550-595 nm
respectively.
Colours can be produced by addition as well as by subtraction (or absorption)
of light of specific wavelengths. The so-called c?Jour circle may be used for
understanding these basic ways of colour composition. Furthermore, the ITC
Colour Chart may be used as an aid in description of photographic colours.
Detection of EMR may be done by photographic techniques which cover the
wavelength range between 0.3 u m and 0.9 p m. Filters and special films are
used for detection in specific wavelength ranges. The main photographic film
122
types are the panchromatic or black-and-white film, the true colour-film, the
Infrared black-and-white film and the false colour-film.
Non-photographic techniques are required for detection in the longer
wavelength regions. The airborne line-scanner may be used for detection in the
Visible and the Infrared. A special detector composed of heat-sensitive
material has to be used for far Infrared.
Remote sensing may be done from different platforms e.g. airborne and
space-borne platforms. The common airborne platforms are the conventional
aircraft but also other types such as balloons, helicopters and drones may be
used. Of all spacecraft, satellites are the most important aids for remote
sensing. The ERTS-satellites or Landsats are available for land mapping on a
small-scale basis. They employ four bands at 500-600 nm, 600-700 nm, 700-800
nm and 800-1100 nm respectively.
Ground investigations may be a support in selecting remote sensors and in
the processing of remote data; special measurements are often necessary.
The spatial variability of soil, rock and plant parameters in the mapping
units is essential. Therefore, a statistical approach is advised in obtaining
reflectance measurements (as well as other measurements) in the field. The
measurements should be applicable over an area equal to or larger than the
resolution element of the remote sensor.
Furthermore, reference fields have to be selected and defined according to
significant properties. The ground investigations have to be correlated with
the remote data in dependence of detector characteristics and have to be
corrected or normalized for atmospheric influence.
4.8. References
Agricultural University, Soil Science and Geology, 1980. Onderzoek naar de Methodiek van Visuele Interpretatie en Semi-automatische Verwerking van Satellietopnamen. L.H. Wageningen. Vakgroep Bodemkunde & Geologie, 5050- 048, The Netherlands: 43 pp.
Akademie der Wissenschaften der DDR, V E R Carl Zeiss Jena und Akademie der Wissenschaften der UdSSR, 1980. Sojus-22 erforscht die Erde. Akademie Verlag Berlin: 283 pp.
Baker, L.R., MacDonald Scott 11, R. e.a., 1975. Electro-Optical Remote Sensors with related Optical Sensors. Chapter 7 in Manual of Remote Sensing (editor R.G. Reeves). her. SOC. of Photogrammetry, Falls Church, Virginia: pp. 325-366.
Bunnik, N.J.J., 1978. The multispectral Reflectance of shortwave Radiation by Agricultural Crops in Relation with their Morphological and Optical Properties. Thesis Agricultural University, Wageningen, The Netherlands: 176 pp.
123
Bijleveld, J.H. and Rosema, A., 1980. A study of Satellite Remote Sensing Application and Mission Objectives in Developing Countries. EARS bv., Delft, The Netherlands: 164 pp.
Colvocoresses, A.P. et al., 1975. Platforms for Remote Sensors. Chapter 10 in Manual of Remote Sensing (editor R.G. Reeves), Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 539-588.
Davson, H. (ed.), 1962. The Eye. Vol. 4. Visual Optics and the Optical Space Sense. Academic Press, New York and London: 432 pp.
Eastman Kodak Cy, 1970. Kodak Filters. B-3. Gerritsen, F., 1972. Het Fenomeen Kleur. Cantecleer b.v. De Bilt, The
Netherlands: pp. 5-80. Higham, A.D., Wilkinson, B. and Kahn, D., 1973. Mulitspectral Scanning Systems
and their Potential Application to Earth-Resources Surveys. Basic Physics & Technology. ESRO CR-231, Neuilly, France: 186 pp.
Hunter, R.S., 1975. The measurement of Appearance, John Wiley & Sons, New York: 348 pp.
Judd, D.B. and Wijszecki, G.W., 1963. Color in Business, Science and Industry. John Wiley and Sons, New York.
Julesz, B., 1975. Experiments in the Visual Perception of Texture. Scientific American, April 1975: pp. 34-44.
Journal 1975-1: pp. 101-106.
York, Oxford University Press: 580 pp.
December 1977: D D . 108-129.
Karssen, A.J., 1975. The Production of a Cartographic Colour Chart.
Kaufman, L., 1974. Sight and Mind. An Introduction to Visual Perception
Land, E.H., 1977. The Retinex Theory of Color Vision. Scientific Amer
ITC-
New
can,
Lee, K. et al., 1975. Ground Investigations in support of Remote Sensing. Chapter 13 in Manual of Remote Sensing (editor R.G. Reeves), Amer. SOC. of Photogrammetry, Falls Church, Virginia: p. 805-856.
Lillesand, T.M. and Kiefer, A.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp.
Rudd, R.D., 1974. Remote Sensing: a better view. Duxbury Press, North Scituat Masachusetts: 135 pp.
Sabins, F.F. Jr., 1978. Remote Sensing. Principles and Interpretation. W.H. Freeman and Cy, San Franisco: 426 pp.
Slater, P.N., 1975. Photographic Systems for Remote Sensing. Chapter 6 in Manual of Remote Sensing (editor R.G. Reeves), Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 235-323.
Smith, J.T. (ed.), 1968. Manual of Color Aerial Photography. Amer. SOC. of Photogrammetry: 551 pp.
U.S. Geological Survey. Eros Data Center, 1981. Landsat Data Users Notes Issue no. 18.
Wijszecki, G. and Stiles, W.S., 1967. Color Science Concepts and Methods, Quantitative Data and Formulas. John Wiley & Sons, Inc., New York: 628 PP.
Young, R., 1964. Bringing Chaos Out of Order. Life, December 1964.
4.9. Additional reading
Bouma, P.J., 1971. Physical Aspects of Colour. Phillips Technical Library.
Boynton, R.M., 1979. Human Color Vision. Holt, Rinehart and Winston, New York:
Feynman, R.P., Leighton, R.B., Sands, M., 1970. The Feynman Lectures on
MacMillan and Co. Ltd. London and Basingstoke: 280 pp.
438 pp.
Physics. Chapter 35. Adison-Wesley Publ. Cy-Menlo Park, California.
124
Gregory, R.L., 1966. Visuele waarneming. De psychologie van het zien (original title: Eye and Brain). Wereldakademie, W. de Haan/J.M. Meulenhoff: 254 PP .
Heyse, P. en Craeybeckx, A.S.H. (ed.), 1959. Encyclopedie voor Fotografie en Cinematografie. Elsevier, Amsterdam: 897 pp.
Werblin, S., 1973. The Control of Sensitivity in the Retina. Scientific American, Vol. 228, Nr. 1: p. 70-80.
125
5.PROCESSING OF REMOTE SENSING DATA AND AUTOMATED CLASSIFICATION
Remote sensing data may contain the following information:
-signal strength in one or more wavelength bands, characterizing materials at
the earth's surface;
-parallax differences, characterizing the geometry of objects at the earth's
surf ace ;
-distance between target and source as acquired by active radar systems.
The spectral information is recorded on photographic film or on magnetic
tape. These records have to be processed to obtain imagery that can be used for
interpretation. A number of aspects in photographic and digital processing are
treated in this chapter (par. 5.1 and 5 . 2 ) . Pre-processing and image-
restoration are discussed briefly, while interactive processing of digital data
is dealt with in more detail. Furthermore, some attention is paid to
information extraction (par. 5.3) and automated classification of digital and
analog data (par. 5 . 4 ) . For parallax differences, the reader is referred to
chapter 7 and for active systems to chapter 13.
5.1. Technical aspects in the processing of photographic imagery
Photographic processing involves either black-and-white technology or
colour-technology.
Interaction of light with the silver halide crystals of the emulsion is
described briefly in section 4.2. Processing of black-and-white, true and false
colour-films is treated in the same section to the extent necessary for
understanding the detection of EMR by photographic techniques.
Some technical aspects of processing are discussed below.
The light and dark spots or grey tones of an image are systematically
related to the amount of exposure of a film. Measures of darkness or lightness
at given points on a film are:
- the opacity 0 = I i / ~ P;
- the transmittance T = Ip/Ii
where Ii = total incident radiation upon the film,
126
I = radiation passing through the film; P
- the density D = log 0 = - log T ( 5- 3)
Instruments designed to measure density on transparent film are called
transmission densitometers. When they are able to measure density on paper
prints, they are called reflectance densitometers (see a.0. Canadian Standards
Association, 1964). The densitometer may have a scanning-device to obtain
density values at regular intervals over the image area. The densitometry of
colour-films is complicated by the fact that the three dyes used have
absorption curves that overlap one another.
There are two basically different measures of colour-film density, being: the
integral or combined density of the three layers and the analytical or
individual density of each layer.
The integral spectral densities are measured with narrow band filters
corresponding to the maximum absorptances of the three dyes. Analytical
spectral densities are usually determined indirectly by computati.on from
integral spectral densities, by using specifications of the film manufacturer.
0
In photographic processing attention has to be given to aspects such as:
characteristic curve, spectral sensitivity, modulation transfer function,
dimensional stability, granularity, silver reduction and printing-paper
(Barrett and Curtis, 1976). Most of these aspects are discussed below. The so-
called characteristic curve, or D - log E curve, of photographic film shows density (D) as a function of log-exposure (Ext). It has an S-shape and in the
central part, the density is nearly proportional to the l o g of the exposure.
The ratio a/b is referred to as the film "y" (see fig. 5.1)
Two other properties can be determined aided by the characteristic curve,
being density resolution, which is the smallest measurable density range (dr),
and radiometric resolution, or the smallest detectable exposure range (rr).
For spectral sensitivity of the different film types, the reader is
referred to section 4.2. The film types mentioned are all sensitive to Visible
radiation and must therefore be developed in complete darkness.
The modulation transfer function (MTF) describes the accuracy of
reproduction of test-objects in which the luminance varies sinusoidally with
the distance (Thompson ed., 1966). It is recorded as a function of spatial
frequency (cycles/mm). At each frequency (f) of sinusoidal intensity patterns
127
---+ Log exposure
Fig. 5.1 Characteristic curve for photographic film.
(white bars gradually passing into black bars), the values of maximum and
minimum density are determined and converted to linear relative exposure
values by means of the D - log E curve of the emulsion. The contrast, or
amplitude at each frequency (f), is expressed as image modulation (M E(f)) by the following equation (Slama ed., 1980; Eastman Kodak Cy, 1972):
The so-called resolving power of a film is a visually determined measure
of the number of line-space pairs per millimeter. The value of resolving power
will be different for different developers, and will change with the
development time (Thompson ed., 1966).
Granularity of a black-and-white photograph or the granular pattern of
discrete particles of metallic silver can be observed under a microscope or
may be measured by a microdensitometer. Graininess is the subjective
impression of non-uniformity in the image by an observer e.g. at 12 x
magnification.
The so-called Root-Mean-Square Granularity (G) can be determined from the
standard deviation of the density measurements a K(D) and from the diameter
of the scanning aperture (K) after Barrett and Curtis (1976):
G = K a K(D) (5-5)
MTF's along with data on resolving power and granularity provide information
on the imaging capabilities of emulsions. For example, an emulsion with good
128
MTF (high response to high spatial frequency), high resolving power and low
granularity will record small details.
In processing, it is usually necessary to control the density of the
product. This may be done by a controlled removal of the silver from the
negative (reduction) or by "dodging" to decrease the density range. Dodging
may be done with the aid of automatic dodging-printers, or manually by
inserting tissuepaper or a mask (Barrett and Curtis, 1976).
The dimensional stability of the film has to be high; that is, swelling
and shrinkage have to be low, in order to limit distortion of the image.
Polyester base material e.g. ESTAR-base of Kodak aerial-film is superior to
cellulose ester film bases.
Carman and Martin (1968) studied the dimensional changes in ESTAR-base aerial-
film used in a Wild RC8 camera and stated that the most serious dimensional
changes are due to the low relative humidity in the camera compartment.
In order to reduce swelling during processing and to improve the dimensional
stability, aerial photographic paper consists of a photographic paper base
coated on both sides with a cellulose ester lacquer (Thompson ed., 1966).
The processing of colour-films requires special attention for dyeing,
colour-balance and resolution. The basis for colour separation in the dye-
forming layers is the added sensitivity by sensitizing dyes that provide
sensitivity to another portion of the spectrum above the natural sensitivity
to blue light. A colour-former, or dye-coupler in the emulsion layer reacts
with a colour-developer agent to produce specific coloured dye. The resultant
dye must have definite spectral characteristics and must be stable to provide
permanency of the colour-image (Smith ed., 1968).
The colour reversal process is described in section 4.2. Unfortunately as
indicated in that section, the layers are not perfect absorbers. Of the three
layers, the yellow forming layer most closely approaches an ideal absorber.
However, the specific ordening of layers in false colour-film enables a rather
good registration of respectively Near Infrared, green and red.
The prime objective of true colour-photography is to reproduce the colours of
the original scene. Colour-print materials, colour filtration and masking as
well as colour printing exposure should be carefully chosen. Use can be made
of analyzing/balancing printing systems.
In determining the need of colour correction, the density to log E-exposure
129
curves of the cyan, magenta and yellow dye layers are very helpful. These
curves should lie on top of (or very close to) each other.
Resolution, or the ability of film or paper to record very fine detail, is
important in determining the usefulness of the material. Lens properties,
nature of emulsion (e.g. granularity), film speed and exposure are only some
of the factors that have impact. Generally, true colour-films are
characterized by lower spatial resolution but higher contrast than
panchromatic films.
In multispectral photography and scanning (MSP and EISS), there is a need
for techniques that enable combinations of the individual products. For this
purpose, positive black-and-white imagery representing the reflectance of
scenery in different wavelength hands can be projected superimposed and in
different colours. In this way, through the use of appropriate filters
different imagery may be produced e.g. blue, green and red light projectors
are used for respectively blue, green and red band imagery to produce true
colour, and the same series of projectors for respectively green, red and Near
Infrared band imagery to produce false colour. Multitemporal one-band
combinations may be produced as well. This way of combining is normally
described as the additive colour technique.
Willems et al., (1977) discuss recording processes based on other light-
sensitive compounds than silverhalides. One of these processes, the so-called
diazo-process is of importance for multispectral remote sensing, since it
offers the possibility to contact-print positive, or negative black-and-white
imagery, in colour. The coloured images can be combined to colour-composites
by subtractive colour techniques.
A diazo-film consists of a transparent acetate base containing a slow reacting
Ultraviolet sensitive emulsion with diazonium salt. On exposure to Ultraviolet
radiation, the diazonium salt desintegrates and reacts with a coupler, which
prevents formation of dye at the exposed places. On the other places so-called
azo-dye is formed; the reaction can be accelerated by ammomium vapour or
liquid. The use of vapour is preferred since it does not involve serious
dimensional changes of the acetate film.
The diazo-materials possess a limited density range. Fig. 5.2 shows density-
ranges of yellow diazo-film obtained from a black-and-white positive with
exposure times ranging from 1 min. to 6 min.
130
1.5-
n
1.0-
0 .5-
0
0 0
0 0
0 0 0
0 0 0
0 .
0 . X
0 X A
+ BW
o 1 min. x i A 0 2 min.
( L ) u y ' A A 3 min. 0 4 min. x 5 min. A 6 min.
5 10 15
0
0
I 1 I
Fig. 5.2. Density for grey scale of positive material and a series of yellow diazo-material exposed according to a time range from 1 min. up to 6 min. (constant development).
Diazo colour-films are available in a number of colours a.0. yellow, magenta
and cyan. The colours mentioned are used for the production of colour
composites. The variability between the diazo-materials of different orders
and the density differences between the yellow, magenta and cyan diazo-
materials offer special problems in obtaining colour composites of good
quality. In spite of these problems, the low price of these materials causes a
high application rate.
In storage, the acetate films present problems with regard to their
dimensional instability. However, diazo-film on a polyester base has come on
the market recently and shows an improved stability (Pinot de Moira, 1974;
Venema, 1980) .
5.2. Processing of digital data
The records of non-photographic sensors have to be converted into one of
the following forms:
- photographic imagery on transparent film or paper;
- computer compatible (digital magnetic) tapes (CCT) and discs;
- computer print-outs, plots, diagrams.
Computers can interact with optical data, which makes it possible to store a
picture in digital form or to produce a picture from digital data.
The principal types of equipment of such computers are (Barret and Curtis,
1976) :
- drum microdensitometer and recorder;
- cathode-ray tube (CRT) readers, writers and displays;
- electron beam and laser recorders.
The so-called image-restoration process compensates for data errors,
noise and geometric distortions in the scanning and transmission processes.
In order to make the image resemble the original scene as much as possible,
the process may include the following (Sabins, 1978):
- correction for the drop-out of scanlines (e.g. Landsat 1, data from one
of the six detectors were not recorded owing to a hardware" problem);
- correction on the detection level (with time, detectors may drift to
higher OK lower levels than the original one);
- correction on horizontal offset of scanlines;
- correction for atmospheric scattering to improve image contrast;
- correction for geometric distortions which are due to variations in
platform attitude, velocity and altitude (nonsystematic distortions) OK
scan skew and distortions or variations in scanner mirror velocity
(systematic distortions);
- corrections on noise due to storage, transmission and ground reception of
data.
The effect of scanner distortions is low in satellite scanners having a small
* Hardware: mechanical and electronical part of computer. Software: programs for input of data, processing and output of computer.
132
scan angle (5.8" for Landsat), and high in airborne scanners that have scan
angles of 45" or 60" (Sabins, 1978).
The two basic methods of data processing are batch processing and
interactive processing. In batch processing, the desired processing programs
are specified beforehand and the operator sees no results until the processing
has been completed. Batch processing is useful a.0. for image restoration and
enhancement.
In interactive processing, the operator may provide instructions and
information to the computersystem at various stages in the processing cycle.
Special-purpose computers are needed for interactive image-processing-systems.
They include units such as tape-reading devices, display devices and control
panels. Sabins (1978) listed a number of commerciable available interactive
systems (see table 5.1).
Table 5 . 1 Commercial available interactive-processing systems.
Processing system Manufacturer Address
MDAS Bendix Aerospace 3621 South State Road, Systems Division Ann Arbor, Mi. 48107
Series 9 Comtal Corp. 169 North Halstead,
IDIMS ESL Inc. 495 Java Drive,
IMAGE 100 General Electric Co., P.0 Box 2500,
System 101 Stanford 650 N. Mary Avenua,
Pasadena, Ca. 91107
Sunnyvale, Ca. 94086
Space Division Daytone Beach, Fla. 32015
Technology Corp. Sunnyvale, Ca. 94086
As an example, an imteractive digital processing method is described
below (Donker and Mulder, 1977). The software has been written in Fortran IV.
Use is made of the PDP 11/45 computer, a grey-scale printer and CCTs of
Landsat. A selected part of the CCT is reformated and stored on magnetic disc.
Half of the disc is used for storage of calculation results. In this way, only
3.4 percent of the original Landsat frame can be stored that is 260.000
pixture elements (pixels).
The following steps have been distinguished in the analysis of Landsat MSS-
data:
133
a. Display of individual MSS bands (level by level display) and histogram
equalisat ion.
In histogram equalisation, the whole range of levels of radiance is subdivided
into intervals that contain roughly the same amount of pixels. Images with
enhanced contrast may be produced in this way. However, it may be necessary to
shift certain levels in order to enhance the imaging of certain features.
Level by level display, followed by ground investigations enables the
selection of radiance levels which are significant to the purpose of the
study. This, together with histogram equalisation produces particular images
of the individual spectral bands.
b. Feature plane,
At this stage a number of radiance levels per band are known to be significant
for the purpose of the study. From each type, a number of pure pixels are
sampled, that is the x-y coordinates are read from the image print-out. A
feature plane plot of the selected sample-set of all combinations of two of
the four spectral bands (six combinations for Landsat) is displayed. In fig.
5.3 the feature plane plot of bands 7 and 5 of the Roermond test-site is given
as an example.
7
30
20
10
0
a r a b l e
w a t e r I * I . I . I
1 a n d
5
0 10 20 30 40 50
Fig. 5.3. Feature plane plot of bands 7 and 5 of the Roermond test-site after Donker and Mulder (1977).
134
The feature plane plots enable us to obtain insight in the structure of the
spectral data. Contrast and intermixing of clusters can be evaluated. In Fig.
5.3 a low contrast of surface waters with towns, of scots pine forest cover
with several other forest cover types, and the intermixing of arable land with
villages, can be observed.
C. Principal component transform (PCT).
The spectral vectors of the sample set can be transformed linearly to new
variables (principal components or PCs) by digital processing. The first new
variable (PC1) has to account for as much of the total variance as possible.
The second new variable (PC2) has to account for as much of the total
remaining variance, etc. In this example, the PC1 and PC2 together account for
98 X of the total variance of the sample-set. Therefore, there is no need for
PC3 imagery and thus a significant reduction in the number of data is
attained.
The principal components of the Roermond test-site were as follows:
Ipcl = (0.2 x 14) + (0.4 x Is) + (0.8 x I ) + (0.5 x 17) 6
Ipc2 = (0.5 x 14) + (0.7 x Is) - (0.2 x Is) - (0.4 x I ) 7
The PC1 is a weighted summation of the 4 MSS channels; the PC2 offers a high
contrast between vegetated and non-vegetated areas. Together, they provide for
most of the information contained in 4 bands and data reduction is obtained.
d. Rotation of the principal axis.
One can judge from the PC1 - PC2 plot, whether rotation of the axes over a certain angle might be needed to obtain maximum distance between spectral
clusters that are significant for the purpose of study. Fig. 5.4 illustrates
the result of a 30' rotation by digital processing; the elongated water
cluster after rotation is more OK less parallel to the rotated PC1 (PC1'); so
are a number of land use classes. The result is an improved contrast and a
better display of spectral variability between several spectral classes.
e. Colour coded imaging.
The pcl and pc2 of' pel' and PC2' images are printed together in different
colours e.g. red and green. Thus futher data reduction is obtained by
135
60.
combining two images into one. There is no forced classification, the final
evaluation is left to the interpreter.
I
pc 2 50-
10 20 30 40 50 60
pc2 30' Rotation
Fig. 5.4.Feature plane formed by PC1 and PC2, and PClt and PC2' after 30" rotation (Donker and Mulder, 1977).
5.3 Information extraction process.
Information extraction processes utilize the decision-making capability
of computers to identify and extract specific information (Sabins, 1978).
It is possible to use ratios of the intensities in the different bands. A
material may have the same ratio value regardless of variations in
illumination as occuring in hilly terrain. The shadow areas in hilly terrain
do not receive direct sunlight but have a certain amount of diffuse light.
Although intensity in these areas will be relatively low, the ratio can be
diagnostic (see fig. 5 . 5 ) and may reveal material-properties. However, it
eliminates the expression of topography.
Change detection can be performed in studies of multitemporal data. The
first step is geographic registration of the images involving geometric
corrections with the aid of control points. After proper geometric
registration and correction for atmospheric conditions, the intensities in one
136
4 0.5-0.6 urn
I
\ I I
5 4 / 5 0.6-0.7 pm
-t- ___c
nor thwes t southeas t
Sandstone r e f l e c t a n c e
1) band I band I r a t i o
sun1 i g h t
shadow
28 42 0.66
22 34 0.65
Fig. 5.5.Ratio band 4 / band 5 (Landsat) of sandstone exposed to direct sunlight and in shadow after Sabins (1978) .
image may be subtracted from those of the corresponding image. Positive and
negative values indicate change, zero means no change. For this purpose,
colour-coded ratio-imagery is also very useful.
5.4 Automated classification
Pixels can be classified during processing. The classes are defined
according to the statistical properties of the data, or according to the
analysis of spectral signatures in training-sets. In section 5.2 an interactive
method is discussed to process the data in such a way that an image is
constructed which has a maximum capability for detection. The interpreter is
expected to perform the final interpretation.
Below, methods are discussed which can be used to arrive at a definite
137
automated classification of the objects (e.g. vegetation, rock outcrops and
soil surface).
Sabins (1978) distinguishes two types of classification: the supervised and
unsupervised classification.
Supervised classification uses independent information e.g. spectral
reflectance data to define training-data for establishing classification
categories. Unsupervised classification only uses the statistical properties
of the data for classification. Objects with high contrast e.g. agricultural
land, forested land, as opposed to water bodies, can be classified according
to the unsupervised classification method. However, to go more into detail in
landscapes with a high variability, generally requires interactive processing
methods, visual interpretation and ground-investigations to enable (supervi-
sed) classification.
One may use PC data or unmodified intensity values from three or more channels
for supervised classification. Training-sets and feature space plots are
composed and classification is left to the computer. Software can be developed
in such a way, that for each point in the feature space, the distance to the
centres of clusters formed by the different feature classes can be calculated.
The minimum distance determines the class to which a point in the feature
space belongs. Of course, the training-set, the spatial variability of the
land features and the discriminating capability of the remote sensor are of
great importance for the quality of the final classification.
Image features can be analysed according to their form and density with the
aid of an image-analysing computer. With the Quantimet 720 (Imanco), the image
is scanned at a low speed and detection is possible in more than thirty grey
levels. Measurements can be obtained from: surface area, intercept, chord
length distribution, perimeter, count or number and optical density of
features . The intercept measurements involve the measurement of the number of chords
(both vertical and horizontal) formed by scanning-lines cutting the detected
features.
Feature measurements can be obtained by the operator interactive method (the
features are selected by light pen) and by function computer methods. The
latter involves feature-classification, that is form-separation and
classification. The features are often identified beforehand, and the
Quantimet is used to obtain quantitative data about area, size, form, etc. of
the features. However, form and density can be used for supervised
138
classification itself.
The Quantimet has been applied in analysing images with high contrast. A
reasonable result has been archieved in distinguishing and quantification of
grasslands and forest areas on Landsat imagery. Other application in image
analysis for remote sensing is limited e.g. the characterization and
quantification of different forest cover types as depicted on large-scale
photographs, appeared to be impossible in cases where soil and tree-crowns
could not be discriminated either on the basis of their density values or
where tree crowns appeared to be interconnected on the transformed imagery
(Mulders, 1977).
5.5. Geometrical aspects
The geometrical aspects include the form and position of objects as
depicted by a specific remote sensor.
Any remote sensing instrument measuring reflected radiation in its angular
field of view is a perspective sensor, since there exists an angular
relationship between the sensor and the object. Furthermore, the angular
relationship between the incident radiation and the object may have impact on
the radiation measurement. Therefore, the slope and position of the object in
relation to the incident radiation and sensor determine the phenomena that can
be measured by the sensor.
Consequently, for a correct classification of objects in accidented terrain,
the geometrical aspects have to be taken into account, which forms an extra
complication. It is for this reason that most successful classifications have
been carried out in flat terrain.
5.6. Conclusions
A remote sensor receives Em, which results either in a latent image of Scenery upon interaction with silver halide grains of a film emulsion
(photographic techniques), or is recorded in analog voltages on magnetic tape
OK disc (non-photographic techniques).
Both types of data have to be processed to produce imagery for interpretation.
The photographic processing involves a relatively great number of variables. A
proper set of processing conditions has to be chosen, which requires skill of
the operator.
Diazo-processes deserve special emphasis in enabling combinations of
multispectral images OK multitemporal images in an inexpensive way.
139
If skill is required for photographic processing, this is certainly true for
digital processing. Computer Science is a profession.
Batch processing according to specified programs is useful in image-
restoration and image-enhancement. Generally, interactive processing is
performed in the production of imagery from digital data for environmental
surveys, which involves various steps in decision making.
PCT can be used for data-reduction and improvement of contrast. Information
extraction of digital data may be done by the application of ratio values.
Change detection is a technique for evaluation of multitemporal data, which,
of course, can only be applied if the data are geographically registered.
Generally, the operator intends to produce an image for interpretation, and
fieldwork is felt necessary for final identification. However, automated
classification reaches higher and is intended to come to a final classifica-
tion. High-contrasting material objects may be classified succesfully, low-
contrasting natural objects, or rapidly changing terrain conditions, often
prevent correct automated classification.
5.7. References
BaKKett, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. London, Chapman and Hall: 336 pp.
Canadian Standards Association, 1964. Diffuse Transmission Density. CSA Standard 2 7.0.2.1.. Ottawa, Canada: 35 pp.
Carman, P.D. and Martin, J.F., 1968. Causes of Dimensional Changes in Estar Base Aerial Film under Simulated Service Conditions. The Canadian Survey OK, Vol. XXII, No 2: pp. 238-246.
Donker, N.H.W. and Mulder, N.J., 1977. Analysis of MSS Digital Imagery with the Aid of Principal Component Transform. ITC-Journal 1977-3: pp. 434-466 (presented in 1976 ISP Commission VII).
Eastman Kodak Cy, 1972. Properties of Kodak Materials for Aerial Photographic Systems. Vol. I: Kodak Aerial Films and Photographic Plates.
Mulders, M.A., 1977. Application of Teledetection in Pedology. Ier Colloque PCdologie TClCdCtection AISS ( I S S S ) , Rome: pp. 311-324.
Pinot de Moira, P., 1974. Diazo Processes. The Journal of Photographic Science. Vol 22: pp. 187-193.
Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. Vol. I. Theory, Instruments and Techniques. Amer. SOC. of Photogrammetry, Falls Church, Virginia: 867 pp.
Sabins, F.F. JK., 1978. Remote Sensing. Principles and Interpretation. 1J.H. Freeman and Cy, San Francisco: 426 pp.
Slama, C.C. (ed.), 1980. Manual of Photogrammetry. 4th edition. Amer. SOC. of Photogrammetry. Falls Church, Virginia: 1056 pp.
Smith, J.T. JK. (ed.), 1968. Manual of Color Aerial Photography. her. SOC. of Photogrammetry, Falls Church, Virginia: 550 pp.
Thompson, M.M. (ed.), 1966. Manual of Photogrammetry Vol. I.3t-d edition.
140
American SOC. of Photogrammetry: 536 pp.
Reproduction. ITC-Journal 1980-1: pp. 140-142.
VOOK Zilver. IGT-nieuws 30, NK. 2: pp. 33-39.
Venema, D., 1980. The Use of Diazo Colour Film in Remote Sensing Imagery
Willems, J.F., Brinckman, E., Delzenne, G. en Poot, A . , 1977. Alternatieven
5.8. Additional reading
Agterberg, F.P., 1974. Geomathematics. Mathematical Background and Geo-Science Applications. Elsevier Scientific Publishing Cy, Amsterdam: 596 pp.
Cutbill, J.L., 1971. Data Processing in Biology and Geology. Publ. for the Systematics Association. Academic Press, London: 346 pp.
Hall, E.L., 1979. Computer Image Processing and Recognition. Academic Press, New York, London: 584 pp.
Hammond, R. and McCullagh, P., 1974. Quantitative Techniques in Geography: An Introduction. Clarendon Press, Oxford: 318 pp.
Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp.
Pratt, W.K., 1978. Digital Image Processing. John Wiley & Sons, New York: 750 pp.
Rietbergen, D. and Steijn, L., 1972. Computers. Moderne Slaven in een Nieuwe Tijd. Samson Uitg. N.V., Alphen aan den Rijn: 191 pp.
Schllpfer, K., 1980. Kopierschichten: sensitometrische Eigenschaften und Anwendung. UGRA Auftrag 1/2, St. Gallen: 24 pp., 35 Beilage.
Wolf, H . , 1976. Der Einsatz von Diazofilmen in der Druckformherstellung Deutscher Drucker, NK. 22: 2 pp.
Wijzecki, G. and Stiles, W.G., 1967. Color Science. Concepts and Methods. Quantitative Data and Formulas. John Wiley & Sons, Inc. New York: 628 pp.
141
6.IMAGE CHARACTERISTICS
Most images jointly possess the property of being structures of grey or
colour tones. However, it will be apparent from the previous chapters, that
there are large differences between photographic imagery on one side and
images derived from non-photographic sensors on the other side. General
characteristics of imagery such as resolution and scale (par. 6.1), tone and
contrast (par. 6.2) are defined in this chapter.
Furthermore, examples are presented on different types of images, being a
first introduction to the image products of remote sensing (par. 6 . 3 and 6.4).
Image enhancement techniques are discussed in par 6.5.
6.1.Resolution and scale
Resolution concerns the minimum separation between two objects, that is
the distance at which the objects appear distinct and separate in an image.
Objects that are spaced closer together than the resolution limit do not
appear as single objects.
Scale is the ratio of the distance between two points on an image to the
corresponding distance on the ground. The image-scale is determined by the
angular field of view and altitude of the remote sensing device, and the
magnification factor in reproduction of the image.
Without magnification, the scale (S) of airphotos can be calculated as
follows:
where c = focal length in m and Z = camera height above the ground in m.
Ground resolution or spatial resolution, that is the ability to resolve
features, can be calculated for aerial photography (Sabins, 1978) by:
Rg = Rs.c/Z (6-2)
where R = ground resolution in line pairs (one black and one white line) per g
m.
Rs = system resolution or resolving power in line pairs per mm,
142
Z = camera height above the ground in m,
c = camera focal length in mm.
Radians are used to describe the so-called angular resolving power (the
radian or rad is the angle subtended by an arc of a circle having a length
equal to the radius of the circle; since there are 2 TI rad in a circle, a rad
is equal to 57.29'). The angular resolving power of a system may be calculated
by dividing the length in m of the subtended arc between the closest two lines
on the ground (that can be depicted by the system) by the distance in m
between the remote sensing system and the ground.
In remote sensing with non-photographic sensors, another term is needed,
being: the instantaneous field of view (IFOV), which is determined by the
instrument's optical system and the size of the detector element. It is a
measure for the resolution of scanning devices; the time of recording for one
scan is divided into small instants, so that at any one instant only EMR from
a small part of the total scan area is being recorded.
The IFOV or 6 of a system in rad is given by (Lillesand and Kiefer, 1979) :
where D = length in m of subtended arc corresponding to the diameter of the
circular ground area viewed,
Z = flying height in m above the terrain.
The terrain characteristics may be such, that objects smaller than the
ground resolution are depicted. This aspect is described by the detectability.
The detectability is the ability of an imaging system to indicate the
presence or absence of an object. When the contrast of an object with its
surroundings is very high, it may be detected even when its dimensions are
smaller than the ground resolution, since it influences to a great extent the
reradiation of the resolution element.
One has to distinguish imaging and non-imaging detectors. If one uses a
photographic film as a detector, an image is formed from the field of view by
interaction of radiation with silver halide grains. The radiation is composed
of reflected radiation from different objects within the field of view, as
well as from so-called airlight (the attribution of light from the atmosphere
between object and sensor). The radiation is directed t o the photographic film
143
by a lens system. The spatial resolution can be calculated according to
equation 6-2, where Rs is amongst others dependent on the granularity and
sensitivity of the film.
The non-imaging detectors measure the total radiation of their IFOV in one or
more spectral bands. An image may be produced by an imaging device such as a TV
system, through composition of the IFOV signals, which thus act as picture
elements (pixels). The spatial resolution of the non-imaging detector is
determined by its IFOV and the speed of detection in relation t o the speed of
the remote sensing platform. For instance, a line-scanning device may show
overlap between adjacent lines resulting in a smaller effective resolution
element than its IFOV.
When spatial resolution of a line-scanning device is given, the quality in
relation to the number of pixels per mm that are shown on the image, and the
scale of the imagery can be indicated (see table 6.1).
Table 6.1. Spatial resolution of line-scanning devices and image quality.
spatial resolution image quality in m poor ( 4 pixels/ fair ( 8 good (12
mm) but tolerable pixels/mm) pixels/mm)
distance scale distance scale distance scale in m/mm in m/mm in m/mm
10 40 1: 40,000 80 1: 80,000 120 1: 12,000 30 120 1:120,000 240 1:240,000 360 1:240,000 70 280 1 : 280,000 560 1:560,000 840 1:840,000
Image quality has to be considered separately from recognizability,
detectability and resolvability of objects (oral communication Ir. Loedeman).
An example may illustrate this: although the image quality may be good, a row
of poles is not directly recognizable as such on radar imagery; it has to he
interpreted from the imaging properties of the system. The row is detectable
but individual poles are not resolved separately.
6.2. Grey tone, contrast and colour
Brightness is a sensation of the eye related to the intensity of light.
The brightness variations of a Black and White image may be calibrated with a
grey scale. In practice, a mental concept of such a scale is used: the so-
called grey tone e.g. light, intermediate and dark tones.
Image contrast may be defined as the ratio between the reflecting power
144
of the brightest (Bmx in W) and darkest (Bmin in W) parts of the image, the
so-called contrast ratio (Cr):
Colour vision is dealt with in par 4.1. For the processing of photographic
films, the reader is referred to par. 4.2. The notations given by the colour-
chart (plate 3) if used as a COlOUK characteristic, provide a rough measure
for the amount of dye in the film and illustrate the subtractive COlOUK
formation. The use of a vector notation for the transmitted light enables to
understand the observed COlOUKS on the imagery (see Fig. 4.6).
6 . 3 . Airphotos
Basically an airphoto presents a structure of grey OK colour tones
(Bennema and Gelens 1969), which enables the recognition of objects.
Particular tone features may he indicated, such as:
- grey (or colour) tone and grey (OK colour) tone changes related to the
reflection of light from the surface of objects;
- shadows of objects being helpful in recognition of high features such as
trees and houses;
- mottling OK spots in darker or lighter tone than the main surface,
usually with an irregular pattern, shape and size.
Size and arrangement of objects can be described by structures, patterns
and textures. Pattern is concerned with the spatial arrangement in repeated
sequence and/or characteristic order of objects. Texture concerns the
repetition of objects too small to be considered as individual elements
(Bennema and Gelens, 1969).
The boundary between structure and texture can he fixed at 1 mm. In
relation to scale, 1 mm means:
1: 5.000 - 5 m 1: 40.000 - 40 m
1:10.000 - 10 m 1:100.000 - 100 m 1:ZO.OOO - 20 m 1:500.000 - 500 m
The following subdivision of textures may be used:
fine < 0.2 mm
medium 0.2 - 0.5 mm
coarse 0.5 - 1 mm
145
At 5/10,000 scales CKOW~S of trees, having a diameter of 5 m, give rise to
coarse textures, at a 20,000 scale to medium and at a 40,000 scale to fine
textures.
Structures are generally described according to both:
- size (diameter OK width) - fine 1-3 mm
- medium 3-5 mm
- coarse > 5 mm
- shape and pattern arrangement
- linear, e.g. parallel, stripy, feathery,
marbled, streaky pattern;
- non-linear, e.g. grid-, mosaic-, spongy,
speckled, dot-, cloudy, patchy pattern.
Example: Coarse patchy pattern with fine textured elements (scale 1:20,000).
Since the size of the objects, as visible on the imagery, is connected to
the image-scale, the scale has to be mentioned always! If needed for the
purpose of description and distinction between different units, the shape of
individual objects, and their arrangement in textures, may be given also. Fig.
6.1 provides a summary and illustration on textures and patterns.
The effect of scale is illustrated in Fig. 6.2. It shows a 1:33,000 scale
image, a 1:17,000 scale image, an enlargement of the 1:17,000 to a 1:10,000
scale image and an image recorded on a 1:10,000 scale. Part of the 1:33,000
image is enlarged 12 x to show graininess, resulting in a 1:2750 scale.
The image quality of Fig. 6.2b is very poor, which does not surprise the
observer due to the high enlargement factor. Also a comparison of Fig. 6.2d
with 6.2e illustrates the decreasing quality upon enlargement. However, the
quality of 6.2d is still acceptable and enlargement factors of 4 x OK 5 x are
normally considered feasible.
The series of airphotos of Fig. 6.2 clearly indicate the importance of
scale in relation to the variability of landscape. The 1:44,000 airphotos
enable only a rough division in landscape-units based on relief and drainage
pattern. The 1:13,000 airphotos present the opportunity to go into much more
detail, and land components can be delineated, based on slope, site, land-use
and tone-analysis. The 1:22,000 photos are intermediate in this respect, as
they show tone patterns, but the land components are too small to be indicated
on the map. Only land units can be distinguished at this scale. Therefore,
146
T e x t u r e s
0,2 mm
0,5 mm
o0oo c o a r s e SI 1 mm
Ar rangement o f s t r u c t u r e s
1 i n b a r e l e m e n t s
p l / pa ra1 1 e l
S i z e o f s t r u c t u r e - e l emen t s
non-1 i n e a r e l e m e n t s
lo ' '1 s k / s p e c k l e d
l o 0 1
f e / f ea t h e r y m 1 1 ' 1
0 0,000
c l / c l oudy 0
O & p 0 0 0
s y l s t r e a k y rn
f i n e
3 mm
medium
5 mm
7 mm
Exarnpl es shape o f e l e m e n t s
1 i n e a r o r e l o n g a t e d
s t r a i g h t
[ c u r v e d
b r o k e n 4
non-1 i n e a r
o c i r c u l a r
fl bean-shaped
,g e l l i p t i c a l
square
0 r e c t a n g u l a r
fi s t a r shaped
a i r r e g u l a r
F i g . 6.1 Tex tu res , p a t t e r n s and examples of shapes
147
Fig . 6.2 Airphotos of d i f f e r e n t s c a l e s of an area between Mundbrega and Maluenda, Prov. Zaragoza, Spain. ( a ) 1:44,000 (1959) ( c ) 1:22,000 (May-June 1974) ( b ) 12 x ( d ) 1: 11,000 (enlarged from ( e ) 1:13,000 (November 1980) 1:22,000)
148
landscape variability has to be evaluated in determining the proper scale for
the purpose of the study. In this case, it concerns eroded land with high
variability and consequently a large scale is necessary, if mapping of soil
series is wanted.
6 . 4 . Images derived from line-scanning devices
The line-scanning devices produce images that consist of picture elements
or pixels arranged in regular lines or columns. The pixels can be located by x
and y coordinates and the brightness of each pixel, ranging from black to
white, can be related to a grey-scale intensity value.
The aspects dealt with in the sections 6.2 and 6.3 concerning grey OK
colour-tones, size, shape and arrangement of objects are also applicable to
imagery derived from non-photographic sensors.
Some specific features of line-scanner imagery are discussed below. Landsat
images are parallelogram-shaped, due to a correction for earth rotation during
the 28 sec. required to scan the earth over the image frame area. The
multispectral scanner of Landsat has four channels sensitive for green ( 4 ) ,
red (5 ) and Near Infrared ( 6 and 7) respectively.
The spatial resolution of Landsat-imagery is determined by the 56 m by 79 m
effective ground resolution cell, the atmospheric conditions, the play-back
and reproduction of the imagery, as well as the contrast ratio of the scene.
An average for the spatial resolution is 200 m to 250 m, although much
smaller, but highly contrasting features such as highways, may be detected as
well.
In contrast to imagery derived from airborne scanning, Landsat-images show
little geometric distortion due to their narrow scan angle.
Geometric distortions in airborne scanning are inherent to the large scan
angles which are used. Since the scanner mirror rotates at a constant linear
rate, the ground resolution cells at either end of the scan line are larger
than the resolution cells in the center of the scan line directly beneath the
aircraft. However, they are recorded at an equal size as compared to the
center cells, which causes compression of the scenery at the edges of the
image. This is illustrated in fig. 6.3.
Aircraft motion distortions involve roll (rotation of the aircraft about
the longitudinal axis) and the effect of cross-winds. Both distortions can be
compensated during the flight.
149
Weather c o n d i t i o n s may have a g r e a t impact on the q u a l i t y of t h e imagery.
Th i s is e s p e c i a l l y t r u e f o r thermal imagery, where s u r f a c e winds l ead t o
smears and s t r e a k s on t h e images.
a) T e r r a i n f e a t u r e s which a r e scanned a t cons tan t angu la r r a t e .
Fig. 6 . 3 Geometric d i s t o r t i o n of
F1 i g h t d i r e c t i o n
b ) R e s u l t i n g image d i s t o r t i o n caused by r e c o r d i n g a t cons tan t l i n e a r r a t e .
scanner images a f t e r Sabins (1978).
An IRLS ( I n f r a r e d Line Scanning) image of an a r e a near Wageningen (The
Nether lands) i s g iven i n f i g . 6.4.
Fig. 6 . 4 IRLS image of an area n e a r Wageningen (The Nether lands) .
The image r e v e a l s i t s scanning n a t u r e i n showing l i n e s which a r e de r ived from
t h e image ou tpu t of a ca thode ray tube . Note a l s o t h e d i s t o r t i o n s a t t h e edges
of t h e image.
A Landsat-image of t h e Konya Basin i n Turkey i s p resen ted i n Fig. 6 . 5 .
Severa l l a k e s a r e ou t s t and ing i n t h e image a s we l l a s a mountaneous a r e a . A t
t h i s sma l l s c a l e t h e scanning l i n e s a r e c l o s e t o each o t h e r and t h e image
resembles very much a normal photograph, hu t upon enlargement t h e l i n e s w i l l
appear more and more.
F ig . 6.5 Landsat-image of band 5 ( r e d ) of t h e Konya Basin i n Turkey: s c a l e approx. 1 : 1.700 .000.
Another t ype of imagery may be c o n s t r u c t e d by u s i n g symbols f o r i n t e n s i t y
classes or other combination of digital data. An example is given in fig. 6.6.
The use of different densities in the symbols may give an impression of tone,
but the main criterion for discrimination is the symbol itself.
Fig. 6.6 Symbols as an aid for image production.
6.5 Image-enhancement
Image enhancement concerns the modification of an image to improve its
quality as pefceived by a viewer. The criterion is subjective and the
enhancement is judged by the observer.
Image restoration concerns improvement of image quality and is based on an
152
objective criterion which is mathematically defined.
Image enhancement is also performed in the interactive processing
described under section 5.2. Digital as well as optical and photographic
methods may be used.
Digital methods for image enhancement are described by H a l l (1979) . One
of the methods is the alteration of grey level values. The transformation may
be linear, logarithmic or exponential. The logarithmic transformation enhances
the low contrast detail, because logarithms provide much detail at low digital
difference.
There are also electro-optical, and photographic optical methods for
image-enhancement.
Film-density contouring may be performed by electro-optical density analyzers.
In density slicing each density measurement is portrayed separately. To
achieve density slicing, it is necessary to control the electronic equipment
in such way that all signals lower than at a selected level will be rejected
and the remainder will be printed (Boynton and Moxham, 1969). Fig. 6.7 shows
density slicing performed on an airphoto of the Calatayud area (Spain).
Fig. 6.7Density slicing on an image of the Calatayud area, Prov. Zaragoza (Spain) : (a) scene after slight modifications; (b) density slicing; the light grey levels are portrayed in black.
153
Electronic printing equipment may be used to enhance contrast in low contrast
parts of the image.
Photographic techniques for density slicing (Ranz und Schneider 1970;
Daels en Antrop, 1970) are the Agfacontouring and the Kodak-Path6 Masking. By
copying the original image on Agfacontour film, the resulting image shows only
a certain density interval transparent, the other density levels are imaged
dark (black). The transparent density interval is determined by filtering and
exposure time. Colour codes can be used for each density interval and the
resultant images can he combined.
The Masking method of Kodak-Path6 uses copies on hard photographic material.
Contrast-rich copies that depress intermediate grey tones are produced. By
varying the exposure time, it is possible to cover the whole grey scale. Such
a copy with a specific exposure time is called a mask. By copying this mask,
an antimask is the result (together they form a homogeneous black image).
Combination of a mask of a first tone level with an antimask of a second tone
level produces an image with a transparent equal density interval etc. In this
connection also the diazo process offers possibilities. By varying the
exposure time, it is possible to produce a limited range of products that
represent different tone or intensity levels of the original image.
Additive colour viewers may be used for projecting transparent
photographic materials, each illuminated with different coloured light (blue,
green and red) and arranged in accurate position by correction of the
projections. The brightness and saturation of colour (and thus the tone
levels) can be controlled. Images of different bands or dates may be combined
and the combination may be enhanced to the judgement of the interpreter.
6.6. Conclusions
Images (aerial photographs and imagery derived from digital processing)
have certain aspects jointly, which are: resolution, scale, tone, contrast,
pattern, texture, mottling and shadow.
While photographic imagery consists of very fine irregular grains, the scanner
produces so-called pixels arranged in regular lines or columns. Geometric
distortions are inherent to large scan angles as used in airborne scanning.
However, Landsat imagery is relatively free of geometric distortion due to the
narrow scan angle used in acquisition.
Thermal imagery in airborne scanning may present specific distortions due to
effects of surface winds.
154
Image restoration is based on an objective criterion. Image enhancement,
however, is subjective and intends modification of an image to improve its
quality as perceived by an observer. Image enhancement may be performed by
digital electro-optical and optical processing as well as photographic
processing.
6.7. References
Bennema, J. and Gelens, H.F., 1969. Aerial Photo-Interpretation for Soil Surveys. Lecture Notes ITC: 87 pp.
Boynton, G.R. and Moxham, R.M., 1969. A Rapid Film-Density Analyzer. U.S. Geol. Survey. Prof. Paper 650-C: pp. 123-126.
Buringh, P., 1960. The Application of Aerial Photography in Soil Surveys. Manual of Photographic Interpretation, Amer. SOC. of Photogrammetry: pp. 63 1-666.
Daels, L. en Antrop, M., 1973. Afstandswaarneming. Dee1 11: Interpretatiemoge- lijkheden. De Aardrijkskunde, Nr. 99-1973/ Nr. 4: pp. 337-353.
Hall, E.L., 1979. Computer Image Processing and Recognition. Academic Press, New York, London: 584 pp.
Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp.
Ranz, E. und Schneider, S., 1970. Der Aquidensiteitenfilm Agfacontour als Hilfsmittel bei der Photointerpretation. Bildmessung und Luftbildwesen, 38 Jg: pp. 3-14.
Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. Vol. 11, Interpretation and Applications. Amer. SOC. of Photogrammetry, Falls Church, Virginia: pp. 869-2144.
Sabins, F.F. Jr., 1978. Remote Sensing. Principles and Interpretation. W.H. Freeman and Cy, San Francisco: 426 pp.
6.8. Additional reading
Barret, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote
Carman, P.D. and Brown, H., 1970. Resolution of Four Films in a Survey Camera. Sensing. London, Chapman and Hall: 336 pp.
The Canadian Surveyor, Vol. 24, No 5: pp. 550-560.
155
7.AERIAL PHOTOGRAPHY
After Louis Daguerre announced his direct photographic process in 1839, it
took only 10 years for the first experiment on aerial photography from kites
and balloons to start. It is reported that topographic mapping using aerial
photography was introduced for the first time in North America in 1886.
The first successful1 flights with an airplane by the Wright Brothers in
1902 led in 1913 to the use of airplanes for obtaining airphotos (source: Wolf,
1974). After that time enormous progress has been made both in instruments and
techniques.
In most soil Surveys, airphotos are used as a basic material. It is
therefore of importance to have some knowledge on technical aspects.
A number of technical aspects are discussed in par. 7.1. These are general
aspects such as: vertical and oblique aerial photography, the structure of a
frame aerial mapping camera, the arrangement of a block of airphotos, drift,
crab and tilt, the shadow characteristics in the terrain and their projection
on airphotos. Stereoscopic devices, relief displacement and parallax are
treated separately in par. 7.2.
The subsequent sections contain the following subjects: aerial mapping
cameras (par. 7.3), photomosaics and othophotographs (par. 7.4), requirements
for aerial survey (par. 7.5).
Finally, some technical aspects of true colour aerial photography (par.
7.6), Infrared aerial photography (par 7.7), multispectral aerial photography
(par. 7.8) and Ultraviolet aerial photography (par. 7.9) are dealt with.
For films, filters and photographic processing, the reader is referred to
chapters 4 and 5, while image characteristics such as photo-scale, are dealt
with in chapter 6. One should be aware that the presented text gives only a
short impression of the science called photogrammetry; the references and
additional reading include some textbooks on this subject.
7.1.General aspects
Aerial photography can either be classified as vertical or oblique.
Vertical aerial photographs are taken with a camera of which the axis is
directed as nearly Vertical as possible. Oblique aerial photographs are taken
with the camera axis inclined from the vertical. High obliques include the
horizon, low obliques do not. Although obliques Offer a wide overview, they
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are in general less suitable for a systematic survey since:
- scale is only constant in lines parallel to the horizon; - atmospheric haze causes low contrast in the background (see fig. 7.1);
- in hilly terrain, slopes facing away from the camera appear in a reduced size.
Fig. 7.1 High oblique airphoto of Paramaribo (Suriname) with low contrast background (Note side friducial marks on the photograph). Courtesy: CBL Suriname.
I will restrict to the most commonly used vertical aerial photographs, which
will be referred to as airphotos.
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In practice, it is difficult to keep the camera axis perfectly vertical in
aerial photography. It concerns only small deviations of the vertical position
known as tilt (see fig. 7.5) usually amounting to less than 1" and seldom more
than 3 " . Tilt is especially difficult to avoid in (large sca1e)'photography at
a low altitude (lower than 1500 m) of hilly terrain or of areas in hot clima-
tes with irrigular thermal pattern. Under such conditions turbulent air causes
sudden movements of the airplane. Displacement in vertical position will lead
to differences in photoscale.
In terrain with great height differences, the distance of the camera to
the ground surface (flying height) is strongly variable and therefore also the
resulting photoscale.
The cameras used in aerial photography have a special construction. See
the cross-section of a frame aerial mapping camera given in fig. 7.2.
Fig. 7.2 Generalized cross-section of a frame aerial mapping camera after Wolf ( 1 9 7 4 ) .
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The main parts of a frame aerial mapping camera are: the camera-magazine,
the camera-body and the lens-cone assembly.
The camera-magazine contains the reels which hold exposed and unexposed
film and also the. film advancing and film flattening mechanism. Film
flattening is generally achieved by applying air pressure into the air-tight
camera cone. The camera body usually houses the drive mechanism for advancing
and flattening the film as well as for the operation of the shutter.
The lens-cone assembly contains lenses, filter, shutter and diaphragm.
Compound lenses bring the light rays into focus in the focal plane.
The so-called nodal points lie on the optical axis; they have the
property that any light ray directed toward the incident (or front) nodal
point passes through the emergent (or rear) nodal point and emerges at the
other side of the lens in a direction parallel to that of the incident ray
(Wolf, 1974).
The principal point, or centre, of a photograph can be defined as the
point in the focal plane where a line from the rear nodal point, which is
perpendicular to the focal plane, intersects.
The vertical airphotos are taken along a series of lines, the flight
strips. Each successive photograph along a flight strip overlaps part of the
previous photograph; the overlap normally amounts to a figure between 5 5 and
65 percent. A pair of successive photos is calles a stereopair, since
stereoscopic viewing is possible.
Information on arrangement of airphotos is summarized in fig 7.3. The
flight line is the line connecting the principal points of successive
photographs: P I , P2, P3 etc. Adjacent flight strips show a lateral
overlapping, a so-called side lap which is normally held between 10 and 30
percent. The photographs of two or more adjacent flight strips are referred to
as a block of airphotos.
The photobase is equal to the distance between principal points of
successive photographs in a flight line (see fig. 7.3). Multiplying the
photobase with the denominator of scale gives
the air base, which is the actual distance between two exposure stations.
1 2 S
(D = - = ;; see section 6.1)
2 The number of airphotos (N) covering a surface area ( A in n ) can be
calculated according to:
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run 1
~-~ _ _ _ _ - - direction of flight -
for Se see fig. 7 . 3 ; using these data
flight line 1 - -
A 2 N =
0.40 x 0.85 x 1 x D2
where Se (=gxhxD2 in m2), endlap = 60% (g = 1-e or 0,40 x l), sidelap = 15% (h
= 1-i or 0,85 x 1) and 1 = strip width. Generally one multiplies N with a
factor 1.2 in order to correct for deficits in coverage due to deviations in
the lines of flight.
run 2
flight line 2 7 - - - ' c - ------
flight 1 - -
ine 3
Fig. 7 . 3 The arrangement in a block of airphotos (straight course).
P
d
1
e i b
g n
'e
ij
principal point, intersection of diagonals (d) and lines joining opposite fiducial side marks (see fig. 7.1); diagonal of airphoto (cm) which may be related to the angular field of view ( a ) and to c = focal distance of the lens system (cm) according d = 2 c tg +a ; strip width (cm) = 4 d n ; distance between flight lines (cm); overlap in cm (in % e/l x 100); sidelap (cm) (in % i/l x 100); distance between principal points of successive photographs or photobase (cm) = 1-e; forward gain per photo (cm) = 1-e; lateral gain per photo (cm) = 1-i; gain in surface areau (cm2) per photo = b x ij = h x g.
The aircraft has to be kept at a constant altitude in a straight line on
correct course. However, the aircraft may be blown off course by wind across
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t h e l i n e of f l i g h t ( d r i f t ) or can be po in ted a t an ang le from t h e l i n e of
f l i g h t ( c r a b ) a s is i l l u s t r a t e d i n f i g . 7.4. Rol l i nvo lves a r o t a t i o n of t h e
a i r c r a f t about t h e l i n e of f l i g h t .
I f photographs are taken when t h e sun i s near t o t h e hor izon , much d e t a i l
i s obscured i n long dense shadows. Conversely when t h e sun is overhead, i t s
r e f l e c t i o n may obscure t h e d e t a i l of a p o r t i o n of t h e photograph.
North of 23"27 ' N l a t i t u d e , t h e s u n ' s r ays around noon are i n c l i n e d
toward t h e e a r t h from t h e sou th , sou th of 2 3 " 2 7 ' S l a t i t u d e they a r e i n c l i n e d
from t h e no r th . Between these l a t i t u d e s near t h e equa to r , t h e sun ' s r a y s
around noon a r e d i r e c t e d n e a r l y v e r t i c a l toward t h e e a r t h ' s su r f ace .
s t r a i g h t course
crab
Fig. 7.4 F l i g h t coverage showing s t r a i g h t cour se , d r i f t and crab .
A t any p l ace on t h e e a r t h ' s s u r f a c e , t h e sun ' s r a y s are from t h e east
p r i o r t o noon and from t h e w e s t a f t e r t h a t t i m e . Thus i t is p o s s i b l e t o
p r e d i c t t h e shadow p a t t e r n when t i m e and p l a c e are s p e c i f i e d .
I f t h e a n g l e wi th t h e v e r t i c a l ( z e n i t h ) of t h e sun's r ays is s m a l l e r t han
( f angu la r f i e l d of view) of t h e camera, t h e image of t h e sun may be seen fa
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on the photograph, the so-called solar reflection point. This situation occurs
throughout the year around noon in tropical areas and during summer in
temperate regions also around noon, especially with cameras having a large
angular field of view. However, the solar reflection point can be detected in
the scene only if highly reflecting surfaces are present.
The point just opposite the solar reflection point does not show shadow,
since no rays behind that area can reach the camera (see fig. 7.5: point T
opposite S, the solar reflection point). The sun and the aircraft are exactly
in line at this point. Therefore at low-altitude flights, the shadow of the
aircraft may be registered at this place. The point is known as the no-shadow
point or hot spot.
Fig. 7.5 shows the shadow characteristics of the terrain. Note the effect
of slope in shortening the shadow when projected on a slope facing toward the
\ ,, ,,, , , ,’ p h o t o negative T N
\ \\ I l l I I /
perspective center
\ // / I I l l \ \ \ \
Fig. 7.5 Tilt and shadow characteristics on an airphoto P = principal point S = solar reflection point N = Nadir T = no-shadow point or hot spot
incident radiation and the reverse effect if slope is facing away from the
incident radiation. The shadows are projected as lines in the one-dimensional
presentation of the photo-negative in fig. 7 . 5 .
The so-called Nadir-point (N), that is the point on the photograph where
a vertical line (from the reference plane) through the perspective centre ( 0 )
of the cameralens pierces the plane of the photograph, is exactly halfway
between the solar reflection point (S) and the no-shadow point (T). The
distance and direction of N from the principal point may be used as a measure
for the amount and direction of tilt.
Below we consider the aspects of photographic printing materials.
Positive prints can be made transparent or printed on paper. Diapositives made
on glass show the least dimensional change and sharpest detail. A l s o positive
transparencies on film base are superior to paper prints. However, for use in
the field, paper prints are preferred, since they have advantages with regard
to handling, writing and drawing when compared with the other materials.
Furthermore, expenses for replacements are relatively low.
The weight and surface of paper prints vary. One can distinguish:
- single weight and double weight, - glossy, semi-matte and matte paper prints.
Double weight paper is stiffer, more durable and less subject to dimensional
change caused by varying humudity and temperature than single weight paper.
Glossy prints are the sharpest type but reflect glare and may crack under
intense use. A compromise between sharpness and durability in the field forms
the semi-matte double weight paper.
The format of airphotos is usually 23 x 23 cm; earlier, 18 x 18 cm was
used. However, other formats, like the 6 x 6 cm, acquired by specific cameras,
may be found as well.
7 . 2 . Stereoscopy
In section 4.1 the cues to depth for human vision have been discussed.
Fusion of double images enables depth perception. The aerial camera produces
two images of the same scene (stereopairs) by successive exposure in the
flight line.
Optical devices are used for viewing stereopairs: lens (or pocket)
stereoscopes, mirror stereoscopes (see fig. 7 . 6 ) and stereoscopic glasses.
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Fig. 7 . 6 Stereoscopes ( a ) Zeiss pocket s t e r eoscope (b ) Case l l a pocket s t e r eoscope ( c ) Topcon mi r ro r s t e reoscope (d ) Wild mi r ro r s t e reoscope ( e ) Old De l f t scanning s t e reoscope
The most s imple s t e r e o s c o p i c dev ices a r e probably s t e r e o s c o p i c g l a s s e s .
T h e i r l i m i t e d use w i l l be due t o t h e d i f f i c u l t y f o r t h e observer t o ma in ta in
the d i s t a n c e between eyes and o b j e c t approximate ly equal t o the f o c a l d h t a n c e
of t h e l enses .
In t h e l e n s s t e reoscopes ( f i g . 7 . 6 a and b ) , a magnifying l e n s i s p laced
i n f r o n t of each eye , and the photographs a r e viewed a t a d i s t a n c e equa l t o ,
o r s l i g h t l y less (e .g . 8.9 cm) than t h e f o c a l l eng th of t h e l e n s (e.g. 11.4
cm). The r e s u l t i s t h a t t h e o b j e c t s a r e a t o r near o p t i c a l i n f i n i t y from t h e
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eyes and the line of sight of the eyes will be parallel or nearly parallel.
Lens stereocopes are inexpensive and easy manageable. A disadvantage is
that the entire overlap of standard airphotos cannot be viewed at one time.
The lens steroscope presented in fig. 7.6 a, differs from that in fig. 7.6 b,
in not having an adjustable eye base.
In mirror stereoscopes, the lines of sight of the eyes are separated by
means of reflecting surfaces, two for each eye (fig. 7.6 c/e). The entire
stereoscopic overlap of standard airphotos can be viewed at one time. To
obtain magnification, binocular viewers (Topcon 3x or 6x) or built-in
magnifiers (Topcon 1,8x) can be used.
The Old Delft scanning stereoscope (fig. 7.6e) enables to move the field
of view either horizontally or vertically by knobs which operate rotating
mirrors and prisms in the instrument. Two magnifications 1.5 and 4.5 are
available and one views from an oblique angle. Through application of two Old
Delft scanning stereoscopes placed across from one another, it is possible to
view the same photographs with two persons simultaneously.
The first step in the orientation of photographs is to nark the principal
points and locate the principal points on adjoining photographs, the so-called
conjugate principal points. The line joining the principal and conjugate
principal points is the flight-line. The flight-line should be parallel to the
instrument base and the line connecting the eyes of the observer.
Furthermore, the photographs should always be oriented in such a way that
the shadows fall as nearly as possible to the observer. Since the overlap area
should be in the center, it will be apparent which is the right-hand print and
which is the left. After adjustment of the interocular distance (e.g. 64 mm),
the two photographs are located apart, parallel to the flight-line to the
correct position for the possible stereoscopic vision.
Relief displacement is the displacement in photographic position of an
object due to its elevation above, or its depth below a reference level. The
displacement is outward from the photocenter for points above the reference
plane and inward for points below the reference plane. Near the nadir there is
less displacement. The concept of relief displacement is illustrated in fig.
7.7.
The projection through an optical center, the so-called perspective
projection, involves a number of phenomena. When an object is in nadir, it is
projected orthogonal (e.g. in photo 1). Out of n a d i r ( a s in photo 2 for AR) it
165
I I I I I I ,
G1 F1 A1=B1
A r = N 1 A2
C I D E ' B ' N1 A '
t n e g a t i v e \ \ \ N , / I
I , #
r = N 1 N2
Fig. 7 . 7 Relief displacement
is projected as a line. Point A above the reference plane is projected as
outward from N l t l and B below the reference plane is projected as B2' inward
from N l l ' (see also the projection of CDE). If A was located higher above the
reference plane, it would be projected more outward etc. The relief
displacement Ar (in mm) can be calculated (see Fig.'7.7), since:
Another aspect connected with perspective projection is that of slope
direction; slopes that are facing toward the optical center are imaged larger
than slopes facing away from the optical center (compare B,'F,' with F,IG,I).
Parallax is the displacement in the position of an object caused by a
shift in the position of image acquisition. The change in position of a point
166
from one airphoto. to the next airphoto in a flight-line is called the
stereoscopic parallax. Every point on successive airphotos has an absolute
stereoscopic parallax (see fig. 7.8).
Fig. 7.8 Parallax and parallax-difference
Absolute stereoscopic parallax of A and B (in nun):
P = X -(-X ) a n d P = X - X A A1 A2 B1 B2
Parallax difference (in nun) AP = P - P = A A - B B AB A R 1 2 1 2
From the parallax difference between two points ( AP in nun, fig. 7.8),
as measured on a stereopair in proper position, the height difference (h in m)
between the points can be calculated as follows:
AP (7-3) h =-
b + A P . ' where b = photobase o r distance between principal points or two successive
photographs in mm and Z = flying-height in m.
The measurements are done with a so-called parallax bar.
The stereoscopic effect may be roughly expressed by the base/height
ratio. If in normal viewing the base is 6.4 cm (eye base), the ratio amounts
to 0.2 at a distance of 30 cm and to 0.00064 at 100 m distance.
In aerial photography the base is the air base (photobase b, multiplied
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by denominator of scale D). For an air base of 2300 m and a height of 3800 m
( a = 9 0 ° , f = 152 mn, format 23 x 23 cm, scale 1 : 2 5 . 0 0 0 ) , the base height
ratio (B/Z) is equal to 0.6; there is vertical exaggeration, when compared to
normal vision. In stereoscopic viewing of a stereopair of airphotos, the
vertical exaggeration can be calculated by multiplying the base/height ratio
with Q/E where Q = distance from the eyes to the stereomodel in cm, and E = eye
base in cm. An average value for Q = 43.2 cm and Q/E is approximately 6.8.
In stereoscopic viewing an approximation of the vertical exaggeration (V)
therefore can be given by the following expression:
B Z V = - x 6.8 ( 7 - 4 )
7 .3 . Aerial mapping cameras
The most common aerial mapping camera is the single lens frame camera, OK
frame aerial mapping camera.
The single lens frame cameras are normally classified according to their
angular field of view into:
- normal angle, up to 7 5 " , often 60" e.g. Wild RC8 Aviotar and Topar (Zeiss, W.
Germany) ;
- wide angle, 75" - loo", often 90' e.g. Wild RC8 Aviogon and Geocon IV (Bajer,
U. S .A.) ;
- super-wide angle, greater than I O O ' , often 120" e.g. Wild RC9 Super Aviogon
and Russar (Russipov, U.S.S.R.).
The focal length (c in cm), the angular field of view ( a ) and the photoformat
(d = diagonal length in cm) are related according to (see fig. 7 . 9 ) :
fd fd tg fa = -OK a = 2 arctg - ( 7 - 5 )
The focal length is related to the flying altitude (Z) as SScale = c/Z; (6-1).
The relation between angular field of view ( a ), focal length (c) and flying
altitude (2) is illustrated in fig. 7.9. A smaller angular field of view
involves a longer focal length and higher flying altitude to obtain the same
photo-scale.
The vertical exaggeration (V) can be expressed in b and c, using equations 6-1
and 7-4. Since B = hxD (where B = air base, b = photobase and D = denominator
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4
A
l c
Fig. 7.9 Relation between angular field of view ( a ), focal length (c) and flying altitude (2 ) .
1 c of scale) and Z = cxD (for S = 6 = 2 ) the equation 7-4 can be written as
follows :
b V = - x 6.8 (7-6)
In table 7.1 the vertical exaggeration for different camera types is given.
Table 7.1 Vertical exaggeration for different camera types and b = 92 mm (photoformat 23 x 23 cm and 60% overlap)
Camera type a c (mm) V
normal angle 60" 300 2.0 wide angle 90" 152 4.0 super wide angle 120" 88 7.1
In table 7.2 the height difference h is given for parallax differences A p of
respectively 0.02 mm, 2 mm and 5 mm (photoformat 23 x 23 cm, overlap 60%).
Apparent is the influence of the angular field a on the height difference at
specified Ap . Besides these cameras, so-called narrow angle cameras may be used for
large-scale photography to reach permissible flying heights.
169
Table 7.2.The he igh t d i f f e r e n c e s f o r d i f f e r e n t s c a l e s and camera types f o r photoformat 23 x 23 c m , ove r l ap 60% and p a r a l l a x d i f f e r e n c e s of 0.02 mm, 2 mm and 5 nun.
camera type a c Z S h a t h a t h a t (mm) (m) Ap= Ap=2mm A~=5mm
normal ang le 60" 305 3050 1:lO.OOO 0.6 in 63 m 150 m 15250 i:5n.nno 3.3 m 318 m 748 m
wide ang le 90' 152 1520 1:10.000 0.3 m 32 m 75 m 7600 1:50.000 1.6 m 158 m 373 m
supe r wide ang le 120' 88 880 1:lO.OOO 0.2 m 18 m 43 m 4400 1:50.000 1.0 m 92 m 216 m
Super-wide ang le cameras may be a p p l i e d f o r s p e c i a l purpose f l i g h t s below
c loud cover.
A n e a r l y complete series of cameras is provided by Ze i s s ( f o r t h e
s t anda rd nega t ive s i z e of 23 x 23 cm), a l s o inc lud ing a so-ca l led in t e rmed ia t e
a n g l e camera ( t a b l e 7.3).
Table 7.3. Ze i s s aer ia l survey cameras.
Type Lens c i n nun angu la r f i e l d a
Narrow ang le camera Tel ikon A 610 30" Normal ang le camera Topar A 30 5 56"
camera
Super-wide ang le S-Pleogon A 85 125"
In t e rmed ia t e ang le Toparon A 210 75"
Wide ang le camera Pleogon A 153 93'
Knowledge of f i l m speed is e s s e n t i a l f o r de te rmining t h e proper exposure
times dur ing t h e f l i g h t , bu t a l s o o t h e r f a c t o r s are impor tan t . For t h i s
r eason , Kodak developed an Aerial Exposure Computer enab l ing t h e e s t i m a t i o n of
l e n s opening and s h u t t e r speed i n r e l a t i o n t o f i l m speed, d a t a , t i m e of day,
a l t i t u d e of f l i g h t , l a t i t u d e and haze c o n d i t i o n (Smith, 1968).
The speed of non-ae r i a l f i l m s is measured i n DIN (Deutsche I n d u s t r i e
Norm) o r ASA (American Standard Assoc ia t ion ) e.g. ASA = 200 means: an exposure
t i m e of 1/200 sec a t a p e r t u r e f / 1 6 (Wolf, 1974).
However, f o r panchromatic aer ia l f i l m s , u s u a l l y t h e so-ca l led aerial f i l m
speed (AFS) is used , which is equa l t o :
AFS = Eo
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where Eo is the exposure (in m cd s-l) at the point on the characteristic
curve (see fig. 5.1) where the density is 0.3 above Dmin under specified
processing conditions (Lillesand and Kiefer, 1979).
Total exposure of photographic film is the product of illuminance and
time of exposure. Illuminance is regulated by variations in the diameter of
the diaphragm (d= opening of the lens or aperture) and may be expressed by the
f-stop according:
f-stop = (7-7) d
The lens types of table 7.3 each have their f-stop setting at specified
film speed and image distortion characteristics.
Other single-lens frame cameras may be used such as the small-sized
Hasselblad with a photoformat of 6 x 6 cm. These cameras may be applied with
focal lengths of 45 and 49 nun (wide angular field), or 70 m (narrow angular
field). The 70 mm type permits photography from small planes at low altitudes.
When compared with wide and super-wide angle aerial mapping cameras, which are
normally used at l o w altitudes, they may have a relatively narrow angular
field and in consequence only slight edge distortion.
In addition to the single-lens frame cameras which are normally used,
there are a number of other camera types. Some of these are discussed below.
Multilens cameras have two or more lenses and expose two OK more pictures
simultaneously.
The so-called trimetrogon camera has a three camera system. Two cameras
expose high oblique photos, while a third camera simultaneously takes a
vertical photo. Covergent cameras consist of two single lens cameras mounted
together, one pointing forward and the other pointing backward in the flight
line. In this way two low oblique photos with great overlap can be taken of
ground scenery. Multilens and multicamera systems may be applied for
multispectral photography through the use of different filters and with
respect to the latter also by using different film types.
The so-called strip cameras expose a continuous photograph of a strip of
terrain below the path of the aircraft. This is accomplished by passing the
film over a narrow slit opening in the focal plane at a rate just equal to the
speed of passage of ground images across the focal plane (Wolf, 1974).
Panoramic cameras take pictures of strips of terrain transverse to the
171
direction of flight. The camera scans laterally from one side of the flight
path to the other. The lateral scan may be as great as 180" enabling
photography from horizon to horizon. The scanning also makes it possible to
obtain a stereoscopic overlap area. The features inherent to panoramic
photography are indicated in fig. 7.10. The distortions are connected with the
large scan angles and the velocities of scanning and the aeroplane itself.
t e r r a
image
( c ) t f l i g h t path
/I
scan no 1
s tereoscopic overlap area
f l i g h t path /
Fig. 7.10 Schematic representation of panoramic photography. (a) field of view in flight path (b) lateral scan (c) panoramic distortion and scan distortion (d) stereoscopic overlap two scans
172
7.4. Photomosaics, orthophotographs and stereotriplets
Aerial photomosaics are assemblages of overlapping airphotos. Most
commonly, they are constructed from vertical airphotos by cutting and matching
the individual parts of the photographs.
Aerial photomosaics may be: controlled, semi-controlled or uncontrolled. A
controlled mosaic is prepared from photographs which have been rectified for
effects of tilt and flying-height variations, and brought to uniform scale by
using control points. An uncontrolled mosaic is prepared by simply matching the
adjacent photos; no rectification or control points are used. Semi-controlled
mosaics are prepared by using control points but without rectification or
otherwise, and without a complete control.
Furthermore, we know index mosaics or photo indexes, and strip mosaics for
engineering projects e.g. in road and railroad construction. Controlled mosaics
are valuable in soil survey projects in that they provide a broad view of the
landscape and enable an accurate plotting of survey and sample points.
Othophotographs are made by removing the effects of tilt and local relief
(height or depth below a reference level) as well as many of the lens
aberrations from standard perspective airphotos. The process of preparation of
orthophotographs is usually referred to as differential rectification. ,For
stereoscopic interpretation of orthophotographs a special photographic image
has to be used, a so-called stereomate. The stereomate is a differentially
rectified photograph, on which image shifts have been introduced in the x-
direction proportional to the elevation differences in the terrain and parallel
to the base of the original stereoscopic model.
For more information on orthophotography, the reader is referred to Slama
(ed., 1980).
Stereotriplets are produced by cutting successive airphotos of a strip and
arranging the pieces in such a way that the central area can be viewed
stereoscopically. This is shown in fig. 7.11. The part at the right on photo 1
and the part at the left on photo 3, both containing P2', together with the
central part of photo 2 are used for the production of a stereotriplet.
For use with a pocket stereoscope, the three parts can be fixed, so that the
distance of equivalent points on successive imagery amounts to 6.4 cm.
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photo 1 photo 2 photo 3
n n n n I I 1 I
- - f l i g h t l i n e
Fig. 7.11 Production of stereotriplets. n = normal to flight-line from centre P, P2', P1', P2 etc.
7.5. Requirements for aerial survey
The data which have to be recorded on each photograph are:
- the photonumber and line of flight; - fiducial marks; - acquisition data and time of day; - flying altitude; - focal length OK scale;
- position related to horizontal (water-level mark).
Other indications may be:
- the organization which carried out the aerial survey; - grey scale for control on development.
The decision to fly OK not to fly must be made daily. A n ideal day for
aerial photography is one free of clouds and atmospheric haze. A day with less
than 10 percent cloud-cover, however, may be found satisfactory. Other factors
that have to be considered are: smog, dust, smoke, high winds and air
turbulence (Wolf, 1974).
The season determines the vegetation cover of the ground and the sun's
altitude. For topographic mapping and soil mapping in the temperate zone, the
photographs should preferably be taken when deciduous trees are bare. For
vegetation studies and forestry on the other hand, it is desirable to take
photographs when the deciduous trees are in full leaf and show much contrast,
e.g. during spring or autumn.
For detection of differences in soil moisture content in semi-arid
regions, the period directly after the rainy season may be chosen for the
aerial survey.
174
The sun's altitude in connection with shadow is an other important
factor. Normally about 30" sun angle is considered the minimum acceptable in
aerial photography. For the temperate zone this means that the airphotos
should be taken in summer, around noon (10.00 a.m. - 14.00 p.m.).
Howgver, in aequatorial zones the high sun's altitude around noon is
normally avoided and airphotos are taken between R.00 a.m. and 10.00 a.m. OK
between 14.00 p.m. and 16.00 p.m.
In selecting the direction of flight-lines, one has to evaluate the
following:
- the physiography of the terrain; generally the flight-lines are chosen
perpendicular to the main physiographic boundaries but great differences in
topography are avoided;
- the position of the sun; generally the flight-lines are roughly in east-
west direction in temperate zones and in north-south direction in
equatorial areas to obtain shadows perpendicular to the flight lines (if
time of day of aerial survey is such as indicated above).
Of course, it may be necessary to find a compromise between physiography
and shadow-effect in the selection of flight-lines.
The scale of aerial photography depends of the purpose of the study and
the geographic dimensions of the landscape units. The dimensions of the basic
mapping unit have to be specified beforehand.
Examples of purpose of study and usual airphoto scales are given below:
Livestock, crop-disease 1 : 2,000 and larger scales
Tree crowns, vegetation damage in forests 1: 5,000 to 1:3,000
Dynamical phenomena of erosion processes 1: 5,000 and larger scales
Farm crop fields, urban details 1 : 10,000
Topographical mapping 1:33,000, 1:25,000 and
1 : 17,000
Reconnaissance survey 1 : 80,000
Photographic imagery may be enlarged as much as 4 or 5 times the origial
format t o a scale suitable for the purpose of study.
7 . 6 . True colour aerial photography
True colour-films may be distinguished in:
175
- direct colour positive films or reversal films
- colour negative films.
Colour negative films offer advantages over reversal films in having a
greater exposure latitude and more control in obtaining the desired colour
balance during printing. In addition, a number of second-generation products
can be easily obtained (Myers, 1 9 6 8 ) .
Colour-films have a slightly lower resolution than black-and-white films.
The reversal film, however, has a relatively high resolving power, since there
is no necessity to produce any prints, which would cause a loss of resolution;
laboratory work and expenses are greatly reduced (Vijlger, 1957) and the film
is therefore more regularly applied in aerial survey.
The resolving power of multi-layer colour-film is not uniform for the
three basic colours. AGFA established the following values for their CN 17
film in the laboratory (VSlger, 1 9 5 7 ) :
- top layer (blue-sensitive) 100 lines/mm
- centre layer (green-sensitive) 70 lines/mm
- bottom layer (red-sensitive) 50 lines/mm
A number of colour-films for aerial survey are on the market.
In the U.S.A.: Eastman Kodak Company with the reversal Ektachrome Aerofilm,
the negative Ektachrome Aerofilm 8442 and the AeKOCOlOUK Film 2445 (Estar
base); General Analine and Film Corporation with positive Anscochrome film.
In Germany: Agfacolour negative film.
In the U.S.S.R.: the three layer colour film, TsN-1.
The external parameters that are of much importance in colour photography are:
the sun's angle, the time of day, the atmospheric condition, the flying
altitude and the angular field of view of the camera.
The reflected light on its way from target to sensor is changed in
composition, due to adsorption by atmospheric constituents and addition of
diffuse light. On clear days, the latter has a higher content of blue as
compared to direct sunlight. Consequently, in oblique photography the horizon
appears bluish (Rayleigh scattering). Under haze conditions also light of
longer wavelengths is scattered and the horizon becomes whitish (Mie
scattering).
Therefore, the edges of aerial COlOUK photographs generally show a loss in
colour fidelity as compared to the central part of the photograph.
Since an increasing flying-altitude normally results in a greater
176
contamination of blue light, the best quality of aerial colour photography is
reached at relatively low flying-altitudes. Meier ( 1 9 6 7 ) reports about colour
photography of good quality of an area in Germany from a height of 2000 m, and
of poor quality from a height of 4000 m. Furthermore, a small angular field of
view will minimize the edge effect.
Filters are used for acquisition of good imagery, e.g. antivignetting
filters for uniform exposure of the image-plane and filters excluding
radiation with wavelengths smaller than 380 nm, 400 nm or 420 nm for
compensation of light, medium and heavy haze respectively (Smith ed., 1 9 6 8 ) .
7 .7. Infrared aerial photography
The two common Infrared sensitive films are the black-and-white Infrared
film and the three-layer colour Infrared or false colour-film (see section
4 . 2 ) . Also the Russian spectrazonal film (SN-2M) must be mentioned. The latter
is a two-layer film. the layers being sensitive for green-yellow-orange, and
for near Infrared radiation.
Outstanding advantages of the near Infrared sensitive films are the
additional information obtainable from the near Infrared and the relatively
high haze penetrating capability. Under thin fog conditions, IR photography
penetrates slightly further than normal photography. Under dense fog
conditions there is no benefit.
Storage of the films requires care: they have to be stored at
temperatures of -23°C to -18°C.
Several Infrared sensitive films are on the market. In the U.S.A., bdak
produces the Ektachrome Infrared Aerofilm type 8443 and the Aerochrome
Infrared film 2443 (Estar base) and 3443 (Estar Thin Base). In the U.S.S.R.,
also black-and-white Infrared film is available besides the spectrazonal film.
Since near Infrared rays (700 -900 nm) are less refracted than Visible
rays, the focusing of near Infrared rays has to be corrected. For black-and-
white Infrared photography this is relatively simple, but for the three-layer
false colour photography, special glasses, o r Crystalline calciumfluoride and
sometimes plastic material, are used for focus correction at three
wavelengths. Such lens-systems are called apochromatic lenses (Gibson, 1 9 7 8 ) .
Pease ( 1 9 7 0 ) has paid attention to processing of False COlOUK reversal
film. By a simple modification of processing, negative material can be
produced. The paper prints derived from this negative material show more
subtle differentiation than prints that have been made from positive
177
transparencies (for routine processing, the reader is referred to the sections
4.2, 5.1 and to Smith, 1968).
Another modification in processing may be used to improve the haze
penetrating capability. Atmospheric haze results in a scattering of green and
red, and consequently produces a blue-green veil on the false colour film. By
the so-called EA-4 processing the cyan layer sensitivity can be increased in
order to obtain a near neutral balance. High altitude Colour Infrared
photography is improved in this way, and at the same time objects with a low
near Infrared reflectance, such as most rocks and soils, can be discriminated
better.
7.8. Multispectral aerial photography
The disadvantage of direct true colour aerial photography according to
Yost and Wenderoth (1967) are:
- fixed spectral sensivity;
- fixed relative exposure for each dye layer;
- inadequate exposure range;
- complexity of processing as compared with processing of black and white
photography,
- lack of true colour fidelity and inability to produce significant colour
differences between objects which have slight spectral reflectance
differences.
Research has been done to evaluate the possibilities of multispectral
photography in obtaining true colours of terrain features and in enhancement
of the imaging of objects, which have only slight spectral reflectance
differences.
The following requirements for multispectral photography can be indicated
(Yost and Wenderoth, 1967) :
- the spectral bands should be correctly chosen after measurement of the
spectral distribution of the illumination and the spectral reflectance of
the targets;
- the camera system has t o be spectrophotometrically calibrated;
- the photographic processing has to be controlled.
By controlled exposure in each spectral band, the multispectral camera
can compensate for the dynamic variables: illumination and atmospheric
178
condition. Furthermore, by controlled processing and additive COlOUK
projection, it is possible to obtain true colours of ground objects or to show
slight spectral differences between objects.
Stellingwerf (1968) and other authors report about the advantages of the
relatively small 70 nun cameras (e.g. Hasselblad). Four of these 70 mm cameras
can be mounted, to one frame aerial mapping camera. The recording of the four
images may be done on one piece of film OK on separate films. When recorded on
one piece of film, it is possible to study the images on the 1-011 with a
pocket stereoscope. However, controlled processing of negatives for each
spectral band is only possible when recorded on separate films.
7.9. Ultraviolet aerial photography
The incoming radiation at wavelengths shorter than 0.28 m is strongly absorbed by ozone and molecular oxygen in the atmosphere, thus limiting the
part of the ultraviolet region that is of practical interest to remote
sensing.
Some quartz glasses, quartz crystal, the salts lithium fluoride and
barium fluoride, are transparant for wavelengths as short as 0.12 lnn but for
wavelengths larger than 0.28 um conventional lenses are quite satisfactory
(Cronin et.al., 1973). If extremes of altitude and unfavourable atmospheric
conditions are avoided, Ultraviolet aerial photographs can be taken, although
image contrast will be low due to strong scattering of UV by atmospheric
particles.
The Kodak P l u s - X Aerographic film 2402 in combination with the IJratten
18A filter may be used for this purpose.
7.10. Conclusions
One of the technical aspects in aerial photography is the position of the
camera axis enabling a first classification of airphotos in oblique and
vertical photos. The latter have a more uniform photo-scale and are normally
used in soil surveys.
Deviations of the vertical (tilt) are avoided as much as possible in
taking vertical airphotos. The photographs are taken in flight-lines and
overlapping position in forward as well as in sideward direction. Deviations
from the flight line direction are a.0. crab and drift..
If the angle of the sun's rays with the vertical is smaller than 4 of the angular field of view of the camera, a no-shadow point OK hot spot can be
179
indicated as well as a solar reflection point, the latter if strongly
reflecting surfaces are present.
Concerning the type of paper prints: a double weight semi-matte paper
print is selected for heavy field use of airphotos, which is usual in soil
survey. Photomosaics are very useful in soil survey projects.
The requirements of aerial survey have to be formulated in the light of
soil survey and other applications as well as the technical aspects involved.
Some technical aspects of modern aerial photography are: resolution power
of multi-layer colour film, the influence of atmospheric condition and flying
altitude on colour rendition.
Infrared aerial photography has a better penetrating capability when
compared with colour aerial photography. Modification in processing of
Infrared false colour photographs may improve the haze penetrating capablility
and the discrimination between objects with low near Infrared reflectance.
Multispectral photography may be applied to obtain true colours of
terrain features and to produce significant colour differences between objects
with slight spectral reflectance differences. Controlled processing is one of
the requirements.
Ultraviolet photographs may be obtained from a low altitude at favourable
atmospheric conditions with Kodak Plus-X Aerographic film 2402.
7.11. References
Avery, T.E., 1962. Interpretation of Aerial Photographs. Burgess Publ. Cy, Mineapolis: 192 pp.
Cronin, J.F., ROoney, T.P. et al., 1973. Ultraviolet Radiation and the Terrestrial Surface. In the Surveillant Science ed. by Holz, R.K., Houghton Mifflin Cy, Boston: pp. 67-77.
Gibson, H.L., 1978. Photography by Infrared. Its Principles and Applications. John Wiley & Sons, New York: 545 pp.
Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpretation. John Wiley & Sons, New York: 612 pp.
Meier, H . K . , 1967. Farbtreue Luftbilder? Herbert Wichman Verlag, Karlsruhe, Bildmessung und Lufbildwesen, Heft 5/67: pp. 206-214.
Myers, V.I. and Allen, W.A., 1968. Electro-optical Remote Sensing Methods as Nondestructive Testing and Measuring Techniques in Agriculture. Applied Optics Vol. 7, NO 9: pp. 1819-1838.
Pease, R.W., 1970. More Information Relating to the High-Altitude Use of Color Infrared Film. Amer. Elsevier Publ. Cy, Remote Sensing of Environment Vol. 1, nr 2: pp. 123-125.
Pease, R.W., 1970. Color Infrared Film as a Negative Material. her. Elsevier Publ. Cy, Remote Sensing of Environment, Vol. 1, nr 2: pp. 195-198.
Slama, C.C. (ed), 1980. Manual of Photogrammetry; 4th edition. Amer. SOC. of Photogrammetry, Falls Church, Virginia: 1056 pp.
180
Thompson, M.M. (ed), 1966. Manual of Photogrammetry; 3rd edition. Amer. SOC. of Photogrammetry. Vol I and 11. George Banta Co, Menasha, Wisconsin: 1199 pp.
Vijlger, K. 1957. Neue Versuche mit farbigen Luftaufnahmen. Herbert Wichman Verlag GmbH, Berlin, Bildmessung und Luftbildwesen, Heft 4: pp. 112- 116.
Wolf, P.R. 1974. Eleme,nts of Photogrammetry, McGraw-Hill Book Cy, New York: 562 pp.
Yost, P.R. and Wenderoth, S., 1967. Multispectral Color Aerial Photography. Photogrammetric Engineering, Sept. 1967: pp. 1020-1033.
7.12. Additional reading
Albertz, J. and Krieling, W., 1972. Photogrammatric Guide. Herbert Wichman Verlag, Karlsruhe: 214 pp.
Aldrich, R.C. Heller, R.C., 1969. Large-scale Color Photography Reflects Changes in a Forest Community During a Spruce Budworm Epidemic. Remote Sensing in Ecology. Univ. of Georgia Press, Athens: pp. 30-45.
Breuck. W. de en Daels, L., 1967. Luchtfoto's en hun Toepassingen. Wetenschappelijke Uitgeverij. E. Story-Scientia, P.V.B.A. Gent: 176 pp.
Corten, F.L., 1966. Physik des Luftbildes in "richtigen" und "falschen" Farben. Bildmessung und Luftbildwesen Bul. 4/1966: pp. 191-201.
Fritz, N.L., 1967. Optimum Methods for Using Infrared Sensitive Color Films. Photogrammetric Engineering 33: pp. 1128-1138.
Howard, J.A. 1970. Aerial Photo-Ecology. Faber and Faber, London: 325 pp. Interdepartmental Committee on Air Surveys, 1970. Specifications for Air
Schuurmans, U.D., 1979. Infraroodfotografie. Focus-10: pp. 50-53. Smith, J.T. (ed), 1968. Manual of Color Aerial Photography. Amer. SOC. of
Photogrammetry, Falls Church, Virginia: 550 pp. Spurr, S.H., 1960. Photogrammetry and Photo-interpretation. The Ronald Press
Cy, New York: 472 pp. Stellingwerf, D.A., 1968. The usefulness of Kodak Ektachrome Infrared Aero
Film for Forestry Purposes. 11th Congr. of the Int. SOC. for Photogrammetry, Lausanne 1968: 6 pp.
Trorey, L.G., 1950. Handbook of Aerial Mapping and Photogrammetry. Cambridge, University Press: 178 pp.
White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press, Oxford: 104 pp.
Williams, J.C.C., 1969. Simple Photogrammetry. Academic Press, London and New York: 211 pp.
Survey Photography. National Research Council of Canada: 32 pp.
181
8. GENERAL DIRECTIONS FOR PHYSIOGRAPHIC INTERPRETATION OF REMOTE SENSING
IMAGERY IN SOIL MAPPING.
Soils are defined as three-dimensional natural bodies with a unique morphology.
They can be studied in the field by auger, trenches and profile pits. The field
survey may be done according to the fixed grid method, the sample line and,
strip methods or the spot and sample area methods. The fixed grid method is
used in detailed OK semi-detailed surveys. Especially small scale surveys
require interpolation and even extrapolation, thus making the use of remote
sensing tools inevitable.
Present remote sensing techniques normally operate from the Visible up to
the Microwave zone (radar). In case of bare surfaces reflectance data offer
direct information about the soil surface. Where surfaces are covered by
natural vegetation OK crops, texture, pattern and tone of vegetation together
with slope and site are the main sources of information. The basic requirement
for image-interpretation in Soil mapping therefore, is to indicate a number of
different aspects which individually, or in combination with other aspects have
a correlation with soil conditions. The areas thus indicated are supposed to
show uniformity in their soil distribution pattern and are delineated on the
images in order t o show the geographical extension of soil bodies (polypedons).
To a certain extent, information on subsurface conditions can be
interpreted from thermal and long wave radar data. Furthermore, the
morphographic position or site may offer strong indications about subsurface
conditions. However, all these deductions mainly have a function in the
planning of the field survey. In other words, the assumptions have to be
verified.
Below, interpretation is discussed with emphasis on methods offering
information about superficial aspects only, and providing steroscopy.
A number of authors present the outcome of their work on airphoto-interpre-
tation. In a general way the methods described by these authors are also
applicable to the interpretation of other remote sensing imagery. For details
on airphoto-interpretation see a.0. Buringh ( 1960), Vink ( 1964), Goosen (1967)
and Bennema and Gelens (1969). The different remote sensing techniques used in
identifying terrain features are treated in chapters 9 through 13.
182
8.1. Methods of image-interpretation
Image-interpretation may be done for many purposes each with its
specified interest in the objects or the features on the imagery. The kind of
objects or features on which a particular analysis is based, is called an
aspect.
The aspects of interest for soil survey can he divided (Bennema and Gelens,
1969) into:
- basic aspects individually visible on the images, e.g. slope and relief (if
stereoscopic observation can be applied), natural vegetation, crops, soil
and rock surface (grey or colour tones);
- compound aspects visible on the images through a combination of two or more of the basic aspects e.g. land types, drainage ways and pattern, faults and
joints,
- inferred aspects not directly visible on the images hut deduced from basic and/or compound aspects e.g. soil depth, parent material, drainage and
erosion condition.
Bennema and Gelens (1969) indicate three relationships between the aspects of
image-interpretation and soil conditions:
- the aspect has a direct relation to soil, e.g. the colour or grey tone of
the topsoil, and the drainage condition;
- the aspect indicates certain conditions of soil formation; changes in the aspect mean changing conditions of soil formation and most likely different
soils, e.g. differences in slope and relief, or in parent material;
- the aspect shows consequences of soil differences, e.g. differences in
natural vegetation and in a number of cases, in land use.
The methods of image-interpretation for soil science are:
- the aspect analysis or element analysis acc. Buringh (1960);
- the physiographic analysis or physiognomic analysis acc. (Bennema and
Gelens, 1969) ;
- the morphogenetic analysis. The aspect analysis is based on a systematic analysis of individual aspects in
the image. For each aspect, an interpretation map is produced. Finally, the
aspect interpretation maps are superposed on each other. As a first approxi-
mation to validity of the boundaries f o r soil survey, the boundaries due to
repetition of two or more aspect boundaries are given more value than the
183
boundaries due to single aspects. However, although accurate, the pure form of
the aspect analysis is time-consuming, and the more experienced photo-
interpreter will directly use certain combinations of aspects for delineation
of mapping units. He will choose those aspects which he supposes to have a
close relation to soil conditions.
Physiographic or physiognomic analysis (Bennema and Gelens, 1969) restricts
itself to the external features as shown in the stereo-image. The same elements
of the aspect analysis are used but in a different way. Those areas which have
uniformity in appearance are delineated and characterized by the same symbol on
the images. When the physiognomy changes, a different unit has to be
delineated. The physiographic analysis includes the analysis of basic and
compound aspects, such as relief, slope as well as vegetation and land use, and
aspects important for the description of the drainage system. A morphographic
analysis resticts itself to those aspects of the physiography that can be used
to describe the morphography of the land, namely: relief, slope, valley forms
and drainage patterddensity.
The morphogenetic analysis comprises the delineation of units not only on the
basis of their appearance, but also on the basis of the processes which have
shaped these units. Most important for the morphogenetic analysis is of course
the geomorphology of the area, but also hydrology and other factors may play
their parts. Specific knowledge is required of the morphogenetic processes and
it is not likely that this analysis is the first step in the interpretation of
airphotos of an unknown area. However, in image analysis some geomorphological
terms may be applied with great certainty, such as: river levees, river basins,
point bars, beach ridges. It will be understandable, that in practice a
combination of the physiographic and morphogenetic analysis is generally
applied.
Table 8.1 summarizes the methods of image-interpretation. The different
phases in interpretation are indicated, being: detection, recognition,
identification, combination, classification and deduction. The information
derived from the aspect analysis and the physiographic analysis can be
transformed by combination and deduction into morphogenetic information,
revealing the cause of the soil conditions.
Fig. 8.1 shows the different steps which may be taken in interpretation if
there are no limitations in identification. (Limitations may exist due to lack
of stereoscopv for relief and slope analysis). The flow chart is
184
Table 8.1. Methods of image-interpretation.
Phases in interpretation
Detect- Recognit- Identifi- Combinat- Deduct- S o i l ion ion cation and ion and ion and format-
Classifi- Classifi- Classifi- ion cation cation cation
Aspects of- basic aspects compound inferred interpreta- aspects aspects t ion
symptoms and
Methods of aspect analysis effects analysis physiographic analysis
transformation + morphogenetic cause analysis
constructed in such a way that the landscape performance on the images
determines the steps to be taken. The occurrence of landtypes and drainage ways
are considered basic for this purpose. If drainage ways are present, the
drainage density, which may be influenced strongly by scale, offers a further
key to interpretation procedures. The analysis of basic and other compound
aspects forms the next phase in interpretation. Deduction is necessary for the
analysis of geological structures and inferred aspects, as well as for
morphogenetic processes.
Some landscapes require a specific approach e.g. parts of river basins with
very low drainage density (continue with analysis of natural vegetation etc.),
dune areas without drainage ways (analyse relief and/or slope, and continue
with analysis of natural vegetation and land use) .
For literature on terrain analysis, the reader is referred to Zuidam et al.
( 1978-1979).
After the image-interpretation, field observations are made to identify soils
and to check the boundaries between the mapping units. Generally, a second and
more final interpretation is made on the basis of the newly acquired knowledge
from the field. The image-interpretation may also be done simultaneously with
the fieldwork.
At present, various remote sensing techniques are at our disposal. Of
these techniques aerial photography is the most common tool in soil survey
since it offers steroscopy that enables accurate-relief and slope analysis.
Other remote sensing techniques, such as multispectral scanning may be used
185
t
7 I/ very low low to moderate high to very
delineation of permanent water courses and intermittent water courses
drainage drainage density high drainage density I
delineation of dry valleys
Figure 8.1 Flow chart for image interpretation
One landtype" Two OK more landtypes*
I asseLsment of drainage pattern
t assesment of slope and site
assessment of natural vegetation, land
and rock outcrops L t use, animal constructions, soil surface
t Deduction on geological structures, kind of parent material and inferred aspects such as soil depth, drainage and erosion conditions.
* Designation in morphographic and physiographic but preferably morphogenetic terms.
for relatively high-standard identification of objects. However, except for
SPOT imagery, they do not offer a complete stereoscopic view and their main
key to relief is shadow.
In radar imagery, shadows together with high lights offer information about
height, slope and orientation. However, steroscopic observation is only
possible by viewing overlapping images. To obtain these for scanning or radar
devices, a two-flight coverage is required which involves relatively high
expenses. Therefore, the new remote sensing techniques are generally not used
in stead of, but in conjunction with aerial photography.
Of the numerous aspects that can be studied in image-interpretation, only a
selection of aspects which are most relevant for soil survey are discussed
below. The obvious first step in image-interpretation is the delineation of
units that internally have a great number of aspects in common, but externally
deviate strongly from their surroundings. These units are called "landtypes".
8.2. Landtypes
A landtype can be seen as an aspect of a very compound nature. The
criteria used for discrimination of landtypes depend on the variety in the
area under consideration. Relief, drainage pattern, natural vegetation, and
sometimes land use may be criteria for the recognition of landtypes. The terms
used for description of landtypes are a reproduction of the physiography or
morphogenesis of the land and depend on the scale of the imagery as well as on
the interpreter's reference level with regard to the landscape genesis, or in
other words, the processes that shaped the units. In small and medium-scale
surveys, often physiographic terms are applied. Pure physiographic terms may
be based on relief features, drainage pattern and topography. The last aspect
may comprise indications such as mountains, hills (isolated, dissected,
elongated and rounded), plateaus, table mountains, plains, etc.
The terms may have a genetic meaning in the sense of
- relative position e.g. interior or coastal lowland and upland;
- geomorphological history e.g. denudational plains, old and young coastal
plains; high, medium and low marine terraces or river terraces;
- tectonical history e.g. land with folds, faults or numerous joints;
structural basins;
- petrological composition (often deduced from drainage pattern and shape or pattern of hills) e.g. volcano land, "kopjesland" (outcropping hard rock);
granite, schist or karst land, the last referring to chemical solution of
gypsum or limestone;
- depositional history and setting e.g. alluvial plain or more specifically
fluvial, coastal or glacial plains; delta, lagoon, dune and beach ridge or
rivervalley land;
- human activity e.g. nature reserve land; (recent or old) arable land,
grazing or forested land; terraced or polder land;
- repeated sequences of soils e.g. land characterized in terms of steepest
slope (relief class) and dominant slope (example: steeply dissected, domi-
nantly moderately steep).
187
Marshland is an example of a landscape in which the relative topographical
position, the natural vegetation or land use and the drainage condition are
expressed jointly.
Further subdivision of land types depends on the scale of survey and may be
done into land-units and/or analogous to the Australian system into land
components. The Australian system shows the following mapping units (Gibbons
and Downes, 1964):
- Land-component, smallest mapping unit; climate, parent material, topography, soil and vegetation are uniform within the limits significant for a
particular form of land use;
- Land-unit, basic sequence of land-components; - Land-system, grouping of land units, which have in common, landforms, or
structural forms of vegetation, or some other significant land charac-
teristics;
- Land-zone, or an area in which a number of similar land-systems are present;
the boundaries between land-zones will always coincide with significant
differences in one or more major environmental features.
Comparison shows that the landtypes mentioned above will often be in medium-
scale surveys at the level of land-unit or landsystem in the Australian
system.
On the level of land-unit, the above given summation of terms for landtype
description also contains indications of landforms. Since it is a free system,
this is allowed and, as has been said, the terms that will be applied depend
on scale and reference level.
When the landform can be inferred and if it is large enough to be
delineated, landform terms are generally preferred above physiographic
indications at high levels in the legends of interpretation maps. This is
mainly due to the high information potential of landforms for soil conditions.
Then physiography may be used for the description of landforms on a lower
level. At large- and medium- scale surveys, the landforms generally become
more important besides the physiographic and broad morphogenetic terms.
Examples are given below:
- Old denudational forms, besides river- and marine terraces and table
mountains: inselbergs, raiias (Pliocene alluvial fan remnants), glacis
(Pleistocene) etc.;
- Recent denudational forms: badlands, gullied land, land eroded by sheet- and
188
rill-erosion etc.;
- Fluvial forms: levees, basins, flood plains (relatively high and low in case of occasional floods, summer and winter in case of seasonal floods),
alluvial fans etc.;
- Colluvial forms: colluvial footslopes etc.; - Coastal forms: beach ridges, swamps, mud flats etc.; - Aeolic forms: barchan dunes, longitudinal dunes, loess mantles etc.; - Glacial forms: gletschers, moraines, ice-pushed ridges etc.; - Karstic forms: gypsum or limestone karst, dolines, collapse sink etc.; - Volcanic forms: dikes, volcano slopes and craters; lava flows, lahars, ash
OK lapilli mantles etc.;
- Diapyric forms: salt d8mes etc.; - Forms derived from tectonical action: anticlinal and synclinal structures, fault structures expressed in the landscape (cliffs).
For more information on landforms, the reader is referred to textbooks on
geomorphology, such as Strahler (1969) and Cooke and Doornkamp ( 1 9 7 4 ) . An
example of an area with different landtypes is given below (see fig. 8.2).
The landtypes have the following characteristics:
A. Elongated Hills: moderate drainage density;
steeply dissected land with rolling footslopes.
B . Steeply dis- high drainage density;
sected land steeply dissected land with rolling footslopes.
C. "Kopjes" Land: very low drainage density;
hilly and steeply dissected land.
D. Plain: moderate drainage density;
undulating.
Further subdivision in land units and components may be done on the basis of
drainage pattern, on the presence of rock outcrops or natural vegetation,
including type, tone and surface density.
8.3. Relief, slope and site
Relief and slope are discussed together, since relief can be considered
as a complex (or a pattern) of slopes. The FAO-classes of relief are based on
the occurrence of steepest slopes. The following classes are distinguished:
Fig. 8.2 Landtypes North-eastern part of Serengeti National Park (Tanzania). Date of flight aerial photograph : Jan. 1972 Landtypes: A. Elongated Hills C. Kopjes Land
B. Steeply dissected Land D. (Undulating) Plain
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relief classes steepest slopes
flat and almost flat < 2%
undulating between 2 and 8%
rolling between 8 and 16%
hilly range in elevation between 16 and 30%
steeply dissected moderate < 300 m*) > 30%
mountainous: great range in elevation (> 300 m*) > 30%
* note of the author
The range in elevation (OK local relief) of mountainous terrain has to be more
than 300 m. A further subdivison of mountainous terrain may be made into:
- low mountainous terrain, local relief between 300 m and 1000 m; - high mountainous terrain, local relief 1000 m OK more.
Local relief can be defined as the maximum difference in elevation within a
mapping unit (e.g. land type).
Relief features are highly visible in the airphotos and show a strong relation
to soil conditions. Soil bodies are likely to OCCUK in repetitive sequences in
areas with a particular relief. Depending on the scale of the imagery and the
characteristics of the area under consideration, it might be necessary to
combine two relief classes in order to characterize a mapping unit. The relief
units may be distinguished in more detail by the following properties: local
relief or maximum height difference, steepness of dominant slopes and dominant
orientation of slopes.
Slope has a particular meaning for soil conditions, since it is:
- a soil forming factor; - the configuration of the surface;
- an expression of geogenesis; - related to drainage conditon; - an important element of land evaluation.
191
The FAO-classes of slope are:
class
1 flat or almost flat
2 gently sloping
3 sloping
4 moderately steep
5 steep
6 very steep
%
0- 2
2- 6
6-13
13-25
25-55
> 55
-
Other aspects of slope are:
- shape - single slopes - convex, - concave, - straight. - complex slopes;
- changes of slope, abrupt (angular breaks) or gradual (smooth);
- size, e.g. long even slopes and short ones;
- position in relation to direct solar radiation, dominant wind direction, or stratification of rocks.
Mapping of the configuration of the surface or morphological mapping may
be done by the analysis of stereo-imagery (e.g. airphotos) and fieldwork. As a
basis of this mapping, Cooke and Doornkamp ( 1 9 7 4 ) present the recognition of
the following features:
- breaks of slope; - gradual changes of slope; - angle (' or %) and shape of slope units.
Cliffs (40' or 84% or more) are indicated separately from the other slope
units. Symbols, as well as an example are given in fig. 8.3.
Site is concerned with the relative position of the mapping units.
Through deduction on degree of slope, shape and arrangement of the mapping
units, it is possible to indicate: plateaus, summits, tops, shoulders, slopes,
footslopes, valley bottoms and other depressions. Landtypes, generally, are
characterized by typical toposequences. The delineation of these site-units
might be of major importance in mapping of soils due to differences in soil
formation (age and process), soil texture, drainage condition, erodibility
etc.
192
II__
slopes
Angular convex break
Angular concave break
Smoothly concex change
Smoothly concave change
Angle of s lope (O)
C l i f f s (bedrock, 3 40')
AAUUUU Breaks of slope
Changes o f slope - Convex slope u n i t - Concave slope u n i t
Convex and concave * too c lose together t o allow the use of separate symbols
Fig. 8 . 3 Symbols for morphological mapping after Cooke and Doornkamp (1974)
8.4. Natural drainage patterns
Streams and drainage patterns are visible through a number of basic
aspects which may be relief, slope, water, soil surface and/or vegetation
(Bennema and Gelens, 1969) .
Rivers OK streams may be destructive OK constructive. respectively erosive Or
depositional. The latter may be accompanied by depositonal terraces, levees,
back swamps and (lower) floodplains. Delineation of chese units is important
for soil mapping, owing to the related differences in soil texture and soil
development.
The main types of rivers are:
- wilded OK braided rivers with an irregular regime; - meandering rivers with a regular regime, their course being
193
- well-developed, - interrupted due to barriers related to geological structures (e.g. dykes
and faults).
Various types of stream forms are given in fig. 8.4.
I meandering lmeandering w i t h r a p i d s I Yazoo
Fig. 8.4 Stream forms and associated patterns.
A so-called anastomotic drainage pattern develops when the river regime
has meandering as well as braided characteristics. Normally the river-channel
i s capable of carrying its water and bedload, but sudden changes may alter the
streamcourse to a more braided pattern. Consequently, this type shows large
floodplains with a network of diverging and joining channels with many oxbow
lakes and cut-off channels of varying width.
The deranged or disordered stream pattern is an immature type. The very
irregular stream valleys are usually wide and many lakes and/or marshes can be
found along the stream-courses. Another pattern is formed when the natural
levees are high. The streams in the back swamps are forced to flow parallel
with the main stream until a break in the levees is reached: the so-called
Yazoo type.
Near to the ocean coasts or near to borders of interior lakes or seas,
the type of shoreline strongly influences the drainage pattern.
Strahler (1969) gives five classes of shorelines:
194
1) shorelines of submergence, caused by a sinking down of the earth's crust or
by the Holocene world-wide rise of sea-level (e.g. ria shoreline) and
characterized by a highly irregular and inherited drainage pattern;
2) shorelines of emergence, caused by a rising of the earth's crust or fall in
water-level of interior seas; the waterline takes a position against what
was formerly a slope of the seafloor; most seafloors have received
stratified deposits derived from erosion of the land and distributed by
currents; the new drainage pattern develops on a relatively smooth, gently
sloping sediment surface;
3) neutral shorelines, being built out into the water by deposition of new
materials, e.g. alluvial fans and delta shorelines; also coral reef
shorelines belong to this group;
4 ) fault shorelines, produced by faulting of the earth's crust in such a way
that there is a dropping, down at the seaward side and a consequent rising,
up at the landward side; usually, the formation of cliffs is the result;
5) compound shorelines are those that show forms of at least two of the
previous classes.
Some examples of drainage patterns at neutral shorelines are given in fig.
8.5.
Figure 8.5 Some drainage patterns at neutral shorelines and alluvial fans.
The dichotomic pattern Is a distributary pattern, which occurs in
195
alluvial fans and deltas. The distributary streams are branching.
The arcuate delta is the most common delta-type. Others are: the bird's foot
and estuarine delta.
The colinear pattern is found in areas with sand ridges. Stream courses and
flowing surface waters may appear and disappear in the marshy interridge
areas.
The elongated bay type is found in deltas and coastal plains. The form shows a
row of troughs, often lying along old beaches. The interlocking or reticular
drainage pattern consists of small "snake-like" distributary streams, which
usually drain into large channels. They are found along sea-coasts in tidal
marshes. The direction of flow is reversed when the tide changes.
The thermokarst stream patterns sometimes assume the shape of huge mudcrack
patterns. The term thermokarst is used to describe the thaw sinks and
associated features which dot arctic coastal plains.
The drainage patterns of inland areas are often dense and complicated,
making it useful to apply additional systems for systematic analysis. Strahler
(1969) has presented a system to analyse the composition of the branching
systems of channels, treating them as lines on a plain. All fingertip
tributaries are designated as segments of the first order, two first-order
segments produce a channel of the second order. At the joint of two second-
order segments arises a third order, etc. (see fig. 8 . 6 ) . This method for the
analysis of drainage patterns makes it possible to designate particular
patterns for groups of stream orders (the pattern of lower orders often
differs from that of higher orders) and also makes a quantification of the
drainage network possible.
Another aspect of drainage pattern is surface density, which refers to
the number and relative spacing of drainage courses per unit area in a
drainage basin. In considering the density, it is usual to take into account
all the drainage courses, even the dry valleys. It is possible to indicate the
density of a drainage pattern by a numerical value. This value is calculated
by measuring the total length of drainage courses per unit area and dividing
the total length of the courses by the surface area of that unit (km/kmL). One
may use a relative surface density: cm/cm2 at a particular scale. Five classes
of surface density are suggested for this purpose:
196
b a s i n
F i r s t o r d e r
Second o r d e r
T h i r d o r d e r
F o u r t h o r d e r
L a r g e r s t ream o f h i g h e r o r d e r
Fig. 8.6 Stream orders after Strahler (1969)
surface density class length of drainage COUKSeS 2 in cm per cm
very high > 4.5 high 3.0 - 4.5 moderate 2.0 - 3.0 low 0.5 - 2.0 very low < 0.5
The various classes are demonstrated in fig. 8.7. This figure may be used for
visual estimation of the relative density classes at a particular scale.
The drainage patterns of the inland areas, excluding stream forms and
associated patterns, can be divided into:
- multi-basinal and radial patterns;
197
Very h igh
High
Moderate
Low
u Very low
Figure 8.7. Relative surface density classes of drainage ways.
- freely developed patterns; - structurally controlled patterns. Examples are given in fig. 8.8.
The term multi-basinal pattern is used for areas in which a number of not
well coordinated depressions are found. They may develop under fully different
conditions.
The shallow-hole pattern, which is accompanied by dolines (solution) and
collapse sink or sinkholes, is most common in limestone areas. The streams in
those areas flow partly underground.
The kettle-hole pattern consists of randomly spaced depressions with an
occasionally water-filled basin. The individual tributary systems may have a
dendritic pattern. They occur in areas with a topography derived from glacial
action.
Radial patterns can be subdivided into centrifugal and centripetal patterns. In
the first case the stream branches run away from the centre, in the latter the
stream branches flow towards the centre (see fig. 8.8).
In the freely developed patterns the influence of geological structure is
weak or negligible. In this concept, areas with strong chemical solution
(shallow-hole pattern) and glacial areas with many depressions (kettle-hole
pattern) as well as radial patterns (e.g. volcanoes) are excluded in preventing
198
I
M U L T I B A S I N A L AND R A D I A L PATTERNS
swallow-hole
radial: centrifugal
kett le-hole
radial : centripetal
FREELY DEVELOPED PATTERNS
dendri t i c
para1 @ 1 e l
subdendri % t i c m subpara1 l e l
STRUCTURALLY CONTROLED JATTERNS
.annular
angulate
rectangular
contorted
Fig. 8.8 Multibasinal, freely developed and structurally controlled drainage patterns.
199
a f r e e deve loping of d ra inage ways upon e r o s i o n a l a c t i o n . The d e n d r i t i c t ype 1s
c h a r a c t e r i z e d by i r r e g u l a r branching of t i b u t a r i e s . Streams of a lower o r d e r
j o i n t h e nex t h ighe r o r d e r s t reams a t approximate ly t h e same angle . The
s u b d e n d r i t i c t ype i s a m o d i f i c a t i o n which may be s l i g h t l y StKUCtUKally
c o n t r o l l e d ( f i g . 8.8).
The p i n n a t e p a t t e r n has a f e a t h e r l i k e appearance. The f i r s t and /o r second o r d e r s t reams a r e o f t e n s h o r t and more o r less p a r a l l e l . The s t r eam branches mostly
j o i n t h e l a r g e r streams a t an a c u t e angle .
The d ichotomic p a t t e r n , be ing c h a r a c t e r i s t i c f o r a l l u v i a l f a n s , a l s o be longs t o
t h e f r e e l y developed p a t t e r n s ( s e e f i g . 8.5). Other t ypes a r e t h e p a r a l l e l and
s u b p a r a l l e l p a t t e r n s .
Examples of s t r u c t u r a l l y c o n t r o l l e d d ra inage p a t t e r n s a r e a l s o g iven i n
f i g . 8.8. In t h i s group are p laced t o g e t h e r t h e d ra inage p a t t e r n s which are
s t r o n g l y in f luenced by g e o l o g i c a l s t r u c t u r e . t h a t i s , t h e presence of beds wi th
d i f f e r e n t r e s i s t a n c e , O K f a u l t s and j o i n t s de te rmine l a r g e l y t h e d ra inage
p a t t e r n .
The annu la r p a t t e r n i s a mod i f i ca t ion of t h e r a d i a l p a t t e r n . The s t ream cour ses
a r e a d j u s t e d t o f low around domes wi th r e s i s t a n t c o n c e n t r i c rock format ions .
The t r e l l i s p a t t e r n i s c h a r a c t e r i s t i c of fo lded o r d ipp ing sed imentary rocks .
The lowest o r d e r t r i b u t a r i e s may j o i n t h e nex t h ighe r o r d e r s t reams a t
approximate ly r i g h t a n g l e s and a r e o f t e n p a r a l l e l . Streams of h ighe r o r d e r s a r e
o f t e n long and s t r a i g h t , and p a r a l l e l t o each o t h e r .
The r e c t a n g u l a r p a t t e r n deve lops i n a r e a s i n which j o i n t s and f a u l t s are
p resen t i n t h e bedrock a t r i g h t ang le s . The a n g u l a t e form i s a mod i f i ca t ion i n
which j o i n t s and f a u l t s a r e o r i e n t e d a t ob l ique ang le s . T r i b u t a r i e s t end t o be
p a r a l l e l . The c o n t o r t e d p a t t e r n i s a l s o s t r u c t u r a l l y c o n t r o l l e d . This form may
i n d i c a t e stream p i r a c y , so t h e d i r e c t i o n of flow may be r eve r sed and sha rp
bends come i n t o being.
I n s tudy ing d ra inage systems, a t t e n t i o n should be pa id t o t h e i n d i v i d u a l
g u l l i e s O K s t reams. In p a r t i c u l a r , t h e shape of t h e c r o s s s e c t i o n can be of
importance. There are two main types : U- and V-shaped v a l l e y s . Other a s p e c t s
can be desc r ibed , such a s form and s t e e p n e s s of v a l l e y s l o p e s , width of t h e
v a l l e y bottom, symmetry and dep th of t h e v a l l e y . The g r a d i e n t of t h e v a l l e y
bottom i s ano the r impor tan t a s p e c t . The water regime of stream courses can b e
eva lua ted t o a c e r t a i n e x t e n t by a i r p h o t o - i n t e r p r e t a t i o n . Permanent and
200
intermittent water courses as well as dry valleys are normally indicated (see
fig. 8.9). Criteria used for evaluation of the water rdgime are a.0.: drainage
pattern, stream order, stream form, valley form and width, and natural
vegetation.
Figure 8.9 Example of analysis of drainage patterns. A. Dendritic, first to third order, high density (second order angulate
B. Subparallel, first to fourth order, moderate density. C. Main river, meandering, tributaries fourth order subparallel and low
D. Parallel, third order, very low density. E. Dendritic, first to third order, moderate density (third order parallel
tendency).
density . tendency)
permanent water course _ _ _ intermittent water course _ _ _ _ _ - dry valleys
8 . 5 . Natural vegetation
Natural vegetation often shows a close relation with relief, drainage
pattern and soil distribution. Therefore, in tropical forest areas and other
201
places where human interference is of minor influence, it is an important aid
in soil mapping. However in many places in these areas, burning, shifting
cultivation and ranging, affect the natural vegetation very much. Then the
impact of these activities has to be understood to use this element in
deducting soil conditions.
An identification of the type of vegetation cover on imagery may be based on:
- grey or colour tone (reflection characteristic); - texture and/or pattern (see par. 6.3); - shape of individual crowns; - height and shadows of trees; - the distribution or surface density of individual tree or shrub cover types; - the site or topographic position. In fig. 8.10 a measure for surface density or cover scale (see Braun-Blanquet,
. 1932) is given. The following coverage indications are suggested:
0- 5 very low 50- 75 high
5-25 low 75-100 very high
25-50 moderate
25 % 50 96 75 96
very-- l ow - c- moderate - - high __c +very 1 ow h igh
Fig. 8.10 Examples of coverage percentages.
Some natural vegetation cover types are (see Fig.. 8.11 and Van Gils and
Zonneveld, 1982) :
- forest (low, medium high, high); - woodland savanna with almost closed canopy; - open woodland savanna (complex cover form); - shrubland and dwarf-shrubland; - grassland (herb vegetation) with scattered shrubs (complex cover form);
202
- grassland (herb vegetation). The so-called barren land, showing no or a scarce vegetation cover, can be
subdivided (after Van Gils and Zonneveld, 1982) into: barren rock, badland,
beach, mudflat, icecap and snow.
SHRUB
GRASSLAND WITH SCATTERED SHRUBS 1 Fig. 8.11 Natural vegetation cover types (originally drawn by W.A. Blokhuis).
More detailed analyses can be made if specific knowledge is available about
the vegetation of the area under consideraton. Large-scale airphotos are often
203
used in v e g e t a t i o n s t u d i e s and make d e t a i l e d mapping of cover types p o s s i b l e .
Also t h e type of photographic f i l m is impor tan t . Full co lour photographs, i f
t aken under clear weather c o n d i t i o n s , o f f e r good p e r s p e c t i v e s . However, f i l m s
s e n s i t i v e t o t h e nea r I n f r a r e d a r e a l s o promising, s i n c e v e g e t a t i o n cover types
wi th d i f f e r e n t s t r u c t u r e s can be d i sc r imina ted by t h e i r nea r In f r a red
r e f l e c t a n c e . The f a l s e co lour - f i lm can be regarded a s s u p e r i o r t o t h e hlack-
and wh i t e - in f r a red f i l m , but i s more expens ive than t h e l a t t e r .
8.6. Land use , c rops and p a r c e l l i n g
By t h e t e r m land use , w e do no t mean a n i n d i c a t i o n of t h e types of c rops ,
bu t a gene ra l d i v i s i o n i n t o l and used f o r a.0. a g r i c u l t u r e , rangeland o r
f o r e s t r y . In t a b l e 8.2, t h e r u r a l l and use c l a s s i f i c a t i o n proposed by Van Gils
and Zonneveld (1982) i s given.
The co inc idence of land use boundar ies w i th s o i l boundar ies is g e n e r a l l y
low (Goosen, 1967), l and use be ing a complex f e a t u r e t h a t depends on p h y s i c a l
a s w e l l a s on socio-economic f a c t o r s . However, i t may be used i n a number of
cases a s a n i n d i c a t o r f o r soil cond i t ions . Actua l ly , l and use over l onge r
pe r iods may have g r e a t impact on soil: i n a c o n s t r u c t i v e sense (e.g. man-made
soils with a Plaggen epipedon) and i n a d e s t r u c t i v e sense (e.g. eroded and
t r u n c a t e d soils).
I n p r i n c i p a l , c rops a r e i d e n t i f i e d on remote sens ing imagery i n t h e same
way as n a t u r a l v e g e t a t i o n . However, f o r proper i d e n t i f i c a t i o n , a r e l a t i v e l y
h igh r e f e r e n c e l e v e l i s r equ i r ed . Height , s i z e , p a t t e r n and tone a r e impor tan t
a i d s f o r t h i s purpose.
Other t y p i c a l a s p e c t s of a g r i c u l t u r a l i n t e r p r e t a t i o n of remote sens ing imagery
a r e a.0. t h e e s t i m a t i o n of product ing a r a b l e ac reage and non-producting a r a b l e
ac reage , and of a r e a s c o n t a i n i n g weeds. Furthermore, t h e soil cond i t ion , t h e
r e f l e c t a n c e of c rops in s p e c t r a l bands and t h e d e t e c t i o n of c rop d i s e a s e s may
be s u b j e c t s of i n t e r e s t .
P a r c e l l i n g i s c l o s e l y connected wi th land use. Shape and s i z e of t h e i n d i v i d u a l
p a r c e l s , t h e i r arrangement and r e g u l a r i t y r e s u l t in a p a r t i c u l a r p a t t e r n . The
h i s t o r y of land use may be r e f l e c t e d i n p a r c e l l i n g , e.g. o l d a r a b l e land
i n t h e Nether lands g e n e r a l l y shows i r r e g u l a r p a r c e l l i n g and small
204
Table 8 . 2 Rural land use classification proposed by Van Gils and Zonneveld (1982)
SETTLEMENT AND INFRASTRUCTURE (a) residential (b) industrial, quarrying, mining (c) transport and communications (d) recreational
AGRICULTURAL (a) annual herbaceous crops; irrigated or dryland (b) perennial herbaceous crops; e.g. alfalfa, grass mixtures, sugar cane, sisal (c) woody crops; including bananas, rubber; annually harvested for fruits,
leaves etc.
RANGELAND (a) ranching (b) pastoralism (c) hunting and gathering
FORESTRY (a) timber (b) pulp-wood (c) wood; firewood, pitwood or pickets and other domestic uses (d) others; e.g. bark, terpentine, tannin, corck; periodically harvested
NATURE RESERVE
WATER (a)ishing (b) storage (c) aquaculture (d) other uses
OTHER USES Water catchment, restauration of soil fertility in shifting cultivation, conservation, protection
NOT USED
COMPLEX LAND USE: Two or more land use categories on different fields but for cartographical reasons put in a single land mapping unit.
MIXED LAND USE: Two or more land use sub-categories are found in the same field; for example intercropping: woody crops (olives) with annual crop (small grains).
MULTIPLE LAND USE: Two or more main land use categories simultaneously or periodically on the same land; for example: dehesa: rangeland/forestry/agriculture shifting cultivation: agriculture/forestry or agriculture/rangeland.
205
size parcels in contrast with recent polder land, which normally has regular
parcelling and large size parcels. The following indications may be used for
description: shape e.g. square, rectangular, longitudinal;
size e.g. very small, small, large;
arrangement e.g. parallel, radial, random;
regularity e.g. regular, irregular.
8 . 7 . Drainage condition
The drainage condition is an inferred aspect, which may be concluded from
features such as:
- land use, e.g. non-irrigated pastures are usually located on sites with
poorly drained soils;
- natural vegetation type; - presence or absence of water-logged areas; - presence or absence of artificial drainage (density - grey or colour tones of bare soil surfaces, e.g. poorly drained so i l s often
and pattern);
show dark tones on the images;
- site.
Drainage condition is a soil property and is therefore strongly related
to the condition of the soil. However, problems are often encountered in the
interpretation and it can be stated that the visibility by means of remote
sensing is only moderate, unless thermal imagery and multitemporal data are
used.
The FA0 classes for drainage condition are as follows:
- very poorly drained; - well drained; - poorly drained; - imperfectly drained; - moderately well drained;
- somewhat excessively drained; - excessively drained.
For explanation of the drainage classes, the reader is referred to FAO:
Guidelines for soil profile description. In most cases it will only be
possible to infer combinations of two classes.
Special mention is made of Infrared photography. Since moist bare soil
strongly absorbs the Infrared radiation, it appears in very dark tones on
these airphotos and can be discriminated clearly from dry soil.
206
8.8. Other aspects
A number of aspects that are important in interpretation of remote sensing
imagery for soil survey, but are not discussed in the preceding text, are:
of the basic aspects - soil surface, - rock outcrops and bare rock areas;
of the compound aspects - geological structures,
of the inferred aspects
- animal constructions; - parent material, - soil depth, - erosion condition.
The soil surface may be bare or only partly covered with crops or natural
vegetation. Differences in soil surface in those cases may be visible through
differences in grey tone or grey tone pattern e.g. dark tones may correspond to
moist heavy soils or topsoils rich in organic matter.
Gilgai relief in Vertisol bodies shows a pattern of depressions, with dark
tones, and higher places, with light tones. Besides this, gilgai is
characterised by a typical cracking pattern.
Ploughing activities on podzols may reveal a typical mottling in areas with
bare soil, owing to the differences in colour between the material of the
horizons exposed at the soil surface (A1 , A2, B2h or B2ir and C).
Rock outcrops and bare rock areas are visible on the airphotos by their
deviating tone as compared with their environment, and often by their structure
(e.g. the occurrence of layers).
A number of geological structures may be identified, such as:
folds - characterized for example by rock layers
sloping in (two) opposite directions;
faults - shift of geological strata visible by
lineaments on the images;
joints - crack systems often affecting the drainage
pattern;
intrusions - often hard rocks, offering more resistance to weathering than other rocks in their
surroundings;
201
dikes - linear intrusions, e.g. dolerite dikes;
volcanoes and their products - volcanoes are characterized by their relatively high elevation and radial drainage patterns; lava streams can often be
characterized by their relative age (due to a.0. superposition and
weathering condition); efflata may form a mantle over older deposits
and can give rise to alluvial fans and lahars.
Some animal constructions belong to the basic elements, hut one of the
most important constructions, the termitemound, is visible through a
combination of surface configuration, natural vegetation or soil surface, and
is therefore a compound element. The termite mounds appear as white dots on
the image. The large ones may have trees or bushes growing on them, while the
rest of the area shows a sparse vegetation.
Many of the boundaries drawn on the interpretation map are also
boundaries between different parent materials. They may appear by differences
in relief and drainage pattern, breaks of slope, etc. In most instances,
fieldwork must decide on the type of parent material, but sometimes it is
possible to identify this to a certain extent by image interpretation.
The identification may be based on:
a. drainage pattern, e.g. swallow-hole patterns in areas with limestone, knob
and kettle patterns in areas with glacial deposits, or radial patterns of
volcanoes; furthermore structurally controlled drainage patterns may offer
strong indications;
b. landform, e.g. table mountains, dunes, alluvial fans, coastal plains and
rivervalleys;
C. site, e.g. colluvial deposits are most likely at the foot of a slope;
d. soil surface (micro-relief and reflectance), e.g. gilgai-pattern (micro-
relief) in Vertisol areas, and differences in reflectance, which are due to
a different soil moisture condition or a different mineralogical and
textural composition;
e. observations at steep slopes with rock outcrops, e.g. stratification.
To a certain extent, a hypothesis on the relative age of the soil
formation may be built up during the interpretation. Suppose we have a terrain
which has a configuration such as indicated in fig 8.11. At A the oldest soils
are expected to be present and consequently, soils will show the strongest
208
development at this place. At B, the very steep slope accelerates erosion and
soils will be shallow and of a young to moderate age. In the sequence, young
soils in colluvial deposits are expected at C and young soils formed in
fluviatile deposits will be present at D.
A
Figure 8.12 Terrain profile (see text for discussion).
As indicated above, conclusions about soil depth may be drawn from the degree
of slope, but they may also be based on site (at C and D in fig. 8.12 soils
will nodually be deep) and the occurrence of rock outcrops (except tropical
rain forest areas), a large area of rock outcrops is often indicative .of the
occurrence of shallow soils.
Three classes of soil depth can be used, being:
a. shallow soils (e.g. < 30 cm), most common in areas with many rock outcrops
and/or steep to very steep slopes;
b. moderately deep so i l s (e.g. 30-60 cm), most common i n areas with few or no
rock outcrops and moderately steep slopes;
C. deep soils (e.g. > 60 cm), most common in alluvial areas and other terrain
with slopes less than 13%.
The classification of depths usually depends on the objectives of the soil
survey. There is no forced classification.
The erosion condition refers to accelerated erosion which may be visible
on the images. The main forms of erosion are: gully erosion, rill erosion and
inter-rill or sheet erosion. Only the gully and rill erosion may be visible as
such on the image, sheet erosion has to be concluded from differences in grey
or colour tones in relation to soils, land use, site and configuration of the
terrain.
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8.9. Conclusions
Since soil has a complex nature, it is not possible to indicate a single
phenomenon that causes its formation, the combination of the various aspects of
interpretation together with deduction plays an important role in image-
interpretation. Most remote sensing techniques are capable to detect
superficial phenomena, and offer a synoptic view of the landscape. However, in
the study of soils, which are three-dimensional natural bodies, field work is
always a necessary complement.
A number of aspects can be distinguished in image-interpretation for soil
survey. They can be divided into basic -, compound - and inferred aspects. Most aspects have to be regarded as symptoms of a complex cause, the soil formation.
However, some aspects may be regarded as results of particular soil conditions.
The three basic methods of image-interpretation are the aspect analysis, the
morphographic and physiographic analysis, and the morphogenetic analysis. The
third method requires not only a morphographic approach, but also knowledge of
processes that shaped the different landscape units.
We recognize three phases in the interpretation for soil survey, being:
1) analysis of landtypes and drainage ways;
2) analysis of basic and other compound aspects;
3) deduction on geological structures, parent material and inferred aspects
such as soil depth, erosion and drainage condition.
The steps that may be applied in interpretation, depend on scale and type of
remote sensing imagery.
Aerial photography shows advantages above most other remote sensing techniques
(except for SPOT stereoscopic imagery) in offering stereoscopy, which enables
accurate analysis of relief and slope. Other remote sensing techniques,
however, may offer good opportunities for optimum identification of specific
objects.
8.10. References
Bennema, J. and H.F. Gelens, 1969. Aerial Photo-Interpretation for Soil Surveys. Lecture Notes ITC, Enschede, The Netherlands: pp. 1-87.
Braun-Blanquet, J., 1932. Pflanzensoziologie, Springer, Berlin, Plant Sociology (transl.) by Fuller ti Conard, 1932. McGraw. Hill Book Cy, New York- London.
Buringh, P., 1960. The application of Aerial Photography in Soil Surveys. Manual of Photographic Interpretation: pp. 631-666.
Cooke, R.U. and J.C. Doornkamp, 1974. Geomorphology in Environmental
210
Management. An Introduction. Clarendon Press. Oxford: pp. 1-413. FAO, Guidelines for Soil Profile Description, MI/70805: pp. 1-53. Gibbons, F.R. and R.G. Domes, 1964. A study of the Land in South-Western
Gils, H. van and I.S. Zonneveld, 1982. Vegetation and Rangeland. ITC Textbook,
Goosen, D., 1967. Aerial Photo-interpretation in Soil Survey. FA0 Soils
Strahler, A.N., 1969. Physical Geography. John Wiley & Sons, Inc.: pp. 1-733. Vink, A.P.A. 1964. Aerial Photographs and the Soil Sciences. Proc. of the
Toulouse Conf. on Aerial Surveys and Integrated Studies: pp. 81-141. Zuidam, R.A. van, Zuidam-Cancelado, F.I. van, 1978-1979. Terrain Analysis and
Classification using Aerial Photographs. A Geomorphological Approach. I.T.C. Textbook of Photo-Interpretation vol. VII, Chapter 6: 310 pp.
Victoria. Soil Conservation Authority. Victoria. Australia: pp. 13-289.
in press (The Netherlands, ITC Enschede).
Bulletin no. 6: pp. 1-55.
8.11. Additional reading.
Barrett, E.C. and L.F. Curtis, 1976. Introduction to environmental remote
Howard, J.A., 1970. Aerial Photo-Ecology. Faber and Faber, London: 325 pp. Lillesand, T.M. and R.W. Kiefer, 1979. Remote sensing and image
interpretation. John Wiley & Sons, New York: pp. 1-612. Zonneveld, I.S., 1975. Methodology and Techniques of Survey of Natural and
Semi-natural Vegetation using Aerial Photographs and Other Remote Sensing Means. Lecture Notes I.T.C. no 8: 136 pp.
Verstappen, H.Th., 1977. Remote Sensing in Geomorphology. Elsevier Scientific Publ. Cy, Amsterdam: 214 pp.
White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press. Oxford pp. 1-104.
sensing. Chapman and Hall, London: pp. 1-336.
211
9. INTERPRETATION OF AIRPHOTOS FOR SOIL MAPPING AND LAND EVALUATION
Airphoto-interpretation is the common aid for soil mapping. In aerial
photography, there is no limitation for scale. Aerial photography not only
offers information on relief and slope but also makes a lot of other applica-
tions possible. However, because of changing weather conditions and cloud
cover, the number of flight days is usually limited, and a repetitive coverage
throughout the year is generally no t economic.
The spectral resolution is limited to the range between 0.12 pm and 0.9 pm,
which is Ultraviolet, Visible and Near Infrared. Aerial photography generally
operates in the Visible zone, but more and more application is found of Near
Infrared sensitive films e.g. Black- and White-Infrared and False Colour. For
the different aspects on aerial photography and physiographic interpretation,
the reader is also referred to the preceding chapters 4 up to and including 8.
Plants are strong reflectors of Near Infrared, and different vegetation
cover types often show a different reflectance. Good results can be mentioned
with regard to the use of false colour-film in agricultural and ecological
studies, in differentiating between vegetation cover types, and in locating
vegetation areas affected by disease.
Due to its successful application, airphoto-interpretation has become a
generally accepted aid for soil survey during the past thirty years. An
evaluation of various remote sensing techniques in northern Canada, taking into
account visual interpretation together with computerized classification of
remotely sensed data, revealed that airphoto-interpretation provided the best
cost and data-effective method for ecological land classification. Mapping of
soils, landforms and landtypes was best accomplished with the aid of airphotos.
It was suggested that other remote sensing means should be used in a
complementary way (Thie, 1976). However, SPOT-data are competitive with
airphotos for medium-scale mapping.
9.1. Interpretation of black- and- white airphotos.
Black- and white-airphotos are the most common tools in soil survey and
the soil surveyor should be trained in making deductions about soil conditions
through physiographic and morphogenetic interpretation. Black- and white-
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photography is normally cost-effective in soil survey projects, provided that
there are no serious limitations in obtaining flight coverage. The general
feature of aerial photography in offering low-cost stereoscopy, is one of its
most important advantages. Another aspect is the grey tone structure that is
more friendly to the Observer than colour tones are. Especially the red and
magenta colours that dominate most of the false colour imagery may fatigue the
observer.
Examples of airphoto-interpretation of areas in Suriname and bnia are
given in figures 9.1 to 9.4. It should be emphasized that in the examples a
selection of aspects has taken place.
The Suriname and Kenia areas have a mean annual rainfall of 2250 and 1550 mm
respectively, and are representative of tropical areas with land use of
respectively low and high intensity. The Suriname area (Fig. 9.1), initially
photographed at a scale of 1:40,000, may be studied using the aspects
landtype/relief, land use/parcelling - natural vegetation, and drainage
condition. The pictured area is an example of the Young Coastal Plain
landscape, which shows in most of the area natural vegetation, since land use
is of low intensity (shifting cultivation is almost absent). Drainage
condition is concluded from site, land use and natural vegetation. A soil map
(Mulders, 1977) is given in Fig. 9.2
Legend Fig. 9.2 Soil Map Northern Suriname (original scale 1:100.000): YOUNG COASTAL PLAIN 4) Poorly drained half-ripe and ripe clay; 8) Well drained medium and fine sand; 9) 11) Poorly and very poorly drained nearly ripe clay; 16) Very poorly drained half-ripe (peaty) clay; 17) (Formerly) artificially drained ripe clay; 19)
Imperfectly drained sandy loam OK medium and fine sand;
Very poorly drained half-ripe and unripe mostly pyritic clay and peat;
Three landtypes can be distinguished, these being: the Beach Ridge Complex (8,
9 and l l ) , the Swamp and Marsh ( 4 , 16 and 19) and the River Flat ( 1 7 ) .
The different units have specific characteristics on the photographs of which
natural vegetation is the most important.
The Beach ridges (8) are characterized by high trees outstanding above a
canopy with moderately high trees. Often the ridges can be recognized by the
linear arrangement of these high trees. Where the ridges are close to each
other and relatively narrow, complexes are distinguished.
Between these, depressions are found with moderately high forest and
213
imperfectly drained soils (9). On other places, where the canopy in the Beach
Ridge Complex shows grass and low trees, soils are poorly to very poorly
drained (11). The Swamp and Marsh shows a unit with grass and moderate to high
coverage by low trees which contains very poorly drained mostly pyritic clay
and peat (19). During a transgression, clays are deposited in the depressions
which now bear an extremely low tree coverage (4), or low tree coverage in the
actual drainage ways (16).
The River Flat (17) was formerly used for plantations. Some of these are now
used again for agriculture, others are not, and have low to moderately high
forest.
The area in Kenia (Fig. 9.3) is initially photographed at a scale of 1:12.500
and may be studied by using the aspects of landtype/relief (Fig. 9.4a), slope,
site and land use/natural vegetation (fig. 9.4b). The present scale enables a
subdivision in landtypes-relief, and when combined with land use/natural
vegetation a relation to soil condition is accomplished. The results of the
interpretation can be compared with the soil map of the area (fig. 9.4).
Legend Landtypes - Relief (Fig. 9.4a): A. Upland ridge complex, mainly elongated: steeply dissected (As) and hilly
(Ah) B. Upland hills: rolling to hilly C. Undulating plain.
Legend (Fig. 9.4b):
Land use Natural vegetation
A. Agricultural use: Extr. low cov. trees annual herbaceous crops, and scrubs; low- pastoralism, mod. COV. grass. some woody crops.
P. Pastoralism. Very low - low COV. trees and scrubs; high COV. grass.
N. Nature reserve Very high COV. scrubs. F. Timber, firewood. Riverside forest; mod. COV. trees.
Abbreviations: extr. = extremely; mod. = moderate; COV. = coverage.
Legend soil map (Fig. 9.4~): C Chromic Luvisols and Luvic Phaeozems G Gleyic Luvisols and Gleyic Phaeozems S Solodic Planosols E Eutric and Chromic Cambisols, Haplic Phaeozems R Eutric Regosol (lithic phase)
Fig. 9.1 Airphoto Stereotriplet of an area in the Young Coastal Plain near Groningen at the Saramacca river
(Suriname).
215
Reconnaissance S o i l Map o f Nor thern Suriname
n o r t h o f t h e 5 t h degree o f l a t i t u d e
e 1 km
Fig. 9.2 S o i l map of t h e area nea r Groningen (Suriname, Map shee t 13). For
legend: s e e t e x t .
The a c t u a l s c a l e of t h e photographs i n Fig. 9.3 only enab le s a subd iv i s ion i n
r e l i e f , t h e s l o p e and s i t e u n i t s be ing too small. Although t h i s produces a
r a t h e r broad s u b d i v i s i o n of t h e l and , t h e i n t e r p r e t a t i o n on l and types and
r e l i e f (Fig. 9.4a) shows a number of u n i t s which a l s o may be recognized on t h e
s o i l map (F ig . 9 . 4 ~ ) .
I n a number of c a s e s , n a t u r a l v e g e t a t i o n and land use provide f o r f u r t h e r
ev idence on s o i l cond i t ions . Compare F of Fig. 9.4b wi th G of Fig. 9.4c, and
n o t e t h a t R s o i l s a r e mainly used f o r p a s t o r a l i s m (and n a t u r e r e s e r v e ) .
The comparison wi th t h e s o i l maps shows t h a t a c l o s e r e l a t i o n between t h e
combined a s p e c t i n t e r p r e t a t i o n maps and t h e so i l . map can be accomplished.
Normally t h e l and type is t h e main c r i t e r i o n f o r d e s c r i p t i o n i n t he legend of
t h e i n t e r p r e t a t i o n map, and a f u r t h e r s u b d i v i s i o n may be made on t h e b a s i s of
Fig. 9.3 Airphoto Stereotriplet of an area near Rangwe (Kisii, Kenya).
217
I n ? r p r e t a 1 a n d t w e s
ion
and r i i i e f
N e
1 k m
I n t e r p r e t a t i o n l a n d use and na t u r a 1 vegeta t i on
1 k m
218
Soil Map
1 km - Fig. 9 . 4 Interpretation and soil map of the Rangwe area (Kisii, Kenya, Top.
map 130/1) a. Interpretation landtypes and relief b. Interpretation landuse and natural vegetation C. Soil map (Breimer, 1976)
other aspects. Examples of legends are given in par. 9.2.
Although qualitative methods are most relevant for soil surveys, quantitative
methods may assist the interpretation and may optimize the use of the infor-
mation content of the airphotos. One of the features to digitize is the tonal
variation. Digitization of the density range on the film is done by using a
computer, the output codes from the digitizer are recorded and stored for
subsequent retrieval and analysis. By using a colour television monitor,
colour can be designated to certain grey levels to facilitate the
interpretation of the images obtained. Benson et al. (1973) used computerized
methods for a detailed study of a fallow field in South Dakota in order to
separate eroded and non-eroded soils. In this study statistical analysis were
used to determine the relationship between soil properties and the tonal
variations on the airphotos. The results indicate that the tonal variation
219
evident on the photographs of the field is related to several soil properties.
The eroded terrain shows light tones due to increased reflectivity of the
surface soil after removal of the A horizon and exposure of the underlying
calcareous parent material. The computerized method may be valuable, for
instance, when multitemporal data have to be studied to detect the progress of
erosion over a certain period of time.
9.2. The legend of the airphoto-interpretation map
A grouping of airphoto-interpretation units may be done as follows:
A, B , C, etc. landtype in morphogenetic terms OK physiographic indicat-
ions such as relief classes and drainage density or
pattern;
A1, A2, B1 etc. physiographic subdivision;
A l l , A12, B l l , etc. phases, minor differences.
When the structure is very complex, additional codes may be applied for a.0.
slope, natural vegetation, land use, phototone or mottling of bare surfaces.
The following features may be indicated: grade OK density, type or shape,
size, regularity and site sequence.
Slope classes provide examples of grade, e.g. classes 1-6. For surface density
or coverage classes, the reader is referred to par. 8.5. (see also par. 6 . 3 :
texture and structure). These low-level codes can be read on the map. The
legend does not show the total number of mapping units as they are delineated
on the map, but insight in the properties of the mapping units can be given
separately.
Examples I and I1 of airphoto-interpretation legends for reconnaissance
survey are given below. The following remarks are made in connection with
these examples.
Different landscapes may need different approaches. In arid areas
attention will be centred on relief, drainage pattern and phototone, while in
areas with tropical rain forest (and low human activity) relief, drainage
pattern and natural vegetation are diagnostic for the distribution of soils.
Furthermore, each study has its own requirements, e.g. erosion studies and
land evaluation need special emphasis on slope and land use.
The level of detail is determined strongly by the scale of the airphotos
220
as well as by the physiognomy of the area. The examples are only meant as a
basis for discussion. It is stressed that the legend of the airphoto-
interpretation map needs much emphasis, and that discussions with team members
may improve it considerably. A s far as soil survey is concerned, the lowest
level should clearly present the soil mapping unit, while the higher levels
have their special value for land division. In semi-detailed surveys, the
lowest level in accidented terrain will most often be based on slope
characteristics.
While a number of aspects are presented in the legend on the map, a separate
description is usually given of other aspects which are not used for
discrimination between the mapping units. This description is given in columns
(tables).
The following requirements are suggested for legends of airphoto-
interpretation maps:
a. the units should be ordered logically, e.g. old to young, high to low
elevation, high to low percentage of slope;
b. high levels generally indicate land types with geographic soil
associations;
C. low levels generally indicate soil series or toposequences of soils (soil
catenas); in other cases, the lowest level is a subdivison made up by
photo-technical description (grey tone or mottling), of which the
significance has to be studied in the field;
d. since morphogenetic terms (e.g. floodplains, levees or dunes) offer more
information about soil conditions, these terms are preferred to physio-
graphic terms (based on features such as slope and relief).
ad a. Proposal for arrangement of aspects and grade or density in the legends: morphography and landtype - land system (or type) - land unit - land component or
- land system - relief - slope, - drainage density/high to low, - high to low elevation, - relief/steeply dissected to flat,
vegetation/forest - grass - bare,
site,
other aspects -
coverage/high to low, structure and texture/coarse to fine,
agricultural use - settlement and infrastructure - water, - land use/nature reserve - forestry - rangeland - - phot ot one /light to dark.
221
EXAMPLE I
Legend of airphoto-interpretation map of the Kilifi-area (Kenya). Scale of panchromatic airphotos 1:50 000. A Relatively high interior upland
Very low to low drainage intensity A1 Rolling land with dendritic drainage pattern
All Open woodland savannah A12 A13
A21 Open woodland savannah
A31 Open woodland savannah A32 Open woodland savannah with up to 50% grazing A33
Open woodland savannah with up to 50% grazing Open woodland savannah with 50-80% grazing
A2 "Kopjes" land (small isolated bare hills)
A3 Undulating land with dendritic drainage pattern
Open woodland savannah with 50-80% grazing A4 Rivervalley land
B Relatively low interior upland B1 Moderate drainage density
B11 Hilly land with subparallel drainage pattern B12 Rolling land with dendritic drainage pattern
Further subdivision on natural vegetation and land use R2 Low drainage density
B21 Rolling land with dendritic drainage pattern B22 Undulating land with dendritic drainage pattern
B3 Rivervalley land Further subdivision on natural vegetation and land use
C Coastal upland C1 High drainage density
C11 Rolling land with dendritic drainage pattern C12 Rolling land with pinnate drainage pattern
C21 Hilly land with subparallel drainage pattern C22 C23 Rolling land with dendritic drainage pattern C24 Undulating land with dendritic drainage pattern
C31 C32 Undulating land with subparallel drainage pattern C33
C2 Moderate drainage density
Rolling land with subparallel drainage pattern
C3 Low drainage density Rolling land with subparallel drainage pattern
Undulating land with dendritic drainage pattern C4 Rivervalley land
Very low to low drainage density D1 Relatively high undulating land
D11 High marine terrace D12 Medium marine terrace D13 Low marine terrace
D Coastal plain and marine terraces
D2 Beach area D3 Estuarine land D4 Tidal creek land
D41 Saline margin D42 Overflow area
followed by deduction on inferred aspects is not included. Note: The description in tables of other interpreted land characteristics
222
EXAMPLE I1
Legend of airphoto-interpretation map of the Antelope Valley Area (California). Scale of panchromatic airphotos 1:24,000.
Landtypes and Other aspects subdivision
Drainage Drainage Vegetation and (Inferred) density pattern land use drainage
condition
A Low mountaneous land A1 High undulating
plateus A2 Steep slopes
A3 Hilly land
A4 Rolling to hilly
land A5 Low, undulating
to rolling land
B Plains B1 Sloping foot-
slopes B2 Gently sloping
alluvial fans
B3 Flat to gently
sloping plain
B4 Flat to gently sloping
depressions
very low dendritic grass and herbs
or bare
grass and herbs
or bare
high parallel trees, shrubs,
high dendritic trees and shrubs
moderate dendritic grass and herbs
or bare low dendritic grass and herbs,
shrubs or bare
moderate parallel and grass and herbs
dendri tic high dichotomic grass and herbs,
bare or arable land
very low dendritic arable land,
grass and herbs or bare
locally grass and herbs diffuse or arable land
-
gully pattern
well drained
excessively drained somewhat excessively drained well drained
well drained
well drained
well drained
well drained
moderately well drained
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9.3. From airphoto-interpretation map to soil map
A soil survey comprises the delineation of soil bodies. This is done by the
study of soil profiles. A soil profile is a sample of a pedon, the smallest
unit of soil. In practice, one uses polypedons, which comprise a number of
pedons with a natural boundary. The polypedon, or natural soil body, may be
homogeneous or composite with regard to soil classes or series.
The units of the airphoto-interpretation map often correspond to natural and
composite soil bodies. Morphogenetic units offer much information about soils,
while physiographic units at least offer information about soil-forming
factors or consequences of soil conditions. The airphoto-interpretation may be
done before. fieldwork or interactively. In both cases, however, the airphotos
have to be interpreted in order to plan the field survey. Bennema and Gelens
(1969) have treated the procedures for soil mapping with the aid of airphotos.
These procedures are summarized below.
The boundaries on the airphoto-interpretation map may be:
- valid for soil survey; - invalid for soil survey, since they present vegetation differences due to
tillage, or envelop units which are too small for the scale of mapping;
- of questionable validity for soil survey; fieldwork is necessary to evaluate
the validity.
Fieldwork enables the compilation of a soil map. It involves the following
activities:
a. check on validity of boundaries;
b. check on accuracy of boundaries;
C. detection of missed boundaries;
d. delineation of boundaries not visible on the airphoto;
e. set-up of legend;
f. profile observations for description and classification of soil.
Skill is required to choose the right location of the field observations.
Their position is related to soil genesis and physiography. One observation
may lead to a hypothesis about the kind of soil to be expected at another
place. The second or third observation may verify the hypothesis or disprove
it. However, when work is getting on, the position of the various soils,
224
generally a repeated sequence in a landscape unit, is no longer a secret and
consequently the density of the observation network generally decreases with
time up to the standard minimum number of observations as guided by the
publication scale.
Procedures of fieldwork with regard to validity and accuracy of
boundaries are the following:
- full check on validity and accuracy of boundaries; - limited check, that is a check only on validity of questionable boundaries;
- no check on validity and accuracy of boundaries. The check on validity and accuracy is related to scale as follows:
- large-scale - full check; - medium-scale - full or limited check; - small-scale - limited or no check.
The total number of observations depends, apart from skill and knowledge
of the surveyor, also on:
- the scale and purpose of the survey; - the scale and quality of the airphotos;
- the kind of landscape. Often selected areas are studied in detail in order to obtain insight in
the kind and distribution of soil bodies. These areas are called key areas or
sample areas. The study of sample areas is usually recommended, but their use
is limited for:
a. relatively small areas;
b. well-known landscapes;
C. detailed surveys;
d. very small scales (e.g. 1:250,000 and smaller).
The requirements for sample areas are:
a. they should be samples of large areas with different mapping units, which
means that they should include many soil units;
b. they should be well accessible;
C. there is a need for more than one sample area for large units.
Procedures with sample areas:
- selection of sample areas by indication of major landscape units in
airphoto-interpretation;
- detailed airphoto-interpretation of sample areas (indication of land
225
components);
- survey of sample areas; - airphoto-interpretation of total area;
- check on validity and accuracy in total area. A revision of the airphoto-interpretation of the total area is usually
necessary due to evidence from field observations.
Tropical forests are almost inaccessible and consequently need specific
methods for soil mapping. Field observations are done in transects and in
sample areas which have a relative dense network of transects. Soil mapping
boundaries are drawn by interpolation between the transects and by
extrapolation outward from the areas with transects. It is important to
realize that remote sensing images, including airphotos, are the only tools
for mapping in tropical forests. Often the remote sensing tool determines the
possible detail. That is, when the interpretation units have shown their
validity as indicators of soil units, the soil surveyor often has only the
opportunity to map and describe the contents of these interpretation units.
This implies that the final map may comprise homogeneous units as well as
heterogeneous units (soil complexes). This statement is made, since the
delineation of boundaries not visible on the remote sensing imagery, generally
requires much field work and thus time and financial means, which may be out
of the scope of the project.
S o i l variability may be studied in the field by statistical methods (see:
Webster, 1977; Northcliff, 1978; Burrough and Kool, 1981).
An example of a possible soil survey using modern techniques like the statis-
tical approach i n conjunction with airphoto-interpretation is the following.
O n the basis of the airphoto-interpretation, mapping units are selected which
show a trend in geographical distribution; these units are studied in detail
either by transects or by sample areas. The variability within the units and
between the units is analysed statistically, in order to check the validity of
the discriminating criteria used to delineate the boundaries between the
mapping units as well as the variation within the units. This might give an
indication of the validity of the mapping units and may offer an indication of
the number of observations necessary to map the units accurately. The
statistical approach is particularly useful in case of large mapping units,
which appear on the interpretation map as homogeneous units on the basis of
226
the criteria used. In the field, sampling together with statistical analysis
might reveal diagnostic soil characteristics, which can be used for a further
subdivison into soil units as well as for description of soil complexes, and,
as stated before, to direct the number of field observations needed for an
accurate description of the mapping units.
The legend of the airphoto-interpretation map has to be transformed into
a legend for the soil map. This can be done by a translation of physiography
and morphography into morphogenesis followed by indication of soil taxonomic
units.
There are two types of soil map legends:
a.physiography and morphogenesis at high level (e.g. river levees soils,
soils of the rolling uplands), followed by taxonomic units, such as soil
series (or higher levels) and phases, the latter generally pragmatic (land use
directed) ;
b.taxonomic units, e.g. orders, suborders, great groups, etc.; associated
soils should be indicated too.
9.4. Land evaluation and planning of field survey
A fundamental approach to land evaluation has been defined in its initial
stage by Beek and Bennema in 1971, and on the Expert Consultation of Land
Evaluation for Rural Puposes at Wageningen (The Netherlands) in October 1972
(Brinkman and Smyth ed., 1973). The first draft of a framework by FA0 (1973)
was widely circulated with a request for comments. This resulted in 1976 in "A
Framework for Land Evaluation".
Land evaluation involves the execution and interpretation of basic
surveys of climate, soil, vegetation and other aspects of land in terms of the
requirements of kinds of land use or LUTS. To be of value for planning, the
LUTS to be considered have to be limited to those which are relevant within
the physical, economic and social context of the area and its population.
Interpretation of remote sensing imagery gives information on soils,
vegetation, present land use, and to a limited degree on climatic conditions.
Also the physical effects of economic and social factors may be visible to
some extent. Their information content and synoptic view cause remote sensing
data to be important aids in land evaluation. A preliminary evaluation based
221
on interpretation results of remote sensing data may be considerably helpful
in the planning. Airphoto-interpretation is applicable for delineation of land
mapping units being characterized by basic, compound and inferred aspects.
These aspects are in fact land characteristics. The ultimate estimation of the
grade of land qualities is only possible after a proper weighing of the land
characteristics that influence the land qualities.
In using such interpreted land characteristics and expected land
qualities and suitability, it has to be kept in mind, that it is only an
interpretation, being of value for the planning of field survey. The best
score will be obtained in S 1 (highly suitable) and N (not suitable) classes.
Field and laboratory data are decisive for the final suitability but the
preliminary interpretation may direct the field survey to areas that are
expected to be suitable for the intended use already at an early stage of the
survey.
Some land characteristics such as relief grade, slope grade, slope
length, site and drainage density may well be estimated by aerial photo-
interpretation and may direct the field survey to the most promising areas.
Inferred interpretation aspects are of considerable value. Each of them
requires a specific approach in deduction. As an example, the erosion
condition is discussed.
The methodology of airphoto-interpretation for erosion and soil
conservation survey is comparable with that for soil survey. However, special
emphasis is laid upon aspects, such as:
- relief and slope (angle, shape, length and position); drainage pattern
and density;
- erosion features; location of severely eroded land 8.0. badland;
- grey tone pattern;
- microrelief and surface stoniness;
- site a.0. relative position of accumulation and erosion surfaces;
- land use and crops, parcelling;
- percentage of vegetation cover;
- percentage o f fallow land and abandoned arable land;
- cattle tracks;
- size-, shape- and position of man-made terraces and other conservation
228
measures.
Examples of soil erosion-accumulation sequences based on grey tone pattern on
airphotos from top- slope- valley bottom (Bergsma, 1974) are:
- the common case dark - light - dark, where the A - horizon on the slopes
is largely eroded and a lighter s u b s o i l is exposed;
- the reverse case light - dark - light, where a light textured surface soil on the slopes is largely eroded and a heavier subsoil (e.g. an
argillic horizon) is exposed.
It will be clear, that the appearance of the area itself, and scale of
the airphotos determine to a large extend the potential of the interpretation.
Furthermore, the information level in the form of maps and reports on
environmental conditions has also much impact.
However, it is important that at the start of the interpretation procedures
the final aim of the project is considered.
The purpose of the survey determines a.0.:
- the minimum area of planning interest;
- the kind of environmental data to be collected;
- the required survey scale.
The latter also depends on existing base maps and other environmental data.
For practical reasons, the working or survey scale is in general larger e.g.
twice the scale intended for the final maps.
For planning of the field survey, three land qualities are important, these
being:
- the size, distribution and arrangement of mapping units or the land
complexity;
- the trafficability expressed by relief, drainage condition and the
presence of roads and tracks, navigable rivers and streams;
- the accessibility of the terrain expressed by type and degree of
vegetation cover and the possibility of housing and/or campsites.
The land complexity is scale dependent. Land may appear homogeneous at large
scales, but heterogeneous at small scales. A measure for land complexity is
the size of the land component or the mapping unit at the lowest level (e.g.
All, A12). If the size of the components is dominantly smaller than 1 cm2, the
land is considered to be heterogeneous at the particular scale and an
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observation density is suggested of at least 2 augerings per cm2 (final map).
Table 9.1. presents estimates of the daily number of auger observations (Nt),
and progress by soil augering in ideal terrain, which is homogeneous at scales
larger than 1:100.000, having slopes not steeper than 16 % and a tree and
shrub coverage of less than 25 %.
This table is based on the following assumptions:
- When there is a check on accuracy, the following reduction factors have to
be applied i n order to calculate the number of augerings contributing to
the daily progress,
0.75 for 1:5000 scale, full check;
0.70 for 1:10.000 scale, full check;
0.85 for 1:ZO.OOO scale, limited check;
0.80 for 1:50.000 scale, limited check;
- the land is considered to be heterogeneous at scales of 1:lOO.OOO and
smaller (Np = Nt);
- at scales of 1:lOO.OOO and smaller, no check on accuracy is performed, but
more time is spent on transport and desk work.
The number of survey team days can be calculated by dividing the total surface
area by the daily progress.
In addition, the terrain characteristics have to be evaluated to obtain
correct estimates for the land under consideration.
The following classes of trafficability are suggested:
a) well drained flat, undulating to rolling terrain; effective transport by
vehicles is possible in the field;
b) as for (a); no effective use of vehicles; main transport on foot;
c) well drained, or excessively drained hilly to steeply dissected terrain;
use of vehicles is moderately effective;
d) as for (c), but no effective use of vehicles; transport on foot;
e) excessively drained mountainous terrain OL poorly drained terrain; no
effective use of vehicles; transport on foot.
N 0
Table 9.1 Approximation of d a i l y p rogres s i n i d e a l t e r r a i n us ing e s t i m a t e s of d a i l y t r a n s p o r t , d a i l y deskwork and auge r ings /h r ( 6 f o r 1: 5.000 s c a l e , 5,9 f o r o t h e r s c a l e s ) .
Kind of survey range of scales scale a r e a survey method average average average d a i l y average 1 cm2 t i m e per t ime per number of auger d a i l y map (S) day spen t day spen t obse rva t ions (N) p rogres s
a t t ran- a t desk N t Na Np s p o r t work area (P)
s u r f a c e
7.25 ha 39 10 29 d e t a i l e d 1:10,000 and 1:5,000 0.25 ha r e g u l a r g r i d 1 / 2 h r 1 h r l a r g e r 1:10,000 1 ha o r f r e e g r i d
d i r e c t e d by physiography; i n t e r p o l a t i o n and f u l l check on accuracy
semi-de ta i led smaller than 1.20,OOO 4.0 ha f r e e g r i d of 1 h r 1 : 10,000 t r a n s e c t s up t o d i r e c t e d by 1 :25,000 physiography;
i n t e r p o l a t i o n and l i m i t e d check on accuracy
14 hr 32 5 27
reconnaissance smaller than 1:50,000 25.0 ha key a r e a s and 1 1 /4hr 1 3/4 h r 30 6 24
medium i n t e n s i t y up t o ex t r a -po la t ion , 1 : 25,000 1:100,000 1 km2 t r a n s e c t s ; 14 h r 2 1/4 h r 25 - 12
1 : 100,000 no check on accuracy
108 ha
600 ha 12 km2
40 km2 21 - 10 reconnaissance smaller than 1:200,000 4 km2 as f o r 1 3/4 h r 2 j hr 1 : 100,000 1: 100.000
low i n t e n s i t y up t o 1: 250,000 -
Nt = N t o t a l , N a = N accuracy check, Np = N p rogres s = Nt - N,
231
The following classes of accessability are suggested, based on vegetation
cover:
A) tree and shrub coverage 0 - 25 X, B) tree and shrub coverage 25 - 75 X, C) tree and shrub coverage 75 - 100 %.
Reduction factors on the average daily number of auger observations have to be
applied for trafficability and accessibility in relation to scale. The
following factors are suggested:
for scales of 1:lO.OOO and larger
trafficability c 0.90 accessibility B 0.90
d 0.85 C 0.85
e 0.80
for scales smaller than 1:lO.OOO same reduction factors, but in addition for
transportability or the use of vehicles in the field, these factors being:
b 0.90 d + e 0.85
Table 9.2. gives a summary on terrain classes and reduction factors. Of
course, further testing on the reduction factors is necessary and ought to be
done according to the specific conditions in land or country.
Table 9.2 Terrain classes and reduction factors on average daily number of auger observations and average daily progress.
terrain trafficability accessibility reduction factors on number classes average daily of auger observations and
daily progress 1 : 10.000 smaller and than larger 1 : 10.000
1 a A 2 a B 0.90 0.90 3 a C 0.85 0.85 4 b A - 0.90 5 b B 0.90 0.81 6 b C 0.85 0.77 7 C A 0.90 0.90 8 C B 0.81 0.81 9 C C 0.77 0.77 10 d A 0.85 0.72 11 d B 0.76 0.65 12 d C 0.77 0.61 13 e A 0.80 0.68 14 e B 0.72 0.61 15 e C 0.68 0.58
- -
Through application of the reduction factors it is then possible to calculate
232
the daily number of auger observations and the corresponding daily progress,
which are both dependent on the terrain characteristics. The calculation
suggested is based on ideal climatic conditions or in other words, a dry
season. When the field work is carried out in a wet season, another reduction
factor should be applied e.g. 0.7 or 0.8.
The following formula may be used to calculate Np for terrain class x (or
Npx) :
Npx = c.s.zx.Npl (9 - 1)
where Npl is Np for ideal terrain class 1 (see table 9.1), and
- c = reduction factor land complexity (heterogeneous terrain 0.5, homogeneous
terrain 1; in table 9.1, c is applied for 1:100.000 and 1:200.000);
- s =reduction factor for climatic conditions, wet season 0.7 or 0.8, dry
season 1;
- Zx= reduction factor for terrain class x (see table 9.2). The average daily progress in ha or km2 ( P ) can be calculated from:
P = Npx . S (9 - 2)
where S = area 1 cmL map (ha or kmL) at scale of publication.
Besides for auger observations, days have to be included for field work
in connection with:
- preparation and detailed examination of soil pits (depth 1.5 - 2.0 m or to
an impenetrable layer); average 2/day,
- deep borings ( 3 - 5 m or to an impenetrable layer) in a free grid or
preferably along transects in order to obtain insight in soil depth, parent
material and in sedimentology.
Soil samples for laboratory analysis are usually taken from
characteristic soil pits (typical soil profiles) throughout the area and if
applicable from the key or sample areas.
Sampling is done from soil horizons and/or stratifications or at regular
intervals in the soil profile. In special cases, a relatively large number of
samples is taken for limited laboratory analysis, often at fixed sampling
depths e.g. for estimation of salinity and/or alkalinity. Depending on the
type of survey and the information required, certain field experiments (like
233
measurements of permeability and infiltration rate and conductivity) are to be
executed as well. The amount of time involved in laboratory analysis varies
greatly with the type of analysis (soil chemical, soil physical and OK
mineralogical) and of course the size and quality of the laboratory to which
the samples are forwarded. An estimate of the rate of progress for soil sample
analysis has to be made in consultation with the laboratory.
Geostatistical approaches (non-aligned sampling OK detailed along transects)
may be used to determine soil variability and discriminating criteria between
soil units.
As stated before, the purpose of study may direct and concentrate the
observations on the more "promising" parts of the area. Consequently, some land
units may be studied in less detail than the rest of the area, and estimates
for smaller scale may be used to calculate the work involved. Such differences
in survey intensity have to be indicated on the map and in the report. A
checklist on the planning of soil survey is given in table 9.3 .
Table 9 . 3 Checklist on the planning of soil survey.
I
I1
111
IV
survey team days
Organization and Administration
Preliminary airphoto-interpretation mapping units: A, B , C, etc. complexity: trafficability: accessibility: housing, campsite: transport in field:
Purpose of field survey: areas of high interest: minimum area of planning interest: kind of environmental data to be collected: required final scale: working scale: basic field equipment for soil sampling, soil description and mapping:
Field survey expected weather conditions in survey-period: observation system(s): surface areas of land units: number of man days involved: - for geostatistical observation: - item for deep augering:
234
V
VI
VII
VIII
- item for soil pits: - item for routine augering per land unit: - delay due to social or religious aspects:
Survey team days for other observations directed by the purpose of study other observations:
Final airphoto-interpretation
Laboratory analysis - samples of soil pits - other samples
Preparation of maps and report - soil scientific work: - typing: - drawing: - other activities
man-days
The data listed in table 9.3 enable the production of a time-schedule for
the soil survey.
A final evaluation involves a calculation of cost of the survey. The attempt
for planning of field survey, needs further application. Good results were
obtained using this method in recalculation of man-days needed for medium and
small-scale soil surveys in Suriname and Pakistan.
A soil map should always be accompanied by a report. An example of the contents
of a soil survey report, which may comprise the following subjects, is given
below:
1) Introduction. Purpose of study Location of the area
Topographic maps Geological maps Data airphotos: scale, flying height, focal distance, aerial film and
Methods of interpretation and fieldwork
Climate Geology, geomorphology, petrology Hydrology Natural vegetation and land use
Relation between soils and soil forming factors Relation of photo-interpretation aspects with s o i l conditions Construction of legend
2) Material and methods.
camera, filters
3) General information on soil forming factors in the study area.
4 ) Airphoto-interpretation and fieldwork.
235
5) Soil data and classification. Description of soil mapping units Soil profile description, laboratory analyses and soil classification Soil variability
Socio-economic considerations Selection and requirements of land utilization types Rating of land qualities Estimation of land suitability classes for land utilization types
6) Land evaluation.
7) Summary. 8 ) References.
9.5. Interpretation of true colour airphotos.
Despite early relatively successful use of aerial colour film, it was only
in the latter half of the sixties that serious attention has been given to
their potentiality. This was primarily due to the insufficient speed and low
resolution of the earlier films. Also the high cost and doubt about the value
for interpretation played a part. It is argued by those who are in favour of
colour photography, that the limited resolution of colour photography when
compared with panchromatic photography, is offset by the higher resolution of
colours. With colours, an accurate distinction between tones is possible to a
degree that is 600 times to 2000 times greater than the distinction in grey
tones (Myers, 1968). The value of colour photography for discrimination between
objects, therefore, is beyond any doubt (for d'iscrimination between different
high chroma soils, the reader is referred to Gerbermann et al., 1971). Although
colour fidelity may be low, it is not a limiting factor in the identification
of terrain information (Anson, 1968). Landform analyses can be usefully
supplemented by photometric information extracted from colour imagery, such as
the ratio Red/Blue revealing differences between soils. For details, the reader
is referred to Piech and Walker (1974).
9.6. Interpretation of black-and-white Infrared airphotos.
Generally, the black-and-white Infrared films offer a good discrimination
between various types of natural vegetation and may emphasize differences in
soil moisture conditions. Since the cost of black-and-white Infrared photo-
graphy is nearly equal to that of panchromatic photography, the application of
this type of film is increasing in tropical forest areas, especially when large
areas are concerned.
236
De la Souchere (1966) compared panchromatic films with black- and -white
Infrared films in order to find new criteria for delineation of different types
of forest in Ctite-d' Ivoire. Small-scale mosaics (1:200.000) of black- and
-white Infrared photographs appeared to be a good aid in comparing the
contrasts in Infrared reflection of different types of forest. However, in
Ctite-d'Ivoire the differences between panchromatic and black- and -white
Infrared as a detecting agent, were found to be variable from one region to the
other.
At large scale (e.g. 1:3,000), individual crowns of trees are visible and the
studies may be directed to crown damage (Wolff, 1966).
Another application of black- and -white Infrared photography may be found
in detecting areas affected by salinity. The crops (e.g. cotton) affected by
salinity will show a lower reflectance when compared with healthy crops.
However, problems may arise in discriminating between the surface soils and the
plants, through which the interpretation may become difficult.
Fig. 9.5 enables us to make a comparison between a panchromatic and a
black- and -white Infrared aerial photograph of an area at the Surinam river.
The panchromatic airphoto was taken in 1953. The black- and -white infrared
airphoto was acquired 22 years later when an oilpalm plantation had been
founded. Both images show the effect of shifting cultivation. The black- and
white -Infrared photograph ha6 high contrast and clearly shows vegetation
differences. The dark spots in the plantation may point to places with a moist
soil surface.
9.7. Interpretation of false colour airphotos.
The first application of the false colour-film took place in World War I1
when it was used as a detection film for camouflaged military objects. The film
is applicable from high altitudes (e.g. 9 km) enabling scales of 1:60.000 up to
1:lOO.OOO. Owing to the recording of green, red and near Infrared radiation,
the potential of this film for discrimination between soils and vegetation is
high. Plants frequently are good indicators of soil condition. Therefore, in
case of soils covered by vegetation, the soil scientist has equal interest in
detection capability of this film when compared with agricultural and forestry
experts. In section 4.2, the formation of colours in the colour Infrared film
is treated. Below, false colours are discussed briefly.
231
Fig. 9.5. Panchromatic airphoto (a) and black- and -white Infrared airphoto (b) of the Victoria area at the Surinam river (courtesy CBL Surinam).
238
Dry soils appear in light blue, or light green, and in the case of high
organic matter content, in grey colour on this film, while wet soils appear in
dark tones. However, grass and healthy broadleaved vegetation are pictured in
red to magenta and conifers show dark tones with a slightly magenta hue.
Vegetation damage may result in a decrease in near Infrared reflectance and
thus leads to an increase in cyan dye and a darker magenta hue. However, plants
with yellow unhealthy leaves will appear in white to mauve tones.
Knipling (1969) states that many of the colour differences on Ektachrome
Infrared aerial photography, particularly the subtle shades of red, can be
traced to variations in foliage area, density and orientation, rather than to
the reflection properties of individual leaves.
When the reflectance of a plant canopy is compared to that of the single leaf,
there is a striking difference between the canopy reflectance of Visible
radiation and that of near Infrared radiation. The canopy Visible reflectance
may account for 40%, and the canopy near Infrared reflectance for 70% of the
reflectance by a single leaf. The difference will be due to interaction of the
radiation transmitted by the toplayers of the canopy with that of the lower
leaves. Upon this interaction the Visible radiation is strongly absorbed while
the Near Infrared is reflected.
The application of false colour-film is reported in detection of
vegetation damage in forested areas (Murtha, 1978) and in urban areas (Remeijn,
1977) as well as in assessment of severity and extent of salt-affected areas in
agricultural fields (Myers, 1966; National Academy, 1970). According to Anson
(1968), the Ektachrome Infrared film is excellent for soil moisture studies and
delineation of vegetation boundaries.
Suitable scales are reported for different studies:
- forestry 1:6,000 and 1:16,000 (Stellingwerf, 1968); - crown damage in urban areas 1:2,000 or 1:5,000 (Remeijn, 1977);
- assessment of crop diseases 1:3,600 up to 1:8,400. For the assessment of salinity problems in growing cotton crops, proper timing
of the aerial survey is required. The crops have to be mature and the cotton
bolls should not be open. Furthermore, moisture stress will be likely when
temperatures and evapotranspiration are high, and irrigation is relatively long
ago. Moisture stressed cotton shows less near Infrared reflectance than healthy
cotton and produces dark magenta tones on the false colour photographs while
cotton plants that are seriously affected by salinity appear as nearly black.
239
Below, an example (see plate 1) of a false colour image of an area in the
Netherlands is discussed. Different land use types are clearly marked: planted
forest and roadside planting (different colour tones), grassland (bright red to
magenta) and arable land (light blueish-green, pink and light red to magenta;
note effect of tillage). Owing to the high reflectance of near Infrared by
grass canopies, red dominates in these places in the picture and differences in
grass coverage are masked. On the contrary, different canopies of planted
forest and roadside planting show much contrast. At least eight different tree
canopies can be recognized by evaluation of colour, size, shape and texture.
While contrast is largest between foliage trees and coniferous trees, this
picture clearly demonstrates the high potential of false colour for
differentiating between foliage tree species. To understand colour formation in
the false colour image, the various objects can be described visually by their
colour according to the I.T.C. Colour Chart (plate 3 ) . The colour codes,
obtained in percentages yellow, magenta and cyan, give an impression of the
dyes present in the transparent film or colour photograph. These dye
percentages are related to the exposure values (see par. 4.2 a.0. fig. 4.9).
However, without quantitative measurements and calibration techniques, the
relation is qualitative and rough.
9.8. Application of multispectral photography.
Experiments have been done with multispectral photography (Yost et al.,
1969) to determine its ability for measurement of basic ecological parameters
e.g. unique signatures for species of agricultural crops, trees and soil
surface types. To correct for variables, different techniques are applied (see
section 7.8), for instance man-made targets of known spectral reflectance are
used for calibration, and measurements on illumination and spectral reflectance
are carried out. Although results are promising for establishing soil surface
types (National Academy, 1970), application is found mostly in the field of
crop growing. According to Kannegieter (1980), multispectral photography may be
applied in order to:
- gain a better insight into disease behaviour of crops as a basis for more accurate control/prevention;
- single out in time, likely priority crop areas for preventative/curative action;
- assess damage and yield-reduction of crops.
9.9. Interpretation of sequential aerial photography.
Interesting results about application of sequential repetitive OK
multitemporal survey are reported by Kiefer ( 1 9 7 3 ) . He stated that the
distinction between different soil types was accomplished better by the use of
photography of certain dates than by photography of other dates. Consequently,
an optimum set of airphotos can be made by selection from multidate
photography. Other applications are found in studies on land evaluation, and
more specific in erosion studies.
Milfred and Kiefer ( 1 9 7 6 ) used sequential aerial photography to study soil
variability. They used airphotos taken on 20 different days from May through
November 1969 of a corn field in the state of Wisconsin. The photographs were
taken from a Cessna 172 aircraft at altitudes ranging from 610 to 1070 m above
the terrain. The film types used were: Kodachrome 11 film and Ektachrome
Inf KaKed Aerof ilm (Kodak type 8443) .
Very little rain had fallen in the area during July, August and September;
consequently, the growth of corn during this period was dependent on moisture
stored in the soil, the amount of which is largely determined by site, texture
and soil depth. The corn grew rapidly where sufficient moisture was available,
but turned brown in places where it was deficient. Dry areas with reduced corn
growth were delineated by interpretation of the repetitive airphotos. The dry
areas corresponded to slight topographic elevations of 1 to 2 m, with gentle
convex slopes. Adjacent nearly-level lower areas did receive runoff from these
areas and were relatively moist throughout the summer, enabling better corn
growth; the soil depth was found to be the greatest in these lower areas. Thus
the crop pattern revealed a dynamic soil property as well as soil distribution.
The relationship between crop growth pattern and soil will vary from year to
year and from region to region depending on differences in soil profile
characteristics, weather conditions and other edaphic factors. Therefore, a
careful evaluation of the validity of assumed causive factors is always a
necessity.
Soil scientists will often find it difficult to make quantitative
statements about soil variability without conducting expensive and time-
consuming field investigations. Sequential aerial photography offers a tool for
evaluation of soil variability and may simultaneously improve the speed and
accuracy of mapping. A small format camera mounted on a light aircraft can be
241
used for this purpose. For economic feasibility, the study of seasonal changes
may be limited to land units selected from a large study area. Diazo techniques
and additive colour techniques (see par. 5.1) may assist in change detection.
Diazo developing of one band positive transparent materials of two or three
acquisition dates in yellow, magenta and/or cyan coloured imagery, forms one of
the possibilities. When superposing the diazos of three acquisition dates in
yellow, magenta and cyan, the resulting coloured image is interpreted. For
imagery with correct colour balance, the interpretation is as follows: black,
grey and white indicate no change; coloured places have undergone a change at
one or more of the acquisition dates, the colours observed are indicative for
change at specific acquisition date(s).
9.10. Conclusions
Black- and -white photographs represent the most common tool for soil
survey by offering a.0. low cost stereoscopy.
A grouping of airphoto-interpretation units is suggested. When the flow chart
on interpretation for soil survey (see Fig. 8.1) is applied, this, together
with the suggested grouping (par. 9.2), may lead to uniformity in the legends
of interpretation maps.
Fieldwork comprises a.0. checking on validity and accuracy of interpretation
boundaries. Field observations may be done guided by physiographic and
morphogenetic interpretation in transects.
The interpretation products may be used for preliminary land evaluation which
is very useful in the planning of field survey.
True colour aerial photography is normally applied at large scales. It is
argued that colour fidelity ,which is low when the colour photographs are taken
from a high altitude, is not seriously limiting the identification of terrain
information.
Black- and -white Infrared airphotos offer a good means for discrimination
between vegetation types and clearly show differences in soil moisture
conditions. Especially in tropical forest areas, application is found for this
type of photograph.
False colour photography deserves attention as it offers a good
discriminating potential for vegetation types and provides means for assessment
of vegetation damage in forest areas, or the severity of salinity as well as
the extent of salt-effected areas in agricultural fields. The information
242
presented by the false colours may be described best through its transformation
in colour codes, representing percentages of yellow, magenta and cyan.
Multispectral photography i s generally applied in agricultural remote
sensing projects, but is also promising for soil survey in regions that contain
large areas of bare soil.
Multitemporal photography may be useful in areas where soil variability is
large.
9.1 1. References
Anson, A., 1968. Developments in Aerial Colour Photogrphy for Terrain Analysis. Photogrammetric Engineering 1968: pp. 1048-1057.
Beek, K.J. and Bennema, J., 1971. Land Evaluation for Agricultural Land use Planning. An Ecological Approach. Wageningen, The Netherlands: 47 pp.
Bennema, J . and Gelens, H.F., 1969. Aerial Photo-interpretation for Soil Surveys. Lecture notes ITC courses Photo-interpretation in Soil Survey- ing: 87 pp.
Benson, L.A., Frazee, C.J. and Waltz, F.A., 1973. Analysis of Remotely Sensed Data for Detecting Soil Limitations. South Dakota Agr. Exp. Station. Journal Series No 1168. SDSU-RSI-J-73-05: 9 pp.
Bergsma, E., 1974. Soil Erosion Sequences on Aerial Photographs. ITC Journal 197413, Enschede, The Netherlands: pp. 342-376.
Breimer, R.F., 1976. Detailed Soil Survey of the Rangwe Area. Training Project in Pedology, K i s i i , Kenya, Agric. Univ. Wageningen, The Netherlands: 56 PP.
Brinkman, R., Smyth, A.J. (ed.), 1973. Land Evaluation for Rural Purposes. Summary of an Expert Consultation (Chairman: J. Bennema). ILRI, Wageningen, The Netherlands, Publ. 17: 116 pp.
Burrough, P.A. and Kool, J.B., 1981. A Comparison of Statistical Techniques for Estimating the Spatial Variability of Soil Properties in Trial Fields, 3Sme Colloque AISS, Traitement Informatiques des Donn6es de Sol (Tome 1 Paris: pp. 29-37.
FAO, 1976. A Framework for Land Evaluation. Soils Bulletin, FAO, Rome nr. 32: 72 PP.
FAO, 1979. Soil Survey Investigation for Irrigation. Soil Bulletin no 42: 188 pp.
Gerbermann, A.H., Gausman, H.W. and Wiegand, C.L., 1971. Color & Color-IR Films for Soil Identification. Photogrammetric Engineering 1971: pp. 359-364.
Kannegieter, A., 1980. An Experiment using Multispectral Photography for the Detection and damage Assessment of Disease Infection in Winter-wheat: agronomic considerations. ITC Journal 1980-2: pp. 189-234.
Kiefer, R.W., 1973. Sequential Aerial Photography and Imagery for Soil Studies. Highway Research Record 421: pp. 85-92.
Knipling, E.B., 1969. Leaf Reflectance and Image Formation on Color Infrared Films. In: Remote Sensing in Ecology; ed. by P.L. Johnson, Athens, Univ. of Georgia Press: pp. 17-29.
Milfred, C.J. and Kiefer, R.W., 1976. Analysis of Soil Variability with Repe- titive Aerial Photography. Soil Sci. SOC. Am. J., Vol. 40: pp. 553-557.
Mulders, M.A., 1977. Reconnaissance S o i l Map of Northern Surinam 1:100.000, Map sheet 13. Soil Survey Department, Ministry of Development, Surinam.
Murtha, P.A., 1978. Remote Sensing and Vegetation Damage: A theory for
243
Detection and Assessment. Symp. on Remote Sening for Vegetation Damage Assessment 1978. Publ. by Amer. SOC. of Photogrammetry: 32 pp.
Myers, V.I., Asce, M., Carter, D.L. and Rippert, W.J., 1966. Remote Sensing for Estimating Soil Salinity. Journal of the Irrigation and Drainage Division. PKOC. of the Amer. SOC. of Civil Eng, IR 4: pp. 59-69.
Myers, V.I. and Allen, W.A., 1968. Electrooptical Remote Sensing Methods as Nondestructive Testing and Measuring Techniques in Agriculture. Applied Optics Vol. 7, No 9: pp. 1819-1838.
National Academy of Sciences, 1970. Remote Sensing. With special reference to Agriculture and Forestry. Washington: 423 pp.
Nortcliff, S., 1978. Soil Variability and Reconnaissance Soil Mapping: a Statistical Study in Norfolk. The Journal of Soil Science, vol. 29, No 3, Oxford Univ. Press: pp. 403-418.
Piech, K.R. and Walker, J.E., 1974. Interpretation of Soils. Photogrammetric Engineering - 1974: pp. 87-94.
Remeijn, J.M., 1977. Infrarood Kleurenfilm voor Vegetatiestudies. Landbouwkun- dig Tijdschrift 89-9: pp. 308-313.
SouchSre, P. de la, 1966. Comparaison des Photographies Panchromatiques et Infrarouges dans la Recherche de Renseignements en Zone Forestiere en Cote-d'Ivoire. IIe Symposium International de Photo-Interpr6tation, Paris 1966: 11/59-66.
Stellingwerf, D.A., 1968. The Usefulness of Kodak Ektachrome Infrared Aero Film for Forestry Purposes. 11th Congress of the International SOC. for Photogrammetry, Lausanne: 6 pp.
Thie, J., 1976. An evaluation of remote sensing techniques for ecological (biophysical) land classification in northern Canada. Proc. of the first meeting Canada Committee on Ecological (Biophysical) Land Classification. 25-28 May, 1976, Petawawa, Ontario: pp. 129-147.
Webster, R., 1977. Quantitative and Numerical Methods in Soil Classification and Survey. Clarendon Press, Oxford: 269 pp.
Wolff, G., 1966. Schwarz-weisse und falschfarbige Luftbilder als diagnostisch Hilfsmittel fiir operative Arbeiten beim Forstschutz (Rauchschaden) und bei der Waldbestandsdhgung. IIe Symposium International de Photo- Interprgtation, Paris 1966: 11/85-95.
Yost, E. and Wenderoth, S., 1969. Ecological Applications of Multispectral Color Aerial Photography. In: Remote Sensing in Ecology edit. by P.L. Johnson, Athens, Univ. of Georgia Press: pp. 46-62.
9.12. Additional reading.
Beek, K.J. , Bennema, J. and Camargo, M., 1964. Soil Survey Interpretation in Brazil. A System of Land Capability Classification for Reconnaissance Surveys. First Draft. DFFS-FA@Stiboka, Rio de Janeiro: 36 pp.
Beek, K.J., 1978. Land Evaluation for Agricultural Development. Thesis Agric. Univ. Wageningen, The Netherlands: 333 pp.
Bennema, J. and Meester, T. de, 1981. The Role of Soil Erosion and Land Degradation in the Process of Land Evaluation. In: Soil Conservation. Problems and Prospects (ed. by R.P.C. Morgan). John Wiley & Sons, New York: pp. 77-85.
Bergsma, E., 1971. Aerial Photo-Interpretation for Soil Erosion and Conservation Surveys. Part 11: Erosion Factors. ITC 9/71, Enschede, The Netherlands: 37 pp.
Bergsma, E., 1980. Method of a Reconnaissance Survey of Erosion Hazard near Merida, Spain. Proc. Workshop Assessment of Erosion in USA & Europe (ed. by de Boodt & Gabriels), John Wiley & Sons, New York: pp. 55-66.
244
Bowden, L.W. and BrooneK, W.G., 1970. Aerial Photography, a diversified tool. Geoforum 1970/2, Braunschweig, Germany: pp. 19-32.
Breuck, W. de en Daels, L., 1967. Luchtfoto's en hun Toepassingen. E. Story- Scientia P.V.B.A., Gent: 176 pp.
Bryan, R.B., 1968. The development, use and efficiency of indices of soil erodibility. Geoderma 2: pp. 5-26.
Clos-Arceduc, A., 1971. Disposition des Structures D'Origine Eolienne au Voisinage d'un Groupe de Barkhanes a Parcours Limite. Revue "Photo Interpretation, No 2 - 1971, fascicule 1, Editions Technip, Paris.
Dudal, R., 1981. An Evaluation of Conservation Needs. In: Soil Conservation Problems and Prospects (ed. by R.P.C. Morgan). John Wiley & Sons, New York: pp. 3-12.
Fairweather, S.E., Meyer, M.P. and French, D.W., 1978. The Use of CIR Aerial Photography for Dutch Elm Disease Detection. Symposium on Remote Sen- sing for Vegetation Damage Assessment, Comm. VII. Int. SOC. for Photo- grammetry, Seattle, Washington 1978: 12 pp.
Florence, G.R., 1980. Survey and Evaluation of Rangelands in the Hukuntsi- Ngwatle Pan Area, Kalahari, Botswana. ITC, Enschede, The Netherlands (thesis): 141 pp.
Foggin, G.t. I11 and Rice, R.M., 1979. Predicting Slope Stability from Aerial Photos. SOC. of her. Foresters, J. of Forestry: pp. 152-155.
Fritz, N.L., 1965. Film sees New World of Color. Citrus World 2 ( 2 ) : pp. 11-12, 26.
Gardiner, M.J. and Husemeyer, C., 1980. Selected Socio-Economic Aspects of Land Utilization. Commission of the European Communities. EUR 6876 EN: 308 PP .
Graham, R., 1980. The ITC Multispectral Camera System with respect to Crop Prognosis in Winter-wheat. ITC Journal 1980-2: pp. 235-254.
Howard, J.A., 1970. Aerial Photo-Ecology. Faber and Faber, London: 325 pp. Kiefer, R.W., 1972. Sequential Aerial Photography and Imagery for Soil Studies.
Highway Research Record 421. Remote Sensing for Highway Engineering: pp. 85-92.
Kirkby, M.J. and Morgan, R.P.C., 1980. S o i l Erosion. John Wiley & Sons. New York: 312 pp.
Lee, J. and Plas, L. van der, 1980. Land Resource Evaluation. Commission of the European Communities. EUR 6875 EN: 144 pp.
Mainguet, M. et Chemin, M.C., 1977. Les Marques de L'Erosion Eolienne dans le Sahel du Niger d'aprss les Images Satellites et les Photographies
' Agriennes. ler Colloque Pedologie T616d6tection, AISS, Rome: p. 139- 148.
Morgan, R.P.C., 1979. Soil Erosion. Topics in Applied Geography. Longman, London and New York: 113 pp.
Purdue University (Lafayette, Indiana), Agric. Exp. Station, 1968-1970. Lab. for Agric. Remote Sensing. Vol. No 3 and 4, Annual reports: 175 pp. and
Thalen, D.C.P., 1979. Ecology and Utilization of Desert Shrub Rangelands in
Vink, A.P.A., 1975. Land Use in Advancing Agriculture. Springer-Verlag, Berlin. White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey.
Clarendon Press, Oxford: 104 pp. Yost, E., 1967. Applications of a Multisprectral Color Photographic System.
C.I.S./I.C.A.S. Symp. on Airphoto-interpretation. Ottowa, Canada:
Yost, E.F. and Wenderoth, S., 1967. Multispectral Coibr Aerial Photography
111 pp.
Iraq. Dissertation Univ. Groningen and ITC, The Netherlands: 428 pp.
19 PP.
Photogrammetric Engineering: pp. 1020-1033.
245
Zonneveld, I.S., 1979. Land Evaluation and Land (scape) Science. ITC Textbook of Photo-Interpretation, Vol VII, Chapter VII, Enschede, The Netherlands: 134 pp.
Zuidam, R.A. van and Zuidam-Cancelado, F. I . van, 1979. Terrain Analysis and Classification Using Aerial Photographs. ITC Textbook of Photo- Interpretation, Vol. VII, Enschede, The Netherlands: 310 pp. and suppl. 23 PP.
246
10. AIRBORNE LINE-SCANNING IN THE 0.3-8 pm REGION
Airborne scanning is treated separately from spaceborne or satellite
scanning, since it differs from the latter in enabling observation at low
altitudes and consequently it may show differences in spatial and spectral
resolution. The spatial resolution of a scanning system is determined by its
IFOV and the speed of detection in relation to the speed of the platform ( s e e
par. 6.1). The speed of platform and groundpass of spaceborne platforms is
normally taken higher than that of airborne platforms. The same can be stated
for the speed of detection. Therefore, airborne scanning permits the use of
relatively long observation times per pixel. Although narrow band data at low
spatial resolution can be acquired from spaceborne platforms, the use of
relatively narrow bands at high spatial resolution is applicable to airborne
platforms only. If these bands are chosen carefully with regard to their
spectral allocation, they may provide much specific information on terrain
features. Of course, the general advantage of scanners, which is the provision
of quantitative data on reflectance or emittance, is valid for arrborne as well
as for satellite scanning.
For the principles of airborne line-scanning, the reader is referred to
par. 4 . 3 and to Lowe ( 1 9 7 5 ) . Imagery from airborne line-scanners is briefly
discussed in par. 6 . 4 , the processing of digital data in par. 5.2-5.4.
10.1. Airborne line-scanners
The airborne line-scanners operating in the Visible and Infrared may be
divided into (Higham e.a., 1973):
a) monospectral line scanners, which are generally modifications of military
hardware; they usually operate in the Infrared region of the spectrum and
many are uncalibrated systems suitable for qualitative sensing only;
integral film recorders are usually present, which are not suitable for
subsequent automatic data processing; uncalibrated systems are a.0. EM1
Airscan, HSD Linescan, Texas Instruments RS 310, De Oude Delft Linescan
and Reconofax; systems with black body reference are the Bendix TM/LN 3
and TI RS 18;
b) modified monospectral line scanners to obtain at least one additlonal
channel; this is usually achieved by the insertion in some part of the
241
optical system of a dichroic mirror to split the beam into two spectral
regions e.g. Daedalus DS 1220/30, Texas Instruments RS 14, SAT Super
Cyclops;
c) multispectral line scanners with limited spectral selection generally in
the Visible through the use of an integrated array of silicon photodiodes
e.g. Daedalus with DS-1250 (analog) and DS-1260 (digital) scanners, and
Bendix M2S; this type of system may also be extended into the Infrared by
the addition of a so-called dichroic mirror;
d) multispectral line scanners with full selection capability over the whole
Visible and Infrared region of the spectrum; this is obtained in the
Bendix MSDS by using dichroic mirrors and two separate grating
spectrometers for the Visible and Infrared.
A s an illustration of (c), the channels of the DS-1260 spectrometer are given
below:
1. 0.38-0.42 pm 4. 0.50-0.55 urn 7. 0.65-0.69 !.&I
2. 0.42-0.45 um 5. 0.55-0.60 prn 8. 0.70-0.79 ~rm 3. 0.45-0.50 pm 6. 0.60-0.65 UIII 9. 0.80-0.89
10. 0.92-1.10 pm
In the example, the channels have a bandwidth of 50 nm for the central
wavelength range (channels 3 up to 6 ) . The Bendix MSDS (d) differs from the DS-
1260 in covering a wider spectral range, being part of the UV, the Visible as
well as the Infrared up to 13 um.
The Bendix MSDS 24 channel allocation is detailed below:
Channel Bandwidth Channel Bandwidth Number (micrometers) Number (micrometers)
1 0.34 - 0.4 13 2.1 - 2.36 2 0.4 - 0.44 14 3.54 - 4.0 3 0.46 - 0.5 15 4.5 - 4.75 4 0.53 - 0.57 16 6.0 - 7.0 5 0.57 - 0.63 17 8.3 - 8.8 6 0.64 - 0.68 18 8.8 - 9.3 7 0.71 - 0.75 19 9.3 - 9.8 8 0.76 - 0.80 20 10.1 - 11.0 9 0.82 - 0.87 21 11.0 - 12.0
10 0.97 - 1.05 22 12.0 - 13.0 11 1.18 - 1.30 23 1.12 - 1.16 12 1.52 - 1.73 24 1.05 - 1.09
248
The Bendix MSDS has been developed for research and is not available on the
market. The most advanced system on today's market is the Daedalus eleven
channel multispectral scanner DS-1268, also known as the Airborne Thematic
Mapper (ATM). It was developed in 1981 as a modification of the DS-1260. The
system covers the bands used by the Landsat 4 Thematic Mapper, the Landsat 3
MSS and the SPOT System:
channel wavelength vm
1. 0.42 -0.45
2. 0.45 -0.52
3. 0.52 -0.60
4. 0.605-0.625
5. 0.63 -0.69
6. 0.695-0.75
channel wavelength um
7. 0.76-0.90
8. 0.91-1.05
9. 1.55-1.75
10. 2.08-2.35
11. 8.50- 13 .OO
10.2. Detection in the Ultraviolet
About 10 percent of the solar EMR that is incident on the earth's
atmosphere is in the Ultraviolet portion of the EMS. The atmosphere strongly
attenuates the Ultraviolet at wavelengths shorter than 0.28 urn, primarily due
to Rayleigh scattering and absorption by ozone and molecular oxygen. Optical
mechanical scanners using mirrors made of aluminum or of silver metal films
(Halter, 1973), UV filters and UV sensitive detectors produce imagery of fair
quality. An example is the Daedalus DEI-238 UV-Visible detector.
The low intensity of Ultraviolet radiation incident at the earth's surface and
the strong atmospheric influence cause the information content of the
Ultraviolet to be low when compared with that of the Visible and the Infrared.
However, despite these limitations, some targets exhibit contrasts in the
Ultraviolet that may be more useful than those obtained in other regions. In
the near Ultraviolet (read near to Visible or 0.3-0.4 pm) and the short
wavelength region of the Visible spectrum (blue), the carbonates, phosphates
and evaporites are usually more reflective than other rock materials.
Acidic rocks, such as granite and rhyolite, show little reflection in the
Ultraviolet but considerable reflection in the Visible, while basic rocks such
as basalt show little reflection in both regions (Cronin et al., 1973).
Data are also available ahout the penetration of Ultraviolet radiation in soil
materials. Coarse textured (dry) Soil materials show deeper penetration than
249
fine textured (dry) soil materials (Cronin et al., 1973).
10.3. Detection in the Visible zone and near Infrared
In chapter 3 the interaction of solar radiation with minerals, rocks,
soils and plants is discussed. In summary, the following is stated about
reflectance of soils and plants.
Soils: - the general pattern reveals an increasing reflectance from 0.5 l m ~ to
2.5 um ; contrast between soils may be obtained in the 0.4-0.5 um the
0.6-0.7 um and 1.7-2.5 um regions;
- increase of organic matter content and moisture content result in
decreasing reflectance over broad spectral regions;
- information about iron content may be obtained from a broad band at 1.1 urn, and weak bands at 0.87 !im and in the Visible;
- H20 is indicated by bands at 1.4 ~.lm and 1.9 um; OH- by a band at
2.2 pm;
- carbonate and gypsum are indicated by bands between 1.7 m and 2.5 um
(strong absorption due to the presence of Cog" at 2.35 m; gypsum
shows a band at 1.75 pm).
The so-called H20 bands are applicable for moisture determination with
artificial illumination in the laboratory. Under natural conditions the
radiation at 1.4 um and 1.9 pm is absorbed by atmospheric H20, which makes
their application in remote sensing complicated.
Plants: - reflection in 0.55 pm band and of near Infrared radiation;
- absorption in 0.44 um and 0.66 wn bands;
- damage affecting morphology results in a decrease of overall
reflectance especially of near h f rared; a change in physiology
involves a shift of the green peak towards yellow wavelengths; a
final change results in a shift towards red wavelengths.
Besides by the reflectance characteristics of the materials, the choice of
channels in remote sensing has to be directed by the wavelength regions as
indicated by the major atmospheric windows (given by Lintz and Simonett, 1976).
These are:
250
0.40-0.75 um 1.19-1.34 pm
0.77-0.91 um 1.55-1.75 pm
1.00-1.12 pm 2.05-2.40 pm
From the information given above, the following optimum channels for
airborne scanning in detection of soils and plants are suggested (Mulders,
1986) :
allocation hands in pm
0.5 3-0.58
0.58-0.63
0.6 3-0.68
0.84-0.90
1.20- 1.30
1.60-1.68
1.72-1.78
2.10-2.25
2.32-2.38
information content
green reflectance of plants
yellow reflectance of soils and plants
red absorptance by plants, contrast in
soil reflectances
maximum NIR reflectance of plants, iron
content of soils
reference value plants
reference value soils
gypsum
layer silicates
carbonate.
Airborne scanning, using the suggested channels, will provide optimum
contrast between soils and plants as well as between different soils and canopy
types. However, there is no general agreement about the choice of channels.
Tucker (1976) found in his study on the reflectance of blue grama grass, the
spectral regions of 0.37-0.50, 0.63-0.69 and 0.75-0.80 pm to be statistically
significant both early and late in the growing season. Of these spectral
regions, only the second is given above in the selection on channels.
Much agreement is found with the work of Bunnik (1978), who considered the
influence of changing canopy morphology, and the effect of a dry or moist
bounding soil, for optimum selection of spectral bands to discriminate between
different green plant canopies. He proposed four spectral bands with centre
wavelength positions at 550, 670, 870 and 1650 nm. The optimum selection is
based on the determination of maximum between class separation in the feature
space, defined by a minimum number of spectral bands selected within the
available atmospheric windows.
251
Present scanning systems are not directed in their choice of channels as
suggested above OK do show only part of these channels. Further testing of the
informative value of the suggested channels is necessary, especially in the
near Infrared > 1.60 pm, since only few data are available (e.g. the bands
1.72-178 urn and 2.32-2.38 pm). Besides bands at 0.45-0.50 !.nn and 0.85-0.95 wn,
the 2.2 um band was pointed out to be valuable for the inventory of hydrother-
mally altered rocks (Rowan et al., 1977).
Abrams et al., (1977) used data of the Rendix scanner for the delineation of
altered rocks. The following ratios were used: 12/13, 12/3 and 5/10 when
expressed in channel numbers, or 1.6/2.2, 1.6/0.48 and 0.6/1.0 when expressed
in approximate centers of channels in um.
The dynamics of soil moisture have to be evaluated in determining the soil
potential in rainfed agriculture. For this purpose, multitemporal reflectance
data may be used effectively. Mc Culloch et al., (1975) considered the use of
changes in reflectance of soil-vegetation units to detect changes in soil
moisture more promising than thermal scanning, though the relationship would
have to be derived for a large number of combinations. Both clay and sandy
soils show a large decrease in reflectance over the 0.5-2.6 wn region at
increasing moisture content (see Johannsen, 1969).
Apart from application in the field of soil moisture mapping, airborne MSS
has also been used for distinguishing freshly tilled soil from crusted surface
soil. The surface roughness can be evaluated from reflectance data taken under
different angles of illumination (e.g. different times of day).
Furthermore, airborne Multispectral Scanning (MSS) has been used to examine
soils with a moderate content of organic matter. For this purpose, Roth and
Baumgardner (1971) studied a soil test area of approximately 45 ha in
Tippecanoe County (Indiana), lying in a transitional zone between Alfisols and
Mollisols. They found a high correlation between multispectral response with
the content of organic matter in the upper cm of soil. Since automated
processing is of great importance in the study of MSS data, the method used by
Roth and Baumgardner is discussed as an example.
In their study, the size of the training set for computer implemented analysis
of multispectral data had an important effect on the correlation. A high rate
of digitization gave much greater correlation coefficient values than does a
low rate of digitization. Furthermore, the selection and number of channels had
a profound influence. In stepwise regression analysis, the charnlel 0.66-0.72
252
was the single best channel for predicting organic matter content in all
training set sizes, except for the single remote sensing unit ( R S U ) . The
channels 0.40-0.44 urn and 0.50-0.52 Dm were also generally high in the
selection of the best two or three channels. Some details of the method are
given below.
Sampling: the field was gridded at intervals of 46 m; at each grid-point a 1 kg surface soil sample was taken at a depth of up to 1 cm; the organic matter content was determined by a modified Walkley Black method.
MSS data: May 6, 1970 , altitude 1000 m; 6 channels in the 0.40-1.00 wn range; RSU approximately 9 m2.
Low digitization rate (LDR): every eighth scan line was digitized at the rate of 220 samples per scan line.
High digitization rate (HDR): every third scan line was digitized at the rate of 440 samples per scan line.
Size of training sets: 1 , 4 , 9, 25 , 6 4 , 100 and 144 RSU; the 25 RSU training set size produced maximum correlation with LDR data.
The channels pointed out for predicting organic matter should be further tested
for their value in other soil conditions. The correlation may be negative. That
is, the absence of organic matter may be indicated by a high reflectance in a
particular channel due to the absence of masking of soil material with specific
properties. In that case, high content of organic matter would produce a low
reflectance in that channel.
Generally, reflectance data indicate the presence or absence of particular
soil materials rather than the absolute contents of those materials. This will
be due to the effect of the type of the materials e.g. mineral grains or very
fine textured accumulations. For example, iron or lime may be present as
coatings on the mineral grains and exert a stronger influence on the
reflectance values than would be expected from their real contents. On the
contrary from uncoated mineral occurrences, high correlations between
reflectance values and contents may be produced.
Finally, attention is drawn to the research need for:
- the study of the soil reflection model;
- polarization techniques in discrimination between dry and moist soil
surfaces;
- back and forward scattering zones (see par. 2.6 and par. 3.2), for
example at the outer sides of large angle fields of view in airborne
253
scanning for discrimination of highly absorbent and highly reflectant
features.
10.4. Detection in the mid Infrared
The mid Infrared shows two atmospheric windows which enable remote sensing
(Fig. 2 . 1 2 ) , these being: 3.4-4.1 and 4.5-5.2 um.
The information potential of these bands (Tables 2.3 and 2.4) is as follows:
bands (pm) information potential
3.4-4.1
4.5-5.2 oxides, S i -0 bending
The value of these bands for remote sensing has to be tested in future (Mulders
et al., 1 9 8 6 ) .
C-H, C - H 2 , C-H3 (organic matter)
10.5. Conclusions
Line scanners may be distinguished roughly into monospectral and
multispectral line scanners.
The information content of the Ultraviolet window is low when compared with ,the
Visible and Infrared. However, some targets such as carbonates, phosphates and
evaporites exhibit higher reflectances in the Ultraviolet than in the Visible.
A number of channels can be selected on the basis of spectral properties of
soils and plants as well as on the allocation of the atmospheric windows.
Application of airborne MSS in soil survey is found in acquisition of
spectral signatures of soil surfaces and in discrimination of moist and dry
soil surfaces. It is especially in arid and semi-arid regions where the soil is
barely covered that airborne MSS is expected to be of great value for soil
survey when applied in combination with airphoto-interpretation. In other
regions, MSS may give much information about soil conditions at the time that
there are large areas of bare soil (e.g. extensive cotton or grain fields out
of the growing season).
Much research is necessary to explore the high potential information content of
airborne MSS. The results may be used for inventory and monitoring of the
environment at a large scale, as well as for the improvement of satellite MSS
techniques.
254
10.6. References
Abrams, M.J., Ashley, R.P., Rowan, L.C., Goetz, A.F.H. and Kahle, A.B., 1977. Use of Imaging in the 0.46-2.36 um Spectral Region for Alteration Mapping in the Cuprite Mining District, Nevada. U.S. Geol. Survey. Open-file Report 77-585.
Bunnik, N.J.J., 1978. The Multispectral Reflectance of shortwave Radiation by Agricultural Crops in Relation with their Morphological and Optical Properties. Thesis Agricultural University, Wageningen, The Netherlands: 176 pp.
Cronin, J.F., Rooney, T.P. e.a., 1973. Ultraviolet Radiation and the Terrestrial Surface. In the Surveillant Science. Remote Sensing of the Environment (ed. by R.K. Holz), Houghton Mifflin Cy, Boston: pp. 67-77.
Higham, A.C., Wilkinson, B. and Kahn, D., 1973. Multispectral Scanning System and their potential Application to Earth Resources Surveys. Basic Physics & Technology, ESRO CR-231: 186 pp.
Holter, M.R., 1973. Ultraviolet Imaging. In the Surveillant Science. Remote Sensing of the Environment (ed. by R.K. Holz), Houghton Mifflin Cy, Boston: pp. 78-82.
Johannsen, C.J., 1969. The detection of available s o i l moisture by remote sensing techniques. Ph.D. Thesis, Purdue University: 266 pp.
Lintz, J.Jr and Simonett, D.S., 1976. Remote Sensing of Environment. Addison- Wesley Publ. Cy, Reading, Massachusetts: 694 pp.
Lowe, D.S., 1975. Imaging and Nonimaging Sensors. Chapter 8 i n Manual of Remote Sensing. her. SOC. of Photogrammetry, Falls Church, Virginia: pp. 367- 397.
Mc Culloch, J.S.G., Painter, R.B., 1975. Application of Multispectral Scanning Systems to Hydrology. In ESRO CR-234, Plessey, United Kingdom: pp. 127- 149.
Mulders, M.A., 1986. Band Selection in Multispectral Scanning for S o i l Survey of Arid Zones. Proc. Symposium Remote Sensing for soil Survey. March 1985 (Wageningen, Enschede). ITC Journal, Enschede, The Netherlands.
Mulders, M.A., Schurer, K., Jong, A.N. de, Hoop, D. de, 1986. Selection of Bands for a newly developed Multispectral Airborne Reference-aided Calibrated Scanner (MARCS). Proc. ISPRS Congress August 1986, Enschede, The Netherlands; pp. 301-303.
Roth, C.B. and Baumgardner, M.F., 1971. Correlation Studies with Ground Truth and Multispectral Data: Effect of Size of Training Field. 7th Symposium Remote Sensing Michigan: 12 pp.
Rowan, L.C., Goetz, A.F.H. and Ashley, R.P., 1977. Discrimination of Hydrothermally Altered and Unaltered Rocks i n Visible and Near Infrared Multispectral Images. Geophysics, Vol. 42, No 3: pp. 522-535.
Tucker, C.J., 1976. Sensor Design for Monitoring Vegetation Canopies. Photogrammetric Engineering and Remote Sensing, Vol 42, No. 11: pp. 1399- 1410.
ISSS hth intern.
10.7. Additional reading
Heide, G. van der and Koolen, A.J., 1980. Soil Surface Albedo and Multispectral Reflectance of short-wave Radiation at a Function of Degree of Soil Slaking. Neth. J. Agric. Sci 28: pp. 252-258.
LARS, 1968. Remote Multispectral Sensing i n Agriculture. Annual Report Vol. no. 3. Laboratory for Agricultural Remote Sensing (LARS). Purdue Univ.,
255
Indiana: 175 pp. LARS, 1970. Item Annual Report, Vol. no. 4: 112 pp. Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpreta-
tion. John Wiley & Sons, New York: 612 pp. Polcyn, F.C., Spansail, N.A. and Mulida, W.A., 1973. How Multispectral Sensing
can help the Ecologist. In The Surveillant Science. Remote Sensing of the Environment (ed. by R.K. Holz). Houghton Mifflin Cy, Boston: pp. 349-359.
Sabins, F.F. Jr, 1978. Remote Sensing. Principles and Interpretation. W.H. Freeman and Cy, San Francisco: 426 pp.
Savigear, R.A.G., 1975. An Approach to the Evaluation of Multispectral Scanning Systems. In ESRO CR-234, Plessey, United Kingdom: pp. 7-50.
256
11. REMOTE SENSING FROM SPACE IN THE 0.3 - 3.0 um ZONE
Satellite imagery is freqoently used in extensive surveys. The cost of the
standard products (e.g. from Landsat) are low in relation to the benefit that
can be obtained from the synoptic view, since a large area is covered at one
time under uniform atmospheric conditions. The multitemporal potential forms
another advantage.
Below, as an introduction, different space missions are discussed (par.
11.1). For practical purposes, the discussion on technical aspects (par. 11.2-
11.3) and interpretation methodology focuses on first generation Landsat
products ( par. 11.4) and Thematic Mapper (par 11.5), which are most widely
used in earth resources surveys. Finally, the application (par. 11.6) is
commented on.
11.1. Manned space missions and unmanned satellites
For specifications on a number of satellites, the reader is referred to
par. 4.4. Below in table 11.1, a summary is given on manned missions and
satellites. It should be noted, that the sensors often cover a spectral region
Table 11.1 A selection on NASA and ESA space missions important for remote sensing of earth resources.
space missions year of manned design life or actual life (a) (first) spacecraft launching
Nimbus program 1958 - 1 year (Nimbus D) Tiros program 1960 - 3 months (1973 end of program) Mercury MA-4 1961 + 3 days Gemini IV 1965 + 2 weeks Apollo-15 1971 + about 2 weeks Apollo-16 1972 + about 2 weeks
Skylab 1973 + 28-84 days per visit ERTS or Landsat 1972 - 1 year
ATS 1974 - 1 year SMSIGOES 1974 - 3 years Tiros-N/NOAA 1978 - 6 months HCMMIAEM 1978 - 1978-1980 (a) Seasat 1 1978 - 106 days (a) Space shuttle 1981 + extended life
Note: Since 1973, also data of the so-called Defense Meteorological Satellite (DMSP) are available.
251
much wider than the 0.3-3.0 m region, but we regard the summary to be of value
at this place in the text.
The use of Mercury photographs for geological mapping dates back to 1963.
Other early spaceborne materials used for the study of megatectonical aspects
and regional geology are Gemini photographs (van der Meer Mohr, 1968).
The Nimbus Meteorological Satellite Program demonstrated the potential of
repetitive coverage in space imaging for Earth Resources Surveys. The Nimbus
program and the high resolution photography of Gemini and Apollo gave an
impetus to the Earth Resources Technology Satellite (ERTS) program, now denoted
Landsat. The Skylab program was a follow-up to the Mercury, Gemini and Apollo
manned space missions. The orbital altitude of Skylab was 432 km and the orbit
had an inclination of 50' to the equator. The imaging was feasible for 75 X of
the earth's surface. The emphasis of the Skylab program was the use of
precisely developed technology of manned spaceflights for advanced study in
physics, astronomy and monitoring of the earth's surface (Otterman e.a., 1976).
A number of sensors was mounted for this purpose in Skylab, including a
multispectral camera cluster, an Infrared spectrometer, a 13 channel
multispectral scanner and Microwave systems (see table 11.2).
Skylab can be regarded as a step in the development towards the Space
Shuttle. The Space Shuttle is a manned spacecraft that carries a space
hbOKatOKy into orbit throughout experimental missions. At the end of each
mission, the orbiter makes runway landings similar to those made by aircraft.
The so-called Spacelab is a European space laboratory for application in the
Space Shuttle missions. The purpose of Spacelab is to provide a ready access to
space for a broad spectrum of experimenters in many fields and from many
countries (Barrett and Curtis, 1982).
Spacelab can act as a bridge between ground or airborne measurements, and long
life automatic satellites. The first payload consisted of a high resolution
aerial mapping camera and an active radar system (9.65 GHz band; X-band see
chapter 13). The second payload of the Space Shuttle (flight 1981) contained
the SMIRR or Shuttle Multispectral Infrared Radiometer, which acquired the
first narrow-band spectral data from orbit (pixel diametre = 100 m). The
centers of the SMIRR spectral bands are as follows in ~nn : 0.60, 1.05, 1.20,
1.50, 1.60, 2.10, 2.17, 2.20, 2.22, 2.35. In particular the region 2.0 to
2.4 pm appeared to have potential for the identification of COfl and OH'-
bearing minerals such as layer silicates (Goetz et al., 1982).
258
Table 11.2. Skylab sensors after BaKKett and Curtis (1976).
Type of sensor Spectral Comments sensitivity range
S-190 Multispectral camera cluster no. 1 no. 2 no. 3 no. 4 no. 5 no. 6
S-191 Infrared specrometer
5-192 Multispectral Scanner channel 1 channel 2 channel 3 channel 4 channel 5 channel 6 channel 7 channel 8 channel 9 channel 10 channel 11 channel 12 channel 13
500-600 nm 600-700 nm 700-800 nm 800-900 nm 500-880 nm 400-700 nm
0.4-2.4 pm and 6-16 um
410-460 nm 460-510 nm 520-556 nm 565-609 nm 620-670 nm 680-762 nm 783-880 nm 980-1080 nm 1.09-1.19 pm 1.20-1.30 pm 1.55-1.75 pm 2.10-2.35 pm 10.2-12.5 pm
Type of film:
B&W: Panatomic-X B&W: Panatomic-X B&W: IR Aerographic R&W: IR Aerographic blOUK: IR Aerochrome COlOUK: S0-242*
Spectral resolution
2 ~ 1 0 - ~ pm to 2 . 5 ~ 10-1 um (lower at longer wavelength)
S-193 Microwave system 13.8-14.0 GHz (passive + active): radiometer, scattero- meter, altimeter
S-194 L-band microwave 1.4-1.427 GHZ Centre frequency of radiometer 1.4134 GHz: bandwidth 27 MHz
* Kodak Film with high resolution at low contrast.
11.2. Technical aspects Landsat
The technical aspects of Landsat are dealt with in the Landsat Data Users
Handbooks (NASA, 1972, 1976; US Geol. Survey, 1979). Below some important
technical aspects are summarized.
The Landsat program has been designated as a research and development tool
259
to demonstrate that remote sensing from space is a feasible and practical
approach to efficient management of the earth's resources. Landsat provides the
repetitive acquisition of multispectral data of the earth's surface on a global
base.
Two sensor systems have been selected for Landsat 1 and 2: a four channel
multispectral scanner (MSS) for Landsat 1 (five channels for Landsat 2), and a
three camera return beam vidicon (RBV).
The RBV camera system of Landsat 1 and 2 operated by shuttering three
independent cameras simultaneously, each sensing a different spectral band in
the range of 0.48 to 0.83 um . The spectral bands are respectively: 1) 0.475-0.575 pm ;
2) 0.580-0.680 pm ;
3) 0.690-0.830 um . The MSS is a line scanning device which uses a mirror that scans
perpendicular to the track of the spacecraft as is shown in fig. 11.1.
MSS scanning arrangement
+ 2 f o r band ( l a n d s a t - 3 )
F i e l d o f v iew =
South Eas t - L ines scan-bands 4-7 - L ines scan-band 8
D i rec t i on o f f l i g h t
Fig. 11.1 Operation of the Landsat multispectral scanner after Short (1982).
Six lines with the same bandpass are scanned simultaneously in each of the four
spectral bands for each mirror sweep. The spacecraft's motion causes the along-
track progression of the six scanning lines. The electromagnetic energy is
260
sensed simultaneously by an array of detectors in the four spectral bands in
the range of 0.5 to 1.1 pm . The spectral bands are respectively:
4) 0.5-0.6 pm ; 6) 0.7-0.8 pm
5) 0.6-0.7 pm ; 7) 0.8-1.1 pm
A band in the thermal Infrared from 10.4-12.6 pm is included in Landsat 2
(band 8 ) .
The MSS data are radiometrically and geometrically calibrated. The detector
outputs are sampled, encoded into six bits and formatted into a continuous data
stream of 15 megabits per second. The continuous StKip imagery is transformed
later on into framed images with a 10 percent forward overlap of the
consecutive frames.
Landsat (1, 2 OK 3) operates in a circular sun-synchronous near-polar
orbit at an altitude of 912-920 km. It circles the earth every 103 minutes,
completing 14 orbits daily, and views the entire earth every 18 days, thus
fixing the repetitive coverage. A typical Landsat daily ground trace is given
in fig. 11.2. Note that due to the rotation of the earth in eastward direction,
the ground track progresses in westward direction.
The sun-synchronous orbit refers to the geometric relationship between the
orbit's descending node (south bound equatorial crossing) and the mean sun's
projection into the equatorial plane. Since the orbit plane rotates at the same
rate as the mean rate of the earth about the sun, this relation is constant. In
other words, the angle between the orbit plane and the line that connects the
earth's centre with the sun's centre remains constant (being 37.5").
For Landsat 1 and 2 the mean sun time at descending mode was established
between 9:30 and 1O:OO a.m. The actual mean sun time at descending node
achieved for Landsat 1 was 9:42 a.m. and that for Landsat 2 was 9:32 a.m. The
local time is determined by discrete time zones.
The image sidelap OK lateral overlap of adjacent tracks amounts 14 percent
at the equator, but increases to 85 percent at 80' latitude. The image sidelap
at different latitudes is given in table 11.3.
The overlap (e.g. 30 X ) provides stereoscopic coverage in terrain with height
differences larger than 100 metres (Hilwig, 1979).
The CKOSS track optical scan of Landsat 1-3 is 185.2 km. To obtain a 185.2
x 185.2 km scene, 390 spacecraft mirror scans (performed in 25 seconds) are
required. The nominal instantaneous field of view (IFOV) of each detector in
bands 4 up to 7 is 79 meters square. Since the next sample overlaps the
261
Fig. 11.2Typical Landsat daily ground trace, showing local time variations within an orbit (after US Geological Survey, 1979).
foregoing sample by 23 metres, the effective IFOV of a detector in the cross
track direction must be considered to be 56 meters. Therefore, the picture
element or pixel has a nominal area of 56 x 79 meters (at nadir point).
The first three Landsats had the same basic 4 band sensor package. Besides
this package, Landsat 4 additionally contains the so-called Thematic Mapper
(TM) The TM operates in seven spectral bands with the following spectral
ranges :
1) 0.45-0.52 urn 5) 1.55-1.75 um
2) 0.52-0.60 urn 6) 10.40-12.50 um
3) 0.63-0.69 um 7) 2.08-2.35 um
4) 0.76-0.90 um
262
Table 11.3 S i d e l a p of a d j a c e n t Landsat 1-3 coverage swaths a f t e r N A S A (1976).
L a t i t u d e (deg rees ) Image S i d e l a p ( X )
0 14.0 10 20 30 40 50 60 70 80
15.4 19.1 25.6 34.1 44.8 57.0 70 .6 85.0
~~~~~ ~ ~~
Both r ad iomet r i c s e n s i t i v i t y and s p a t i a l r e s o l u t i o n a r e improved i n t h e TM, t h e
l a t t e r be ing 30 m f o r bands 1-5 and 7. Band 6, t h e thermal band, ach ieves a
p i x e l s i z e of 120 m on t h e ground.
Landsat 4 h a s a sun-synchronous near -polar o r b i t a t a nominal a l t i t u d e of
705 km over t h e equa to r . The s a t e l l i t e c r o s s e s t h e equa to r a t approximate ly
9:45 a.m. on each pass . Each o r b i t t akes n e a r l y 99 minutes and t h e s p a c e c r a f t
w i l l complete j u s t ove r 144 o r b i t s p e r day cove r ing t h e e a r t h eve ry 16 days.
The lower o r b i t of Landsat 4, necessary f o r t h e 30 m ground r e s o l u t i o n of t h e
TM, r e s u l t s i n a n e a r t h coverage cyc le d i f f e r e n t from t h a t of t h e e a r l i e r
Landsa ts ( N A S A , 1982).
In t h e e a r l y o r b i t s of Landsat 1, t h e RBV system genera ted d a t a of
e x c e l l e n t q u a l i t y . However, a s a r e s u l t of a c i r c u i t f a i l u r e wi th in weeks a f t e r
launch , t h e RBV system ceased t o func t ion . The RRV on Landsat-2 is i n working
o r d e r , bu t i s ope ra t ed p r i m a r i l y f o r equipment t e s t i n g purposes and i s be ing
h e l d i n r e s e r v e f o r p o s s i h l e s p e c i a l O K emergence use (Na t iona l Academy of
Sc iences , 1977).
The Landsat 3 RBV system c o n s i s t s of two RRV cameras, each capable of
imaging an a r e a approximate ly one-fourth t h e s i z e of a n HSS scene. One broad
s p e c t r a l band 0.505-0.750 !im i s covered by t h e RBV system. The ground
r e s o l u t i o n of t h e RBV imagery i s cons ide rab ly Sharper ( 3 8 by 38 m) than t h a t of
t h e MSS. This advantage of RBV d a t a does no t d imin i sh t h e va lue of t h e b e t t e r
s p e c t r a l i n fo rma t ion of MSS da ta . Good r e s u l t s may be obta ined when both a r e
used i n combination ( N A S A , 1979, Landsat Data Users Note No 5).
A s may be ev iden t from t h e foregoing , problems may occur due t o c i r c u i t
f a i l u r e s . However, i t i s a l s o p o s s i b l e t h a t t h e a c t u a l l i f e t i m e of a system
263
extends the lifetime expected. It is therefore necessary to indicate the status
of the satellite systems. The status of the Landsat series is summarized below
(see NOAA, 1983, for Landsat 3 and 4):
Landsat 1 July 22, 1972fJanuary 6 , 1978; RBV failure within 2 weeks;
Landsat 2 January 22, 1975f.January 22, 1980; reactivated June 6 , 1980;
Landsat 3March 5, 1978/September 30, 1983; thermal band failed August 11,
1978; MSS line start problem mid 1978; RBV is working nominally;
Landsat 4 July 29, 1982; failure of X-band transmitter February, 5, 1983; data
relay system operational on limited basis end 1983; final
verification of the Thematic Mapper ground processing system January,
1985;
Landsat 5 March 1, 1984; MSS and TM operational.
There is a global notation system for Landsat data. A nominal scene centre
may be designated by path and row number. The path number refers to one of the
nominal tracks. The row number refers to the latitudinal centre line of a frame
of imagery.The following photographic products are available:
- system corrected images, comprising radiometric and .initial spatial
correction;
- scene corrected images, additionally containing transformation into
Universal Transverse Mercator or Polar Stereographic coordinates.
A 15-step grey scale tablet is exposed on every frame of imagery, which is
related to the energy incident on the sensor. The grey tones cannot be used
reliably for microscale radiometry, because the areas in the order of a few
pixels are subject to influence by neighbouring areas and do not supply enough
data power to average the noise down to a low figure.
Digital data are available in the form of Computer Compatible Tapes (CCT),
These tapes are standard half-inch wide magnetic tapes and are supplied in 9-
track or 7-track format.
For an optimum choice of MSS imagery and CCT there are three requirements:
a) information about availability, which can be obtained by a query for
computer search and/or microfilm images; the requisites involve
coordinates, required image quality and maximum cloud cover; microfilm
images are useful to locate the cloud cover;
b) evaluation of meteorological data such as temperature, precipitation and
evapotranspiration diagrams (fig. 11.4);
264
c) evaluation of agricultural data by means of a crop calendar (fig. 11.5).
and data about the development of natural vegetation.
Inquiry forms for geographic computer search and order forms for Landsat
standard products are available at the Eros Data Center, Sioux Falls, USA. The
price of 18.5 cm negative or positive Landsat MSS imagery is relatively low and
CCT's are available at a reasonable price (US EOSAT: pricelists).
For a detailed discussion on the selection of Landsat MSS data, the reader is
referred to Hilwig (1979).
To guarantee the satellite data flow, the quality of the data, and to
provide aid and information, ground station networks as well as distribution
networks must be available. The approximate receiving ranges of operating and
proposed Landsat ground stations are shown in fig. 11.3. The European stations
for Landsat data are located at Fucino (Italy) and Koruna (Sweden).
The so-called Earthnet, set up by ESA for reception and distribution of
satellite data in Europe, became operational in 1978 and includes two other
stations: Lannion (France) for reception of HCMR and Nimbus 7 data (Nimbus 7
was launched at 24/10/78) , and Maspalomas (Canary Islands) for Nimbus 7 data
only.
The Earthnet programme office is located in Frascati (Italy). Data distribution
relies on this office and on a network of national points of contact. Recent
satellite data have to be ordered through these national contacts.
11.3. Annotations Landsat MSS imagery
The data on Landsat photographic products as given by NASA (1972) are
summarized below. For examples on Landsat imagery, the reader is referred to
fig. 6.5 and par. 11.4.
From each 55.8 mm image (scale 1:3,369,000), an enlargement to 18.5 cm (scale
1:1,000,000) is available.
Four registration marks are placed beyond the image corners to facilitate
alignment of different spectral images of the same scene from the same payload
sensor. The intersection of diagonals drawn through the four registration marks
is the format centre of the image.
Latitude and longitude tick marks are placed outside the edge of the image at
intervals of 30 arc minutes. At latitudes above 60 degrees north or south, tick
marks are spaced at one degree intervals.
265
120' 80' 40' O 0 40' 80' 120'
kote: ;overage circl'es based on lhdsat-'3 reception (alt i tude: 917 km)
NASA HO ~ 1 8 0 4358 ( 1 ) REV 9580
Fig. .11.3 World-wide location of operating or proposed ground stations for reception of data transmitted by Landsat after Short (1982).
A 15-step grey scale tablet is exposed at the bottom of every frame of imagery.
Above the grey scale tablet an annotation block is shown that contains the
following:
a) day, month and year of data acquisition;
b) latitude and longitude of image format;
c) item of nadir from spacecraft;
d) sensor and spectral band;
e)
f) codes for spacecraft heading, orbit revolution number and ground
sun elevation angle and sun azimuth angle;
recording station;
g) codes for size, processing, computation image centre, signal processing
266
prior to transmission and signal gain;
h) agency and project;
i) frame identification number.
The scanning nature of Landsat images appears more and more in the form of
lines upon enlargement. The discrete rectangular pixels as determined by the
ground resolution of 56 x 79 metres appear when prints of medium scale are
obtained from automated processing (Fig. 11.11).
11.4. Processing and interpretation of Landsat MSS data
The processing of Landsat MSS data may include:
- photographic processing of negative into positive black- and -white images,
the production of diazo materials e.g. band 4 in yellow, band 5 in magenta
and band 7 in cyan;
- automated processing of digital data e.g. ratioing and principal component
transform OK PCT.
Donker and Mulder (1977) showed for a test area at Roermond (The
Netherlands) how PCT can be applied to produce an optimum image for visual
interpretation of Landsat data (par. 5.2). Several ratios were applied in
automated processing. Dethier et al. (1975) used the so-called Band Ratio
Parameter (BRP) for comparing the relationship between absorbed and reflected
radiation by vegetation:
BRF' = band - band , where band 7 is the intensity of radiation in
band 7 + band 5
band 7 etc. Another ratio, which is often used, is the 715 ratio.
Sabins (1978) stresses the advantage of ratio values (ratio 415 Landsat) i n
removing illumination differences between sunlit and shadow areas.
Hielkema (1979, 1980) presented the following general conclusions as an
outcome of his study on Landsat data of desert areas:
- band 7 appears to be far less sensitive to changes in vegetation cover than
band 5;
- combination of bands 5 and 7 seems to provide the best basis for separation
of the abiotic and biotic environment;
261
- combination of bands 4 and 5 indicates the best prospects for separation of
abiotic spectral classes;
- multitemporal analysis for change detection is hampered by atmospheric
conditions changing through time; it is suggested to apply a correction
factor obtained by PCT on a representative sample set for each acquisition
date; using 715 ratios, the data normalization involves the definition of
two new spectral axes in the band 7 against band 5 plot in such a way that
the main 715 data axis has an orientation of 45' and that the main data axis
intersects the spectral axis at the origin; the result is a series of band
715 data clusters of which the main axes have a slope of 4 5 ' ;
- data sampling techniques have to be used for reducing the total data
processing volume of Landsat to perform monitoring activities over large
areas at an economic level.
Interpretation of multitemporal Landsat imagery may be done by integrating
static and dynamic interpretation aspects. Hilwig ( 1 9 8 0 ) analysed the following
interpretation aspects on Landsat imagery of the Dehra Dun region in Northern
India:
static aspects dynamic aspects
- drainage pattern - drainage condition
- alignments - vegetation and land use
- landform
For analysis of static aspects, the best image has to be selected from a set of
images; often a band 5 or 7 image of one date is selected as the best one.
However, dynamic aspects have to be studied on multitemporal combinations.
Finally, a multitemporal physiographic interpretation map can be composed.
Photographic and digital processing produces a set of image products. Each
image product may have its specific value for interpretation. Therefore, basic
data are needed for a proper selection of imagery with regard to the purpose of
the interpretation.
The study on small-scale soil and land use mapping of the Calatayud Basin
(Prov. Zaragoza, Spain, by Mulders and O'Herne, 1984) is used as an example
throughout most of the following text.
The Calatayud Basin is filled in with Miocene sediments, which are composed of
gypsum, marl and limestone series in the central part and mainly of
268
Po mm
250
200
150
50
0
# I
10
Yearly average temperature Yearly average precipitation Yearly average potential evapotranspiration
... monthly average temperature ("C) - monthly average precipitation (mm) _ _ _ monthly average potential evapotranspiration (PE in mm) R = recharge U = utilization D = deficit
Ta = 13.8"C Pa = 431 mm PEa = 704 mm
Fig. 11.4 Climatic data and soil water balance of the Calatayud Basin. (Mulders and O'Herne, 1981). T and P for station Calatayud (1948- 1966); PE for station Zaragoza (Ta = 14.6; T distribution identical to Calatayud) and PE = c.Eo Note:Eo is evaporation of free water surface;
c is a factor relating Eo to PE for a crop; it amounts to 0.65 for grassland.
conglomerates, breccies and loams at the fringes of the basin.
Climatic data are given in fig. 11.4 and a crop calendar is presented in fig.
11.5.
The climatic data and the crop calendar were used in the selection of imagery
and digital products (see fig. 11.5). In this case, average climatic figures
could be used. However, when precipitation is subject to strong variation and
thus not reliable, data of the actual precipitation are required for the
selection of satellite products. In fig. 11.5, an estimation on the percentage
of green vegetation for the different crops is given. This estimation together
with the acquisition dates of the satellite products gives insight in the
information potential of the remote sensing data.
A flow chart is suggested for small-scale soil, land use and natural vegetation
mapping with the aid of Landsat MSS data (table 11.4).
269
% o f cover by green vegetation as funct ion o f time and crops.
Fig. 11.5 Crop calendar for the Calatayud Basin, the selected Landsat images and CCT's (Mulders and O'Herne, 1981).
Agricultural activities: M = manuring P = field preparation S = sowing H = harvesting
Landsat products: u - imagery 0 - CCT's
The following materials were produced in the study of the Calatayud Basin for a
preliminary interpretation:
a) positive black- and -white images of several acquisition dates
(which may he combined to colour comhinations using a Colour
Additive Viewer) : b'> diazo imagery of several acquisition dates (hand 4 in yellow, hand 5
in magenta and hand 7 in cyan to produce false colour composites);
270
Labora tory P rocess ing Work c
Contras t Enhancement and/or Enlargement i n d i v i d u a l Rand Imagery
-+ 4,5 ,7 O K 6 combinations
+ Mult i t empora l Combinations e.g. Band 7 and /o r 5
c Se lec t ion of a r e a s f o r d i g i t a l p rocess ing
P rocess ing o f - s e l e c t e d a r e a s c
Histogram Equal- i s a t i o n O K sca- l i n g i n d i v i d u a l Band Data
+ 4,5 ,7 ( O K 6 ) co- l o u r coded com- b i n a t i o n + r a - t i o i n g e.g. 715; P r i n c i p a l Com- ponent Transform
+ d i g i t a l mul t i - t empora l Imagery e.g. 715 01-7-5
7+ 5
271
Table 11.4 cont inued
F u r t h e r Study Photographic P roduc t s i n c l . a i r p h o t o s
F u r t h e r d a t a Compress i o n and Informat ion E x t r a c t i o n
c Automated C l a s s i f i c a t i o n
I n t e r p r e t a t i o n c
c Fie ld Work F i n a l Fieldwork and C l a s s i f i c a t i o n
Desk Work Cans t ruc t ion of S o i l . Land Use and Na tu ra l Vegeta t ion Maus
c ) d i azo imagery of one band of d i f f e r e n t a c q u i s i t i o n d a t e s ( e . g . band 7 of
January in yel low, of June i n magenta and of September i n cyan t o produce
mul t i t empora l co lou r composi tes ) ;
d) p o s i t i v e en largements of n e g a t i v e imagery;
e ) CCT de r ived p roduc t s a f t e r
- l e v e l by l e v e l d i s p l a y on a line p r i n t e r o r TV sc reen ; h i s togram
e q u a l i s a t i o n f o r enhancement of c o n t r a s t ;
- combinations of two o r more bands in co lour ,
- 7 / 5 r a t i o i n g and P r i n c i p a l Component Transform (PCT).
The a u x i l i a r y equipment may be t h e fo l lowing:
- l i g h t t a b l e and overhead p r o j e c t o r ( f o r a up t o d ) ;
- co lour a d d i t i v e v iewer ( f o r a and d)
- l i n e p r i n t e r and co lou r g r a p h i c s system/TV sc reen ( f o r e )
A band 7 image of t h e Calatayud area i s shown i n f i g . 11.6 The Calatayud Basin
has a SE-NW o r i e n t a t i o n and i n c l u d e s most of t h e image.
The p re l imina ry v i s u a l i n t e r p r e t a t i o n may comprise t h e fo l lowing:
- t h e a n a l y s i s of s t a t i c e lements e.g. r e l i e f , d ra inage p a t t e r n / d e n s i t y ;
o f t e n p o s i t i v e black- and -white imagery i s used f o r t h i s purpose (e.g.
band 5 o r 7 ) ; imagery acqu i red a t low sun a n g l e s i s most s u i t a b l e f o r t h e
a n a l y s i s of r e l i e f ;
- t h e a n a l y s i s of dynamic e lements e.g. n a t u r a l v e g e t a t i o n and l and use;
t h i s is b e s t acqu i r ed wi th mul t i tempora l co lou r composites and f a l s e
co lou r composites (pho tograph ic o r d i g i t a l p roducts ) .
As a n i l l u s t r a t i o n of non-d ig i t a l methods, a n example of co lou r a n a l y s i s of
272
Fig. 1 1 . 6 . A band 7 image of 30 January 1975 of the Calatayud area (Landsat ID n r 2008-10081).
273
multitemporal diazo colour composites of part of the Landsat frame (see plate 2
for band 5 composite) is given in fig. 11.7.
The colour analysis of fig. 11.7 is done by mutual composition of the
multitemporal combination of band 5 with that of band 7. Besides colour,
pattern is also considered. The multitemporal combination for each of these
bands is as follows:
January - yellow, June - magenta, September - cyan (a low % of secondary colour
means a high intensity of reflected radiation)
For arrangement of the units, the saturation of the dominant colour of the unit
was used in this order: yellow, magenta, cyan.
For arrangement within the units, the percent of coverage (from high to low) of
the coloured components was used.
A first interpretation as aided by the crop calendar (fig. 11.5) and airphoto-
interpretation gives a good impression of the structure of the data. Some
examples are discussed below.
Mapping unit C contains mainly young pinus plantations, matoral and erial (low
shrubs and grass), furthermore some almonds and grapes. The dominant vegetation
(in 60 % of the area) results in a moderate band 7 intensity in January and in
very low band 7 intensities in June and September. The very low band 7
intensit,ies are due to the low vegetation coverage at those dates. The moderate
intensity in January will be due to the growth of matoral and erial at that
time . Mapping unit G1 shows a dominant vegetation of grapes, unit I mainly contains
irrigated fruit trees. Both units have a high reflectance in band 7 in June
pointing to a relatively high vegetation cover. Mapping unit M shows very high
reflectances in most of the area throughout the year in band 7 as well as in
band 5, the latter pointing to an extremely low vegetation cover. The very high
reflectances are due to the presence of gypsiferous soils in this unit.
A comparison of the Landsat pixel size with the size of parcels that show
different land utilization types, revealed that i n a number of mapping units
(e.g. A2s F3, G2, H2, J1 and J2) it will be very difficult to indicate the type
of vegetation and/or soil surface responsible for the reflection, the size
of parcels being equal to or smaller than the ground resolution cell. Also the
non-dominant relative intensity figures appeared difficult to translate
214
Fig. 11.7 Colour analysis of multitemporal band 7 and band 5 colour composites of the Calatayud area (for location: see Fig. 11.6).
being often a mixture of heterogeneous pixels.
The translation was most successful in the mapping units with homogeneous
vegetation. Apparently, there is a limit in classification accuracy as related
to homogeneity of the landscape.
Limitations of the visual COlOUK analysis are the inaccuracies related to the
estimation of the colour codes and to the analysis of complicated colour
patterns. The best results will be obtained when images of good quality are
used, as acquired with reversal film.
The study of the multitemporal photographic products and of the images for
analysis of static aspects is used in this stage to select areas for digital
processing.
Digital processing may be done to get products that are helpful for
275
i n f o r m a t i o n e x t r a c t i o n e.g. t h e band 7 r a t i o .
hand 5
Ry t h i s r a t i o a n i m p r e s s i o n may b e o b t a i n e d of t h e h i o t i c / a b i o t i c d i s t r i b u t i o n .
F i g . 11.8 p r e s e n t s t h e 7 / 5 r a t i o p i c t u r e f o r t h e a r e a n e a r C a l a t a y u d ( a p p r o x .
t h e same area as i n f i g . 11.7) . The 7 / 5 image shows a v e r y h i g h c o n t r a s t
be tween areas w i t h low ( < 20 X) v e g e t a t i o n c o v e r and a r e a s w i t h h i g h ( > 6 0 Z)
v e g e t a t i o n c o v e r ; a p p e a r i n g as w h i t e a r e a s and h l a c k a r e a s , r e s p e c t i v e l y , i n
f i g . 11.8, which i s a n e g a t i v e image.
W x 100 r a t i o ( 5 ) + 1
( r a t i o p i c t u r e d i s p l a y e d a f t e r h i s t o g r a m
equa 1 i sa t i o n )
F i g . 11.8 R a t i o p i c t u r e o b t a i n e d f rom MSS d a t a of t h e a r e a n e a r C a l a t a y u d on 4 September 1976 ( I D n r 1-215-031-084).
The p r e s e n t e d r a t i o - p i c t u r e i s of poor q u a l i t y b e c a u s e of t h e r e p r o d u c t i o n
p r o c e s s . A number of i n t e r a c t i v e s y s t e m s o f f e r t h e p o s s i b i l i t y of d i s p l a y i n g
c o l o u r - c o d e d d e n s i t y s l i c e d r a t i o p i c t u r e s on a TV-screen. I n t h i s way
c o n s i d e r a h l e i n f o r m a t i o n on v e g e t a t i o n a n d l a n d u s e c a n h e e x t r a c t e d . Using a
r a d i o m e t r i c and g e o m e t r i c c o r r e c t i o n as d e s c r i b e d hy n r o n s v e l d a n d L u d e r u s
( 1 9 8 2 ) , a d i g i t a l m u l t i t e m p o r a l image c a n h e p r o c e s s e d w i t h optimum d e t e c t i o n
p o t e n t i a l . The f o l l o w i n g r a t i o s may h e u s e d :
h a n d s 7 - 5 o r h a n d s 7 + 6 - 5 - 4 b a n d s 7 + 5 bands 7 + 6 + 5 + 4
Problems c o n n e c t e d w i t h m a t c h i n g of m u l t i t e m p o r a l d i a z o imagery a re a v o i d e d
t h e n , and s u c h p r o d u c t s c e r t a i n l y a r e p r e f e r r e d a b o v e t h e v i s u a l l y matched
276
images discussed above.
In addition to the digital multitemporal image, specific questions which
are related to the purpose of the Survey, landscape performance and
agricultural practice, determine the type of other imagery wanted. For example,
relief analysis is done preferably on images acquired when the sun angle is
low, and soil surface analysis preferably when the vegetation cover is low.
It may be practical to use Principal Component Transform (PCT) to obtain
data compression. If performed before the actual fieldwork, the data-points to
compose the sample set may be selected at random. On the other hand, the visual
interpretation products of Landsat imagery and digital ratio pictures may be
used for fieldwork to identify objects, thus enabling the composition of a
fieldborne sample set for PCT.
The PC1 and PC2, calculated by using the CCT-data of the fieldborne sample set
of the Calatayud area, already accounted for 98 to 99 Z of the total variance;
this implies that the original four-dimensional data set can be compressed into
a two-dimensional one without significant loss of information.
The values of PCl and PC2 are:
PC1. = 0.33 I4 + 0.53 I5 + 0.62 I6 + 0.46 I7
PC2 = -0.35 I4 - 0.62 I5 + 0.21 I6 + 0.67 I7
PCI is a weighted summation of the four MSS-bands. PC2 strongly depresses the
radiation in bands 4 and 5 . These are weighted and subtracted from the weighted
summation of bands 6 and 7. The difference between terrain objects which are
highly reflectant and those which are low reflectant in the near Infrared is
enhanced in this way.
The feature plane formed by PCl and PC2 for the data of 4 September 1976 is
shown in fig. 11.9.
The feature plane formed by the calculated values of PC1 and PC2 of the ground
observations on reflectance is presented in fig. 11.10.
When comparing the feature plane of the CCT-PC values with the one of the
ground observation PC values, there appears to be a rotation over about 20" of
the latter with respect to the CCT-set. This will be due mainly to atmospheric
influences. According to Hielkerna (1979, 1980), the data can be normalized by
defining two new spectral axes.
The ground observations on reflectance and the general observations to identify
terrain features are both useful for the identification of clusters in the PCI-
pc2 feature space of the CCT data. A better understanding is obtained a.0. of
the influence of vegetation cover by grapes on reflectance:
211
1 I I I I I I I I 1 30 40 50 60 70 80 90 100 110 120
PC1
Fig. 11.9 Fea tu re p lane of PCI and PC2 of MSS d a t a h th September 1976.
Legend: D = grapes K = wheat ( b a r e s o i l ) E = n a t u r a l v e g e t a t i o n 0 = orcha rds F = f o r e s t ( p i n e ) T = town I = i r r i g a t e d c rops Y = nea r ly bare gypsum s o i l s
s e e t h e sequence K2-E-D2-D1 i n f i g .
from l e f t t o r i g h t .
Fig. 11.11 p r e s e n t s t h e PC1 and PC2 p i c t u r e s (ob ta ined by l i n e - p r i n t i n g ) of t h e
CCT of January 1977 f o r p a r t of t h e Calatayud Basin. The in f luence of t he low
sun ang le a t t h e a c q u i s i t i o n d a t a i s c l e a r l y noted i n t h e h igh c o n t r a s t PC1
image, e s p e c i a l l y i n t h e upper p a r t of t h e image where t h e r e i s a s t r o n g r e l i e f
caus ing shadow a reas . In c o n t r a s t t o t h e PC1 image, t h e PC2 image does not show
t h e h igh c o n t r a s t . However, some f e a t u r e s show up c l e a r l y such as pine f o r e s t s
and v a l l e y s wi th orchards . Apparently t h e informat ion con ten t i s t o t a l l y
d i f f e r e n t and ( a s s t a t e d above) one has t o choose the most a p p r o p r i a t e d a t a a s
r equ i r ed f o r t h e purpose of s tudy and t h e p h y s i c a l cond i t ions .
PC1 and PC2 may be shown combined through co lou r coding ( s e e p l a t e 4). Analys is
of t h e s e co lou r coded PC imagery enab le s t h e d e l i n e a t i o n of main landscape
u n i t s and t h e i r c o n t e n t s wi th regard t o land use and n a t u r a l v e g e t a t i o n a t t he
t i m e of a c q u i s i t i o n .
The informat ion con ten t of Fig. 11.11 i s very s p e c i f i c s i n c e i t concerns PC
imagery of one a c q u i s i t i o n d a t e . Therefore , t he boundar ies t h a t can be
i n d i c a t e d i n t h i s f i g u r e do no t have t o co inc ide wi th those of t h e
11.10 where cover by grapes i s i n c r e a s i n g
278
pc2
30 1 - - -I
,---- I
(pq lo + +
I \,+ D1 '-.
I I - 110 120
pc 1
30 40 50 6 0 70 80 90
Fig. 11.10 Feature plane of PC1 and PC2 of ground observations on reflectance in September 1979.
Legend: D1 = grapes covering >80% K1 = wheat stubble fields D2 = grapes covering
E = nat. veg. & grape
F = forest (pine &
20-80% of soil
COV. <20% 0 = orchard, fruittrees
Q. ilex) Y = bare gypsum soils
K2 = bare s o i l s
multitemporal analysis of fig. 11.7. This actually being s o , the main landscape
boundaries can still be delineated although minor deviations do exist.
The deviations must draw the attention of the interpreter. In general
there is an explanation which is often found in the fields of soil surface,
land use and vegetation.
A number of features can be identified in this stage on the basis of
multitemporal combination and knowledge derived from field observations.
Question marks have to be put at places where uncertainty exists on
identification. These places have to be examined in the final field work.
The terrain features of the area were also arranged to test automated
classification. A method was used that minimizes the variance within cluster
with respect to the distances of the objects to the centroids of the clusters.
The results for part of the area are shown in a black- and -white coded image
(fig. 11.12). This type of coding is less expensive with regard to reproduc-
tion. However, colour coding provides much more contrast and is therefore
superior for interpretation purposes. A number of land features were properly
279
Fig. ll.llPC1 (left) and PC2 (right) pictures ohtained by line-printing for the Calatayud area of Landsat MSS data of 17 January 1977 (ID nr. 2-215- 031-040).
classified, a.0. nearly hare gypsiferous soils, forests and orchards. However,
wheat is only partly classified correctly; remarkable is the classification of
the village Munsbrega, which has many white houses, thus resembling a nearly
hare gypsum spot. A correct classification in other classes then the three
mentioned above is hampered and may even be impossible, since there is a great
variation in land use and most fields are small (mean size: 0.6-0.9 ha, that is
close to the ground resolution cel), which makes it very difficult to obtain
pure pixels for a training set. Therefore, many pixels could be classified only
as mixtures of different classes. In this study,'it means that only in those
280
Fig. 11.12
scale app. 0 1 2 km
Automated classification of MSS data of 6 June 1976 of the area near Calatayud, using a clustering method. orchards 8 wheat forests (pine) :: nearly bare gypsiferous soils nat. vegetation 2) nearly bare soils, grapes, nat. vegetation
(low coverage)
parts of the area with sufficient uniform land use units, e.g. the river
valleys and the forested areas, automated classification has been successful.
However, multitemporal approaches will certainly improve the classification
results.
Plate 5 shows the digital classification of this area and its surroundings
in colour.
In conclusion, the following can be stated about interpretation methods.
283
The different photographic and digital products each with their specific
information content have to be studied. The resultant interpretation products
should be compared with each other. Converging evidence may present certainty
in delineation of mapping units. However, in a number of cases, question marks
have to be put on the interpretation maps. These question marks may refer to a
complicated physical structure, to limitations of the spatial and spectral
resolution of the remote sensor or to the lack of terrain knowledge.
The fieldwork comprises the mapping of key areas, the composition of
sample sets and the checking of different mapping units. Furthermore, special
emphasis is laid upon the question marks arisen during the interpretation of
photographic products and/or imagery derived from digital processing.
With the results of the fieldwork, and where applicable automated
classification, a final interpretation is performed and a small scale map is
constructed after field-checking.
11.5. Interpretation of Thematic Mapper (TM) Data
The TM bands are introduced in section 11.2. The main purpose of the TM
was the improvement of spatial and spectral resolution taking the first
generation Landsat MSS as a small-scale mapping tool with limited spectral
potential.
The improvement in spatial resolution is easy to see in fig. 11.13, since dry
gullies and ravines as well as the parcels of arable land are pictured more
precisely by the TM.
The spectral resolution has been improved by the introduction of relati-
vely narrow bands. Besides the statements made by the U.S. Geological Survey
(1982) about the information of TM bands for vegetation, rocks and soil mois-
ture, additions can be made with regard to soil mineralogy (see table 11.5).
An impression of the structure of TM data can be achieved by calculating
the correlation coefficients between the different bands, being an appropriate
technique for multiband data in general.
In table 11.6, this has been done for the bands 1-5 and 7, for two areas in
Tunisia..The correlation coefficients of the Seftimi area are lower than those
of the Kasserine area, suggesting that more information may be obtained by
processing the Seftimi data set. In both areas, the correlation between the
first three bands is high, while also band 5 and 7 show a good correlation.
282
Fig. 11.13 TM band 4 image (a) and first generation Landsat MSS band 7 image (b) of the Kasserine area (Tunisia: Mulders and Epema, 1985). Acquisition: a) 29th January 1983
b) 31St December 1984
Imagery with high information potential may be produced by combination of the
bands 5 OK 7, with band 4 or band 3. Furthermore, highly interesting features
283
Table 11.5. Spectral properties of TM bands.
TM band Wavelength Information on vegeta- Information on soil minera- nr . in um tion, rocks and soil logy by absorption phenomena
moisture (US. Geol. (Mulders and Epema, 1986) Survey, 1982)
1 0.45-0.52 differentation of soil iron oxides from vegetation and deciduous from conife- KOUS flora
vegetation 2 0.52-0.60 green reflectance of
3 0.63-0.69 chlorophyll absorption II 11
4 0.76-0.90 determination biomass
II I I
I, I,
content, delineation of moist areas
moisture content
soil moisture
types hydrothermal silicates mapping
5 1.55-1.75 vegetation and soil gypsum
6 10.40-12.50 vegetation stress,
7 2.08-2.35 discrimination of rock calcite, gypsum and layer
may be extracted by a display of one band and a one band/total intensity ratio
(total intensity = summation of intensity reflective bands that is 1 + 2 + 3 + 4 + 5 + 7 ) . The display of band 5 appeared to be highly sensitive in the
Seftimi area to the classes which were chosen.
Gypsiferous areas could be discriminated by careful selection of classes
(Mulders and Epema, 1986) . The 5 / 4 ratio enabled the indication of areas with a
higher gypsum content within the gypsiferous area. Due to their absorption in
band 5, these areas were characterized by a lower ratio.
Table 11.6 Correlation coefficients between the bands 1-5 and 7 of data sets for the arid Seftimi area (lower left) and the semi-arid Kasserine area (upper right) after Epema ( 1 9 8 6 ) .
1 2 3 4 5 7 1 - .971 .944 .835 .834 .824 2 .928 - .978 .878 .894 .887 3 .972 .978 - .878 .928 .892 4 .622 .778 .790 - .892 ,843 5 .6a2 .812 ,843 .724 - .975 7 .425 .509 .533 .434 ,868 -
The band 5/total intensity ratio image of the Kasserine area produced high
contrast between bare clay soils in a playa and other bare soil surfaces in the
area. The bare clay surfaces showed a low ratio value, which was most probably
284
due to a reduction of the near nadir scattered radiation (received by the TM
sensor) because part of the band 5 radiation was specularly reflected by platy
surface crusts. Owing to the low sun angle at approximately 9:45 a.m. when the
TM passes, this radiation is not detected by the TM sensor.
11.6. Application
Hilwig et al., (1974) concluded in their study on visual interpretation of
Landsat-1 imagery of the M6rida-region (Spain) that this kind of imagery
promises to be very valuable for exploratory surveys (at scales up to
1:500,000), valuable for reconnaissance surveys (at scales up to 1:100,000) and
useful for surveys at scales up to 1:50,000 in conjunction with conventional
aerial photo-interpretation.
Nowadays, Landsat MSS data are applied in numerous surveys, especially in
exploratory and schematic surveys. But also at reconnaissance scales, Landsat
MSS may be used as a valuable aid in the pre-fieldwork stage, since a
multitemporal coverage offers insight in the dynamics of the environment.
However, some coastal areas and parts of the equatorial tropics are so clouded
that it is impossible to obtain images with a low cloud cover. In such areas
low altitude aerial photography and radar have definite advantages.
Furthermore, the low ground resolution and the low equatorial overlap (for
stereoscopic observation) of the first generation Landsat MSS determine its use
to be not competitive with aerial photography. However, TM data proved to be as
valuable as airphotos for reconnaissance mapping of arid areas in that they
offer additional information on soil mineralogy, which as such could not be
interpreted from the airphotos.
11.7. Conclusions and comments
The application of first generation Landsat MSS imagery is found to be
useful in small-scale survey. The cost of Landsat MSS images are low for small-
scale inventory of large areas when compared with those of aerial photographs.
It should be noted, that the degree of detail on Landsat MSS imagery with
respect to landform is much less when compared to that of airphotos.
If only a broad view is needed, a schematic analysis of medium-scale
airphotos in order to indicate only the main landscape boundaries, may be
sufficient. However, the large number of photographs needed to study an
285
extensive area, is a drawback for this approach. Moreover, the synoptic view
and the multitemporal capacity of Landsat are points in favour of its
application for exploratory survey.
A synthesis between interpretation of Landsat MSS imagery and the interpreta-
tion of airphotos of selected key areas is considered to be a proper approach
in small-scale soil mapping. The study of Landsat images of one acquisition
date is generally done for the analysis of static elements: relief, landform,
drainage pattern/density and alignments. For the study of dynamic elements such
as natural vegetation and land use, multitemporal combinations have to be used.
The application of automated processing of Landsat MSS data enables a more
accurate determination of terrain features. Automated classification is
successful, in areas with low variability in land use and crops. The benefit of
automated processing will of course be great when sufficiently large areas are
concerned, e.g. the total area of a Landsat MSS frame (185 x 185 km). Field
checking over such large areas requires much time and finances. To utilize the
higher spatial resolution of Landsat systems, RBV images may be used (38 x 38 m
ground resolution) or TM (Landsat 4-5; 30 x 30 m ground resolution). The latter
may provide specific information on the type of soil surface, making it a
valuable tool for mapping of arid areas or other, large, areas with bare soils.
In par. 14.4 (2b), the French satellite SPOT-1 is mentioned, which offers
a 10 m and 20 m ground resolution, and stereoscopic capability. The first
products (obtained in 1986) show a very good quality, and certainly widen the
application potential of satellite-derived products for environmental mapping.
However, the spectral domain limits itself to the 0.50 - 0.90 m range, leaving the 1.5 - 2.4 um range with its high information potential ( s e e par.
11.5) unique for the TM.
11.8. References
Barret, E.C. and Curtis, L.F., 1976. Introduction to Environmental Remote Sensing. Chapman and Hall, London: 336 pp. Item., 1982: 352 pp.
Bronsveld, M.C. and Luderus, F.J.D., 1982. Analysis of Multi-Temporal Data for the Identification of Land Use and Crops (case study on the Mgrida region in the Province of Badajoz, SW Spain). ITC, Enschede, The Netherlands, IBM Netherlands and Madrid, Vol. I and 11: Vol I 38 pp. App. 34 pp; Vol.
Dethier, B.E., Ashley, M.D., Blair, B.O. et al., 1975. Satellite Sensing of Phenological events. Search Agriculture Vol. 6 nr. 1, New York, 46 pp.
Donker, N.H.W. and Mulder, N.J., 1977. Analysis of MSS digital Imagery with the aid of Principal Component Transform. ITC Journal 1977-3, Enschede, The
I1 45 pp. Vol I.
286
Netherlands: pp. 434-466. Epema, G.F., 1986. Processing of Thematic Mapper data for mapping purposes in
Tunisia. hth ISSS Symposium Working Group Remote Sensing for Soil Survey (1985). ITC Journal, Enschede, The Netherlands.
Goetz, A.F.H., Rowan, L.C. and Kingston, M.J., 1982. Mineral Identification from Orbit: Initial Results from the Shuttle Multispectral Infrared Radiometer Science, Vol. 218: pp. 1020-1024.
Hielkema, J.U, 1979. Advanced Training and Research on Satellite Remote Sensing Techniques and Application in the United Kingdom and the United States. FAO, Rome, AGLT/RSU series 2/79: 111 pp.
Hielkema, J.U., 1980. Remote Sensing Techniques and Methodologies for Monitoring Ecological Conditions for Desert Locust Population Development. FAO, Rome/USAID, CGP/INT/349/USA: 63 pp.
Hilwig, F.W., Goosen, D. and Katsieris, D., 1974. Preliminary Results of the Interpretation of ERTS-1 Imagery for a Soil Survey. ITC Journal 1974-3, Enschede, The Netherlands: pp. 289-312.
Hilwig, F.W., 1979. Selection of Landsat MSS data for Inventories of Earth Resources. ITC Journal 1979-2, Enschede, The Netherlands: pp. 249-266.
Hilwig, F.W., 1980. Visual Interpretation of Multitemporal Landsat Data for Inventories of Natural Resources. ITC Journal 1980-2, Enschede, The Netherlands: pp. 297-327.
Karssen, A.J., 1975. The Production of a Cartographic Colour Chart. ITC-Journal 1975-1: pp. 101-106.
Meer Mohr, H.E.C. van der, 1968. Geological Interpretation of Hyperaltitude Photographs from Gemini Spacecraft. 11th Congr. of the Int. SOC. for Photogrammetry, Lausanne: 6 pp.
Mulders, M.A. and O'Herne, E., 1981. Methodology of Small Scale Soil and Land Use Mapping with Landsat Data. Calatayud Basin (Spain). Int. SOC. of Soil Science. Third Symposium of Working Group "Remote Sensing for soil Surveys" Jablonna, Poland: 30 pp.
Mulders, M.A. and Epema, G.F., 1986. The Thematic Mapper. A New Tool for S o i l Mapping in Arid Areas. hth ISSS Symposium Working Group Remote Sensing for Soil Survey (1985). ITC-Journal, Enschede, The Netherlands.
NASA, Goddard Space Flight Center, 1972, 1976. Data Users Handbook. NASA Earth Resources Program.
NASA, EKOS data Center, 1979. Landsat Data Users Note. Issues No 2 and No 5, May 1979. Sioux Falls, South Dakota.
NASA, 1982. Landsat Data Users Notes Issue No 23 (July). EKOS Data Center, Sioux Falls, USA.
National Academy of Sciences, 1977. Resource Sensing from Space: Prospects for Developing Countries. Washington: 202 pp.
NOAA, 1983. Landsat Data Users Notes Issue No 26 (March), EKOS Data Center, Sioux Falls, USA.
Otterman, J., Lowman, P.D. and Salomonson, V.V., 1976. Surveying Earth Resources by Remote Sensing from Satellites. Geophysical Surveys 2: pp. 431-467.
Short, N.M., 1982. The Landsat Tutorial Workbook. Basics of Satellite Remote Sensing. NASA Reference Publication 1078, Washington D.C.: 553 pp.
US Geological Survey, 1978. Manual on characteristics of Landsat Computer Com- patible Tapes produced by the EKOS Data Center Digital Image Processing System. US Government Printing Office 024-001-03116-7 Washington: 70 pp.
US Geological Survey, 1979. Landsat Sata Users Handbook. Arlington USA. US Geological Survey, 1982. Landsat Data Users Notes, Issue No 23 (July, 1982).
EKOS Data Center, Sioux Falls, S. Dakota: pp. 1-12.
281
11.10. Additional reading
Allen, T. and btham, J., 1980. Landsat orbits in a melting pot. New Scientist 17 April 1980: pp. 144-152.
Campredon, R. Celles, J.C., Le Page, A. et Leprun, J.C., 1982. Essai de Cartographie, GQologique Automatisee d a m un secteur SahQlien, Influence des Facteurs Pedologiques et Phytosociologiques. Bull. SOC. GQol., France, t. XXIV, No. 1; pp. 7-12.
Finch, W.A. Jr., 1973. Earth Resources Technology Satellite-1. Symposium Proceedings September 29, 1972: 165 pp.
Gulinck, H., Gombeer, R. and D'Hoore, J., 1977. Area Measurements in Landsat imagery with Quantimet 720. Microscopica Acta, Supplement 1. Hirzel Verlag, Stuttgart: pp. 71-76.
Gulinck, H., 1980. Recalibration of Multitemporal Dfgital Landsat MSS Data for Atmospheric Interaction. Application to Phenological and Pedological Landscape Studies. Pedologie XXX, 1, Ghent: pp. 89-114.
Hempenius, S.A., 1976. Critical Review of the Status of Remote Sensing. Bildmessung und Luftbildwesen. Heft 1, 44. Jahrgang: pp. 29-41.
LARS, Laboratory for Applications of Remote Sensing and the Agricultural Experiment Station Purdue Univ., Indiana, 1975. Natural Resource Mapping in Mountainous Terrain by Computer Analysis of ERTS-1 Satellite Data. Research Bulletin 919: 124 pp.
Masson, Ph., Chavel, P., Equilbey et Marion, A., 1982. Apports du Traitment NumQrique d'Images Landsat a 1'Etude des Failles Libano-Syriennes. Bull. SOC. Sol., France, t. XXIV, No. 1: pp. 63-71.
Pacheco, R.A. and Howard, J.A., 1977. Application of Satellite Remote Sensing to Landscapes and Soils. ler Colloque PQdologie TQlQdetection AISS, Rome: pp. 109-123.
Reeves, R.G. (ed.), 1975. Manual of Remote Sensing. Vol. I and 11. The American Society of Photogrammetry: 2144 pp.
Vegas, P.L., 1974. Extracting Land Use Information from the Earth Resources Technology Satellite Data by Conventional Interpretation Methods. NASA TND-7730. Lyndon B. Johnson Space Center: 54 pp.
Bijleveld, J.H. and Rosema, A,, 1980. A Study of Satellite Remote Sensing. Application and Mission Objectives in Developing Countries. EARS b.v., Delft, The Netherlands: 164 pp.
288
12.THERMAL INFRARED LINE SCANNING AND RADIOMETRY IN THE INFRARED AND MICROWAVE
ZONES
Hudson (1969) reports about the development of Infrared techniques.
As early as 1910, many workers were intrigued by the potential abilities of
heat seekers and were proposing a wide variety of Infrared search devices. Many
of the basic techniques used today for generating tracking signals, and
suppressing the effects of unwanted backgrounds, were conceived in the 1910
era. In the early 1920's the availability of the thallous sulfide detector
encouraged a new generation of workers to concentrate on Infrared search
devices. Some major events in the development of Infrared techniques were: the
development of the image converter tube in the early 1940's, the lead sulfide
detector in the late 1940's, the development of photon detectors sensitive in
the 3 to 5 !.I m window in the mid 1950's, and of small and reliable cooling
devices in the early 1960's. In the 1940'9, techniques of remote Infrared
sensing were primarily devoted to military applications for such purposes as
fire control, missile guidance, night vision etc. Through extensive efforts by
the military, the technology was advanced to a point where it became
economically feasible to contemplate a wide range of peaceful uses for Infrared
sensors (Schaper, 1976).
Remote sensing in the thermal Infrared is very promising, since it enables
us to fill in the emission properties of natural targets, and we will acquire
data on an important part of the interaction between solar radiation and
objects at the earth's surface.
In chapter 4 (section 4.3), the line-scanner is discussed. This, in combination
with a thermal detector is the common device for remote sensing in the far
Infrared. We will concentrate on this device but also mention the so-called
Infrared imagers, capable of real-time picture presentation. In the chapters 2
and 3, I have discussed various elements of basic physics in connection with
the interaction between solar radiation and materials at the earth's surface,
of which a number of phenomena are important for this chapter. These are:
sections subjects
2.2 radiation laws;
289
2.7
3.1
3.2
3.3
thermal properties;
spectral emissivities rocks and minerals;
thermal data soils;
thermal properties plants.
12.1. Airborne Infrared line scanners and Infrared imagers
Thermal Infrared radiation has a wavelength, somewhat smaller than cloud
drop diameters, and therefore is not able to penetrate cloud cover. It can
however penetrate haze better than Visible radiation due to its longer
wavelength (MacDowall, 1972).
The Infrared line scanners or IRLS (see section 4.3) with their small
field of view (typically between 1 and 5 mRad) operate either in the 3.5-5 m , or in the 8-14 um transmission window. Normally the detectors have to be
cooled, that is to 77 K and 25 K, respectively. The equipment can record
temperature differences either very precisely (e.g. 0.1 K) within a limited
range of temperature, or less precisely (e.g. 1 K) within a wider range.
The radiometric temperature will always be less than the actual
temperature because of reduced emissivity (Fitzgerald, 1974). For example,
quartz shows an emissivity minimum near 9 um . To avoid the emissivity minimum of quartz, a narrow band covering the region 10.4 um to 12.6 um has to be
used for precise measurements (Taylor, 1979).
Lowe (1975) has listed commercially available Infrared scanners: Daedalus,
Reconofax (HRB Singer), Bendix T/M and Siddeley (TRW Hawker). The various
scanners differ in their methods of data recording and their ancillary
equipment as well as in resolution, sensitivity and v/H ratio (velocity/height
ratio).
The Infrared imagers differ from the line scanner in that they scan in two
directions, thus forming an image without the requirement of platform motion.
The AGA Thermovision System 680 operates by two rotating prisms, the Dynarad
201 by oscillating mirrors. Several systems claim spatial resolution of 1.7
mRad and a temperature sensitivity of about 0.1 K. The Infrared Imagers are
well suited for real-time qualitative detection of thermal anomalies. They can
be adapted to aircraft (MacDowall, 1972; see also Borg, 1968).
12.2. Satellite programs
One of the earliest concepts of remote sensing in the Infrared from
290
satellites is the first successful satellite of the Nimbus series.
Many thermal Infrared images with low spatial resolution have been
acquired from meteorological satellites, a.0. ATS (Applications Technology
Satellite), ITOS ( Improved TIROS Operational Satellite), NOAA (National
Oceanographic and Atmospheric Administration) and Meteosat (tables 4.3 and
11.1).
The NOAA satellites circle the globe at an altitude of 1500 km in near
polar orbits. Images of equatorial localities are acquired twice daily: one
during the day and one during the night. Besides thermal Infrared (10.5-
12.5 um ), a separate imaging system is used for coverage in the Visible (0.5-
0.7 pm ). The scanning radiometer of the early NOAA series has a ground
resolution of 4.0 km in the Visible and 7.5 km in the Infrared. However, the
so-called "very high resolution radiometer" of the NOAA series has a ground
resolution of approx. 1 km for both the Visible and Infrared bands (Sabins,
1978).
The Skylab multispectral scanner S-192 (described in table 11.2) acquired
daytime Infrared imagery in the 10.2-12.5 pm band (channel 13) with a ground
resolution cell of 79x79 m.
Landsat 3 (table 4.3) also includes a thermal band (10.4-12.6 um ).
However, at the end of the year 1980, an anomaly appeared in the data being
returned from the Landsat 3 MSS. Because of this, NASA decided not to operate
the MSS on Landsat 3 (NASA, 1981).
The so-called Meteosat programme is the European space Agency's first
meteorological satellite programme (see Lennertz and Pryke, 1978). Meteosat-1
was launched in 1977 and contains two adjacent channels in the Visible (between
0.5 pm and 0.9 pm ), besides two Infrared channels, these being the 5.7-
7.1 pm band and the 10.5-12.5 pm band.
The Heat Capacity Mapping Mission (HCMM) was the first of a series of small
(short-term), relatively inexpensive Application Explorer Missions ( A E M )
conducted by NASA. Compared with Landsat, the orbit accuracy and attitude
stabilization is considerably less precise.
The HCMM or AEM-1 was launched on April 26, 1978. The radiometer aboard
acquired data in two spectral channels, being 0.5-1.1 um and 10.5-12.5 m . The ground resolution was 600 m at nadir, the swath width was about 700 km. The
620 km high near polar orbit of the satellite was sun synchronous with passes
over the USA at approx. 1:30 pm and 2:30 am, closely matching the maximum and
291
minimum daily temperatures of the surface. The earth was covered only within
the range of five receiving stations, thus covering parts of the USA, Europe
and Australia (Lillesand and Kiefer, 1979).
In addition to the four channel MSS of Landsat 1 and 2, the Landsat 4
(launched in July 1982, table 4.3) carries an advanced multispectral scanner;
the so-called Thematic Mapper (TM). Besides bands in the Visible and the Near
Infrared, the TM has one band in the far Infrared (10.4-12.5 um), which has a
120 m resolution.
12.3. Characteristics of airborne thermal Infrared imagery
Geometric distortions due to the large scan angle and aircraft motion as
well as the effect of surface winds on thermal imagery are discussed briefly in
section 6 . 4 .
Below I will explain some density differences that may be observed on
thermal imagery ( s e e also Bennema, 1972). An example of thermal imagery of
grassland near Uithoorn at the Amstel river in the Netherlands is given in fig.
12.1; it concerns a day-time image.
A gully pattern is clearly marked in the grassland. The gully is cold (moist)
and shows relatively warm borders (due to their dry position). The contrast
between the grassland parcels is determined by the grass coverage: a dense
cover means a low temperature. The white (warm) parcels have been intensely
grazed and had a low density cover at the acquisition date. The ditches are
colder than their SuKKoundingS, but the walls which are sunlit have been warmed
up in the preceding hours and appear white on the image.
Thermal images record the pattern of heat radiated from materials,
something which the human eye is not capable of doing. The momentaneous
radiometric temperatures of the interfaces of, respectively, soil and plant
with air are registered, the first being strongly influenced by soil properties
such as moisture condition of the topsoil and roughness of the soil surface,
the second by crop OK natural vegetation properties, and in case of a low
vegetation cover, also by soil properties.
For a dense vegetation cover e.g. grown crops or dense grassland, signal
strength is determined by evapotranspiration of crops, which is related to the
available soil moisture and the actual weather conditions.
Fig. 12.2 contains thermal imagery of 15 March 1973 of the Agricultural Station
at the Haarweg, Wageningen, The Netherlands. The crops grown at the
292
Fig. 12.1Day-time thermal image of grassland near Uithoorn, n a m e s Binnenpolder at the Amstel (The Netherlands); acquisition date: July 1976, 2:OO pm.
293
Fig. 12.2 Thermal imagery of 15 March 1973 of the Agricultural Stat ion a t the Haarweg, Wageningen, The Netherlands.
294
acquisition date are given in fig. 12.3.
Image quality appears to be strongly dependent on the meteorological conditions
(table 12.1).
Fig. 12.3 Agricultural Station at the Haarweg, Wageningen, The Netherlands on 15 March 1973.
Experiments: g = grass g= = grass and clover g' = grass experimental field J = winter wheat ws - winter wheat (sprinkler irrigation) rs b - bare soil 1,2,. = field numbers
- winter rye (sprinkler irrigation + strips of bare s o i l )
Except for the evening, image quality is good. Influence of wind is most
visible in the morning and evening imagery.
For a characterization of the grey tones on the images, the N-scale of the
Standard Soil Colour Chart (Fujihira Industry Co, Ltd, Tokyo, Japan) was used:
1 - black N 1/0 4 - dark grey N 410
2 - black N 2/0. 5 = grey N 5/0
3 = greyish black N 3/0 6 = grey N 610
7 = greyish white N 7/0
8 = greyish white N 8/0
9 = white
The grey tone differences are related to thermal differences and therefore can
be used for a qualitative signature.
295
Table 12.1 Meteorological data Observing Station Deelen at a distance of approx. 17.5 km of the Haarweg (Wageningen) on 15 March 1973.
time of weather surface air rel. hum. low cloud turbulence observat- last 3 hrs wind temp . ion speed
05.00 am groundfog 8 Kts 0°C 97 x stratus NIL increasing 6/8 cloud cover 400 ft
11.30 am hazy 12 Kts 8.4"C 53 X cumulus light- 1 /8 moderate 3000 ft
21.00 pm increasing 5 Kts 3.0"C 69 Z strato NIL cloud cover cumulus less than 3500 ft 4/8
Further information: the precipitation in the preceeding 12 hrs was NIL and the earth's surface condition was DRY.
In Table 12.2 the grey tones have been indicated for the different fields as
given in Fig. 12.3.
Grassland has a qualitative signature 5-7/3-6/9-7 (intermediate-warm/inter-
mediate-cold/warm) different from that of winter rye with 6/2/9 (intermediate/-
cold/warm) and winter wheat with 21'6-8/7 (cold/intermediate-warm/warm) OK
winter wheat/sprinkler irrigation with 2/5-6/4 (cold/intermediate/-
intermediate). The qualitative signatures represent the early morning/just
after noon/evening grey tones. For bare land there are different signatures,
which are related to differences in soil surface texture, tillage or summer
crop. Most surfaces have a clay texture and show a signature 2/3-9/dominantly
7-8 (cold/cold-warm/warm. Differences in thermal behaviour, especially just
after noon, may be related to different tillage practices or summer crops. The
soils were moist enough to produce thermal radiation in the evening, but in the
early morning they were colder than grassland. Bare land with a sandy texture
deviates in producing a signature 2/2-6/2 ( co ld / co ld - in t e rmed ia t e / co ld ) . The
upper part of soil is apparently dry and impedes radiation from, or into the
soil. From the examples given, it will be evident that much specific knowledge
is required for the interpretation of thermal imagery.
12.4. Thermal models
Thermal measurements are relatively accurate and enable the indication of
296
Table 12.2 Grey tones of 21 fields of the Agricultural station at the Haarweg (Wageningen, The Netherlands).
field relative thermal condition at different acquisition land use number times; grey tones 1-3 relatively cold, 7-9 relative-
ly warm, 4-6 intermediate condition
5 : 2 3 - 6 : 4 2 hrs 1 2 : 0 9 - 1 3 : 4 3 hrs 2 1 : 4 0 - 2 3 : 0 0 hrs
1 5(+7) 3(+4) 9(+7 +4) grassland 2 5(+7) 5(+4) 9(+a) grass experi-
3 7 (+6 ) 6(+5 +4) 9 (+a ) grassland 4 2 4 7 bare land 5 5 6(+4) ~ + 7 ) grass and
6 2 4 7 bare land 7 2 8 7 winter wheat +
bare land 8 2 a 7 bare land 9 2 a 7 bare land
10 2 6 7 winter wheat 11 2 3 4 bare land 12 2 8 8 bare land 13 2 8 ( + 9 8 (+7 ) bare land 14 2 6(+5 +4) 7 (+8 ) bare land 15 7 (+5 ) 3(+5) 9(+8) grassland 16 6 2 9 winter rye
mental field
clover
(sprinkler irr. + bare soil)
17 2 6 2 bare land 18 2 6 4 wint erwhea t
(sprinkler irr.)
19 2 2 2 bare land 20 2 2 2 bare land 21 2 5 4 winter wheat
(sprinkler irr .)
small differences in vegetation morphology and coverage, soil roughness, soil
moisture and porosity. Generally, the purpose of the research is to obtain
insight in the thermal condition of objects at the earth's surface, rather than
the identification of the objects, which is best done with the aid of Visible
and near Infrared radiation.
Thermal data are used at different scales of mapping. At small scales, an
overall view may be obtained from the thermal condition of complex land units.
At large scales, single land units or objects are recognized individually.
Surface temperatures of units such as parcels with annual crops can be
calculated from the thermal radiation received by the detector. These and other
297
data, as input to thermal models, may yield evapotranspiration estimates, and
subsequently, estimates on soil moisture pressure.
Natural objects show a lower emittance than a black body. Combining the
formulae 2-4 and 2-5, the emittance of natural objects (M in Wm-’) is given by:
4 M = E U T
where E = emissivity,
u = Stefan-Botzmann’s constant (Wm-2K-4),
T = temperature (K).
(12-1)
The thermal Infrared is absorbed strongly by the atmosphere (fig. 2.12) .
However, windows are found between 3 um and 5 um and between 8 m and
14 um . In the day-time the first window also shows contribution of solar
radiation (fig. 2-4), the second is practically free of solar radiation and is
therefore generally used. Apart from absorption, the atmosphere itself acts as
a source of thermal radiation.
In calculating the crop surface temperature from remote sensing data, the
influence of different atmospheric layers can be evaluated as follows
(Nieuwenhuis, 1979): the radiance at the top of layer n (M”) is equal to the
emittance of layer n, augmented by the amount of transmitted radiance derived
from layer n-1, therefore:
where Tbc = equivalent black body crop surface temperature (K),
T = transmittance.
Neglecting P and M in formula 2-32, the energy balance equation is as follows:
Rn = S + A + LE (12-3)
where S
A
LE = evapotranspiration OK latent heat flux into the air (w~a-~).
= heat radiation from, or into the soil (Wm-’),
= heat radiation from, or into the air (Wm-’),
R~ (the net radiation) can be split up into a net short-wave and a net long-
wave radiation term (Nieuwenhuis, 1981):
298
4 Rn = (1 - p ) Rs + E (R1 - 0 T ) ( 12-4)
where Rs = incoming short-wave radiation flux (Wm-2),
p = CKOP*S reflectance,
E = crop's emissivity (section 2.2),
R1 = long-wave sky radiation flux (W~I-~),
u = Boltzmann constant,
Tc = crop surface temperature.
Considering a crop surface with a temperature Tc ( K ) which transports heat up
to a certain height above the surface through a column of air with temperature
Ta ( K ) , the transport equation can be expressed as (Nieuwenhuis, 1981):
Ta - Tc A = - d C -
'ah ( 12-5)
where d
C
rah= turbulent diffusion resistance of the atmosphere for heat transport
(s.rn-') as determined by wind velocity, atmospheric stability and
the height and roughness of the crops.
= density of moist air (Kg r3), = specific heat of moist air (.J.Kg-lK-l),
P
Combining the equations 12-3, 12-4 and 12-5 the relation between LE and Tc can
be found (Soer, 1980):
( 12-6)
The momentary evapotranspiration has to be converted into 24 hr estimates
of evapotranspiration. This can be done by the so-called Tergra-model (Soer,
1977). Subsequently, the moisture condition of the soil (soil moisture
pressure) can be estimated from the evapotranspiration rate (Soer, 1980). This
method has been applied successfully to obtain data about soil moisture
pressure in the root zone of grassland, but may also be practised for other
conditions. However, problems may arise when plants are in a recovery period
(after being stressed) before the normal water uptake and the transpiration
proceed (Jackson, 1982). Moreover, if the rootzone cannot be adequately
specified, the data obtained refer to the soil moisture availability rather
than the soil moisture pressure in the rootzone.
299
Price (1982) discusses the estimation of regional evapotranspiration through
analysis of satellite thermal infrared (HCMM) data. The following steps are
indicated:
- correction of the data for atmospheric effects which are related to the
water-vapour content;
- preliminary estimation of LE;
- correction of LE through the use of a numerical simulation model, the
Tell-US model.
The Tell-US model is presented by Rosema (1978). He used the following
eq ua t i ons :
- the transient heat flow equation for a homogeneous soil
2 2 dT/dt = a d T/dZ ( 12-7)
where T = soil temperature (K),
t = time ( s ) ,
Z = depth (m),
a = A/C , a = soil thermal diffusivity (m2 s-'),
A = soil thermal conductivity (Wm-lK-l),
C = volumetric heat capacity of the soil (Jm-3K-1);
- The surface heat balance equations a.0. LE in the case of bare soil
LE = dL (sa - h. go) / ra ( 12-8)
where L = heat of evaporation (J Kg-l),
= specific vapour density at height Za, sa h = surface relative humidity,
go d
ra
= saturated specific vapour density at the surface,
= density (Kg m -3 ),
= turbulent diffusion resistance for heat transport ( s m-').
300
A simulation model of the daily course of the soil surface temperature and
heat balance is used.
Atmospheric stability is important. Due to the relatively high stability of the
atmosphere at night, there is a high correlation between the surface
temperature and the thermal inertia of soils. In the day-time, due t o
atmospheric instability, the surface temperature largely depends on the level
of evaporation, i.e. on the surface relative humidity, or crop resistance. The
so-called Tell-us interpretation algorithm solves the thermal inertia P (2-29)
and the surface relative humidity (h) and additionally determines the daily
evaporation total. Look-up graphs, such as the one given in Fig. 12.4 are used
for their determination.
Tell-us (originally developed for bare soil surfaces) uses two remotely
sensed surface temperatures, close to the daily maximum and minimum
temperatures and needs only a few place-dependent input parameters, and seems
therefore operationally attractive.
However, Huygen (1979) points to problems related to the application of
Tell-us to vegetated surfaces. For more information on the Tell-us model, the
reader is referred to Klaassen and Rosema (1979) and Huygen et al. (1979) .
Estimates on thermal inertia are often used as a discriminating criterion
between different soil types. In studying various soil surfaces, I’ratt (1979)
found differences in thermal inertia between different soils having the same
volumetric moisture content. Apart from its dependency on the soil moisture
content, the thermal inertia appears to be strongly dependent on the porosity.
Soils with a different porosity but the same moisture content vary strongly in
their thermal inertia values (see fig. 12.5).
For the estimation of the thermal inertia, Pratt (1979) uses two primary
values, being: the maximum diurnal temperature difference of the soil surface
( AT ) and the albedo of the soil surface (A), which are both correlated to
soil moisture content, texture and structure (porosity), and may be estimated
from a remote distance. The value of thermal inertia is then estimated, using a
calibration chart (see fig. 12.6). The chart is calculated from model slmula-
tion of the diurnal temperature variations for a given set of meteorological
conditions.
12.5. Interpretation of thermal data.
There are three basic approaches in the handling of thermal data, namely
301
322
31e
LL 314
VI L 1
0 1 310 m 7
v
? 306 3 c,
m L W
W c,
302
n 3 298
294
291
l i n e s o f equal - - P
h - _ _ - - .. . . . . . . . . . . . . .
:/\ I
d a i l y evap.
Night t e m p e r a t u r e (26.30 h r s ) K
Fig. 1 2 . 4 . Look-up graph March 5, 1971 Avondale loam, Phoenix (Arizona) after Rosema (1978) . Courtesy of the European Space Agency.
the application of thermal models ( s e e Sabins, 1978), the empirical approach
and the physical explanation assisting the visual interpretation of thermal
imagery. With the Terga model, SOeK (1980) derived simulated crop surface
temperatures that agree well with the actual temperatures measured (for
grassland in the Netherlands). The calculated evapotranspiration rates were
compared with those derived from water balance estimates, the differences being
within 30 percent accuracy.
Rosema (1978) reports about results obtained from a bare soil test plot,
consisting of so-called Avondale loam (US Water Conservation Laboratory,
Phoenix, Arizona). The interpretation algorithm discussed in the previous
section ( 1 2 . 4 ) has been applied to this data set. A good correspondance was
302
P 100 % sand
S 0
-v v) 0
.r
.r
n 5 V
7
.r 0 m
100% c l a y
@ - ~ o r o s i t y=30 %
P 100 % sand
100 % c l a y
M o i s t u r e Conten t (m3m3)
@Poros i ty=50 %
P
0 -Poros i t y=40 %
P
I I
0.1 ' 0 . 3 ' 0.5 Mo is tu re Content ( m 3 P )
t - P o r o s i t y = 6 0 %
Fig. 12.5 Thermal inertia (Jm-2s-fK-1) simulation of soils with a variable clay/sand ratio and moisture content for porosities ranging in value from 30 to 60 percent after Pratt et al., (1979) .
found between average soil moisture content of the top 7 cm of soil and the
average soil moisture content determined with the Tell-us algorithm. However,
the daily evaporation according to the Tell-us algorithm was somewhat under-
estimated.
Huygen and Reiniger (1979) have tested the Tell-us model for the
conditions of a catchment area in the UK (Grendon). They met two problems
concerning the model, being: the numerical value of the soil heat capacity and
303
4000
3000
2000
1000
0.2 0.4 0.6 0.8
A1 bedo
Fig. 12.6 Thermal inertia calibration model to calculate thermal inertia values from maximum diurnal temperature difference ( A T ) and albedo values after Pratt e.a. (1979); wind speed 2.5 m s- , surface roughness 0.001 m, radiative sky temperature - 13"C, air temperature 15-25°C.
the assumption of a constant surface relative humidity.
The night surface temperatures proved to be sensitive to the (high) heat
capacity value employed. The soil temperatures simulated with a relatively high
soil heat capacity were lower than the "correct" values, the difference ranging
from 1.3"C for a water-saturated soil to 2.7"C for an air-dry soil.
For the rather moist atmosphere in Grendon, condensation will have its effect
on surface temperature. However, condensation is not included in the model when
calculating the cumulative evaporation.
Huygen and Reiniger (1979) suggest corrections for these problems and conclude
that the use of simulation models and the look-up tables they produce should
always be accompanied by a proper examination of the assumptions inherent to
the models.
The empirical approach involves a correlation between image signatures and
304
the corresponding ground features without a direct consideration of the
underlying physical causes. The thermal imagery in this approach is interpreted
visually, or the interpretation is done with the aid of densitometric
measurements. Image enhancement may be achieved by density slicing. An example
of the empirical approach is discussed in par. 12.3.
One may also use physical explanation to assist the visual interpretation.
Bijleveld (1977) applied this interpretation method on thermal images of an
area in Zeeuws Vlaanderen (The Netherlands). The images were acquired at four
points of time within 24 hrs.
Particularly in the day-time, temperature differences in images can be seen
between one parcel and another, which may be due to differences in surface
roughness.
The surfaces covered with vegetation, apart from the tree-covered areas,
exhibit a large diurnal amplitude of the Surface temperature.
Part of the area is clearly discriminated from the rest of the area in showing
lower temperatures of bare soil surfaces at night and higher temperatures
during the day-time. The soils in this part are dry sands rich in quartz.
During the day-time the dry quartz sand of the bare soil generally develops a
higher real temperature and radiative temperature than moist clay deposits (the
sand has a high reflectance but a low absorptance when dry).
At night the sandy surface develops a real temperature lower than its
surroundings; the difference in radiative temperature may be even larger than
that in real temperature, considering the relatively low emission coefficient.
Quartz has a low emission coefficient when compared to clay, feldspar, humus or
water.
Thus, a bare soil surface that has a higher radiative temperature than its
surroundings during the day and a lower one at night is generally a dry surface
and is very likely to be a sandy surface.
Compaction of soil may be detected by IRLS (Janse, 1973), since it
produces a higher thermal conductivity and density. Although the specific heat
of compacted soil is lower, mainly due to a lower water content (see table
3.1), the thermal inertia (2-29) will be higher, assuming the surrounding soil
to contain about 20 % air and 20 % water. In this case, the compacted soil will
have a relatively low temperature at 14:OO a.m., since much heat is transported
downwards, but it also shows a relatively low night temperature the latter as a
305
result of the high rate of heat transfer at the compacted soil surface.
It is possible that IRLS may provide a new soil-mapping tool in arid
areas. This may be true when the surface conditions as influenced by tillage or
range management are identical over large areas.
Otterman et al., (1975) described a case where management was important. They
studied albedo and temperature of nearly bare ( < 25 Z vegetation cover)
overgrazed areas and nearby areas with a vegetation coverage between 25 Z and
80 Z respectively, in the Sinai/Gaza strip and in the Negev. The overgrazed
soil has a very high albedo in contrast to the vegetation covered soil. The
latter is affected in a significant way by dark vegetation debris littering the
surface. The protected site was measured to have summer afternoon temperatures
which are some six degrees higher than those of the bright, protected side. The
higher radiation temperatures on the vegetated site are an indication that the
evapotranspiration and thermal inertia of the green biomass in this study area
do not affect appreciably the thermal flux, which is actually dominated by the
albedo differences. This is supported by the results obtained by Saltzman and
Ashe (1976). They found that the diurnal temperature range at the surface is
most sensitive, on a percentage basis, to the conductivity of the soil and to
the surface albedo, in that order; quite sensitive to the emissivity and less
sensitive to the water availability factor for evaporation.
With regard to the phenomena studied, Saltzman and Pollach (1977) state the
following: the high temperatures and "darkness" of the Negev are caused by
plant debris with conductivities closer to that of soil, than to live
vegetation.
12.6. Application of thermal Infrared line scanning
Hudson (1969) presented a summation of applications of Infrared techniques
of which I will only give a selection.
Apart from military, industrial and medical applications there is a broad
application field in Earth Resource Surveys a.0.:
- remote sensing of weather conditions;
- determination of constituents of the atmosphere;
- measurement of the earth's heat balance;
- terrain analysis a.0. in volcanic areas;
- detection of water pollution;
306
- sea-ice reconnaissance;
- detection of forest fires.
Van Dijk et al., (1971) did not find an unambiguous correlation between
temperature measurements at 1.5-2.0 m below the soil surface and the 1nfrar.ed
line-up of an area in Oman. The temperature variations found by remote sensing
could only be related to superficial effects of surface features and to the
presence of shallow groundwater. This limits the possibilities for geological
application of IRLS. However, they expect interesting application fields for
the detection of surface salt-domes and large structural depressions.
Very interesting applications are found in the field of agriculture a.0.: - the estimation of evaporation over large areas;
- study of microclimate and the location of night frost areas;
- the study of soil temperature and soil moisture condition;
- detection of diseased crop areas and extend of soil salinity (see
Myers et al., 19615).
Furthermore, thermal data (e.g. Landsat 4 ) may be used in combination with
Visible and near Infrared data, to improve differentiation of land cover types
(Ormsby, 1982) .
12.7. Non-imaging sensing in the Infrared and passive Microwave sensing.
Infrared radiometers (see also section 4.3) operate in the following way:
the radiant flux of an area is measured and compared with the energy from a
black body source of a known temperature. By this comparison, the absolute
temperature can be obtained rather accurately.
Fig. 12.7 represents schematically the elements of a radiometer. In this
figure, the primary optical system is shown as a refractive element, but
reflective systems are more widely used.
The wavelength range is controlled by a filter or a combination of a filter and
other optical elements. The modulator, or chopper, causes the detector
alternately to look at the target and then to check the internal reference. The
output of the detector is a chopped alternating electrical signal, the
amplitude of which is related to the radiance difference between the target and
the reference.
307
Radiation reference Object Image o f f i e l d s top
plane i n ob jec t plane Primarv I I
A- - __--- ten1
Fig. 12.7 Elements of a radiometer after Lowe (1975) . (Used by permission of Am. Soc. for Photogrammetry and Remote Sensing.)
The radiometer records the radiant temperature measured along a narrowwidth
path on the ground. At any instant in time, the radiometer senses the thermal
radiation within its instantaneous field of view (IFOV or R ).
A small I F O V is desirable for high spatial detail. On the other hand, the great
quantity of energy, which is obtained by a large I F O V , permits more sensitive
temperature measurements and thus an improvement of radiometric resolution can
be expected.
An example of a thermal radiometer is the Barnes Model PRT-5, which operates in
the 8 to 10 pm band. For aircraft use it is supplied with a 2.5 mrad I F O V . It
has a temperature range of -50°C to i 1 5 0 " C and responds to temperature changes
as small as 0.1"C (Lillesand and Kiefer, 1979).
Passive Microwave sensors exist both in the form of radiometers and
scanners. The basic configuration of a Microwave radiometer includes an antenna
with a large beamwidth. The antenna signal is alternately sampled together with
a calibration temperature reference signal. The low strength antenna signal is
amplified and compared with this reference signal. The difference between these
308
signals is electronically detected. A scanning device, the so-called "Naval
Weapons Center High Resolution Microwave Imaging System" has been developed.
The product of this system is an image which bears a marked resemblance to
thermal imagery. Estes et al., (1977) report about passive microwave imagery
obtained by this scanner from a flying-height of 760 m. Density measurements on
the basis of this type of imagery have been found to relate quite
systematically to the moisture content of the topsoil.
During the past decade there has been a significant interest in
investigating the potential of Microwave radiometry to obtain information on
soil moisture. The effect of moisture on the dielectric constant of soil, the
response of microwave sensing to soil moisture, the effect of soil surface
roughness, as well as the masking effect of vegetation to the respons of the
underlying soil have been investigated. The results indicate that passive
microwave measurements using wavelengths from a few cm down to 21 cm ( 1 , 4 GHz)
can only indicate the effect of soil moisture to very shallow depths, being
approximately 2 cm. Furthermore, the Microwave brightness temperature
measurements of bare soil indicate that, when roughness increases, the
sensitivity to soil moisture decreases. The effect of the roughness on the
measurement sensitivity is dependent on the wavelength of the EMR used for
detection (Newton et al., 1982). Using a model with roughness correction, Burke
and Schmugge (1982) found a more sensitive response to soil moisture content of
bare soils at a wavelength of 21 cm, than at either 2.8 cm or 1.67 cm. In
studying wheat and alfalfa fields, the 21 cm radiation provides soil surface
moisture information as it penetrates through the vegetation layers. At the
shorter wavelengths of 2.8 and 1.67 cm, the vegetation controls the overall
microwave signature, since the short wavelength radiation cannot penetrate
through the vegetation canopy.
The investigators of test-flights on radiometry often spend much time in
determining the relation between the sensor output and the ground scene. Which
particular object in the ground scene produced the response in the sensor
output? To overcome this problem, Epler and Merrill (1969) describe the use of
a movie camera aligned in such a way that the optical axis nearly coincides
with the radiometer bore sight, and the camera field of view includes the
complete boresight path.
On each image, fiducial marks are fixed with respect to the camera optical axis
309
and serve as a reference for all measurements on the images.
12.8. Conclusions
Infrared line scanners, Infrared imagers and Infrared radiometers are the
instruments for sensing the thermal Infrared, using airborne or spaceborne
platforms. The HCMM of 1978 gave an impetus to the modelling of thermal
processes at the earth's surface.
Some models use one remotely sensed surface-temperature, close to the daily
maximum, and need a large number of place-dependent input parameters. However,
the Tell-us model uses two remotely sensed surface-temperatures close to the
daily maximum and minimum temperatures and needs only a few place-dependent
input parameters.
The use of simulation models and the look-up tables they produce, should be
accompanied by a proper examination of the assumptions inherent to the models
to avoid misinterpretation.
It is clear that much specific knowledge is required for the interpretation of
thermal data. Furthermore, the data are very sensitive to physical surface
properties and may reveal much information on this topic. The use of airphotos
e.g. false colour, or true colour airphotos in a complementary way is advised.
There is a wide field for application of Infrared techniques of which
agricultural applications such as evaporation studies are very promising.
Passive microwave sensors were originally characterized by a low spatial
resolution. However, recently scanner devices became available which offer an
important improvement with regard to this aspect.
I am well aware of the fact that the present text on thermal data is only
an introduction to this subject and consequently an extensive list is produced
on additional reading to indicate ways of further study.
12.9. References*
Bennema, J., 1972. De toepassing van Luchtopnames in de Bodemkunde. Landbouw-
Borg, S.B., 1968. Thermal Imaging with Real Time Picture Presentation. Applied kundig Tijdschrift 84ste jaargang nr 1: pp. 6-14.
Optics, Vol. 7, no 9: pp. 1697-1703.
* see also chapter 3.
310
Burke, H.K. and Schmugge, T . J . , 1982. E f f e c t s of va ry ing S o i l Mois ture Contents and Vege ta t ion Canopies on Microwave Emissions. IEEE Trans. on Geoscce and Remote Sens ing , Vol GE-20, No 3: pp. 268-274.
B i j l e v e l d , J .H . , 1977. Thermal I n f r a r e d Scanning f o r t h e Survey of Quaternary Geology. “ A T e s t i n an A g r i c u l t u r a l Area”. NIWARS publ. No 39, D e l f t , The Nether lands : 88 pp.
D i jk , C. van, Mulder, C . J . , Po ley , J.Ph. and S teven inck , J. van , 1971. Exp lo ra t ion f o r ( sha l low) Geo log ica l S t r u c t u r e s wi th t h e Thermal I n f r a r e d Imagery Technique i n some Deser t Areas of Oman. 7 th Symposium on Remote Sens ing , Michigan: pp. 2115-2131.
Epp le r , W.G. and Merrill, R.D., 1969. R e l a t i n g Remote Sensor S i g n a l s t o Ground- Tru th Informat ion . Proc. of t h e I E E E , Val 57, No 4 A p r i l 1969: pp. 665- 675.
E s t e s , J .E . , Mel, M.R. and Hooper, J . O . , 1977. Measuring S o i l Mois ture w i t h and Airborne Imaging P a s s i v e Microwave Radiometer. Photogrammetric Engineer ing and Remote Sens ing , Vol. 43, No. 10: pp. 1273-1281.
F i t z g e r a l d , E., 1974. M u l t i s p e c t r a l Scanning Systems and t h e i r P o t e n t i a l App l i ca t ion t o Earth-Resources Surveys. S p e c t r a l P r o p e r t i e s of Ma te r i a l s . ESRO CR-232, N e u i l l y , France: 231 pp.
Hudson, R.D. Jr., 1969. I n f r a r e d System Engineer ing . John Wiley & Sons, New York, London: 642 pp.
Huygen, J. and Re in ige r , P., 1979. A T e s t of t h e Tel l -us Model f o r t h e c o n d i t i o n s of t h e Grendon T e s t S i t e . Te l l -us News le t t e r 8. J o i n t Research Cen t re , I s p r a , I t a l y : 16 pp.
Huygen, J., 1979. F u r t h e r Developments of t h e Te l l -us Model. Te l l -us News le t t e r 11, J o i n t Research Cen t re , I s p r a , I t a l y : 17 pp.
Jackson , R.D., 1982. S o i l Mois ture I n f e r e n c e s from Thermal - Inf ra red Measurements of Vegeta t ion Temperatures. IEEE Transac t ions on Geoscience and Remote Sens ing , Vol. GE-20, No 3: pp. 282-285.
J anse , A.R.P., 1973. Toepassing van Warmteheelden. Landbouwkundig T i j d s c h r i f t 85-6, The Nether lands : 10 pp.
Klaassen , W. and Rosema, A., 1979. G e n e r a l i s a t i o n of t he Tel l -us Model t o Vegeta ted Sur faces . EARS bv. D e l f t , The Nether lands : 18 pp.
Lennercz, D. and Pryke, I., 1978. The E a r t h Observa t ion Programme of t h e European Space Agency. Proc. of I n t . Conference on Ea r th Observa t ion from Space and Management of P l a n e t a r y Resources , Toulouse 6-11 March 1978, ESA SP-134: pp. 163-176.
L i l l e s a n d , T.M. and Kie fe r , R.W., 1979. Remote Sens ing and Image I n t e r p r e t a - t i o n . John Wiley & Sons, New York: 612 pp.
Lowe, D.S. ( a u t h o r - e d i t o r ) , 1975. Imaging and Nonimaging Sensors . Chapter 8 i n Manual of Remote Sensing (ed . R.G. Reeves) Amer. Sac. of Photogrammetry, F a l l s Church, V i r g i n i a : pp. 367-397.
MacDowall, J., 1972. A Review of S a t e l l i t e and A i r c r a f t . Remote Sens ing Ins t rumen ta t ion . 1st Canadian Symposium on Remote Sens ing , Ottawa, 7 February 1972: pp. 39-68.
Myers, V . I . , Asce, M . , Can te r , D.L. and R i p p e r t , W . J . , 1966. Remote Sens ing f o r Es t ima t ing S o i l S a l i n i t y . J o u r n a l of t h e I r r i g a t i o n and Drainage Div i s ion . Proc. of t h e Amer. SOC. of C i v i l Eng. I R 4: pp. 59-69.
NASA US Geol. Survey, Eros Data Cen te r , 1981. Landsat Data Users Notes. I s s u e No 16 January 1981.
Newton, R.W. e.a. , 1982. S o i l Mois ture In fo rma t ion and Thermal Microwave Emission. IEEE Trans. i n Geoscce and Remote Sens ing , Vol. GE-20, No 3: pp. 275-281.
Nieuwenhuis, G. J . A . , 1979. In f luence of atmosphere on t h e r m a l i n f r a r e d r a d i a t i o n . Nota ICW 1159, Wageningen, The Nether lands .
Nieuwenhuis, G . J . A . , 1981. App l i ca t ion of HCMM S a t e l l i t e and Ai rp lane Ref l ec t -
311
t i o n and Heat maps i n Agrohydrology. ICW Techn. B u l l 122, Wageningen, The N e t h e r l a n d s o r Adv. Space Res. Vol 1, COSPAR: pp. 71-86.
Ormsby, J.P., 1982. The u s e of Landsat-3 Thermal Data t o h e l p d i f f e r e n t i a t e Land Covers . Remote S e n s i n g of Environment 12, E l s e v i e r Scce. Publ . Co, New York: pp. 97-105.
Otterman, J . , W a i s e l , Y. and Rosenberg , E., 1975. Western Negev and S i n a i Ecosystems: Comparat ive Study of V e g e t a t i o n , Albedo and Tempera tures . Agro-Ecosystems 2. E l s e v i e r S c i e n t . Publ . Cy, Amsterdam: pp. 47-59.
P r a t t , D.A. and E l l y e t t , C.D., 1979. The Thermal I n e r t i a Approach t o Mapping o f S o i l M o i s t u r e and Geology. Remote S e n s i n g of Environment 8, E l s e v i e r Nor th Hol land: pp. 151-168.
P r i c e , J.C., 1982. E s t i m a t i o n of R e g i o n a l S c a l e E v a p o t r a n s p i r a t i o n t h r o u g h A n a l y s i s of S a t e l l i t e T h e r m a l - I n f r a r e d Data . I E E E Trans . on Geosc ience and Remote S e n s i n g , Vol GE-20, No 3: pp. 2A6-292.
Rosema, A. , 1978. The A p p l i c a t i o n of Thermal I n f r a r e d Remote S e n s i n g Data t o S o i l M o i s t u r e and E v a p o r a t i o n D e t e r m i n a t i o n . J o i n t ESA/FAO/I!MO I n t . T r a i n i n g Course i n S a t e l l i t e Remote S e n s i n g A p p l i c a t i o n s i n Agroc l imato logy and Agrometeorology, FA0 Rome: 19 pp.
S a b i n s , F.F. Jr., 1978. Remote S e n s i n g . P r i n c i p l e s and I n t e r p r e t a t i o n . W.H. Freeman and Cy. San F r a n c i s c o : 426 pp.
Sa l tzman, B. and Ashe, S . , 1976. The V a r i a n c e of S u r f a c e Temperature due t o D i u r n a l and Cyclone-sca le Forc ing . T e l l u s 28: pp. 307-322.
Sal tzman, R . and P o l l a c k , J . A . , 1977. S e n s i t i v i t y of t h e D i u r n a l S u r f a c e Tempera ture Range t o Changes i n P h y s i c a l P a r a m e t e r s . J o u n a l of Applied Meteoro logy , Vol. 16: pp. 614-619.
Schaper , P.W., 1976. I n f r a r e d S e n s i n g Methods. In : Remote S e n s i n g f o r Envi ronmenta l S c i e n c e s . S p r i n g e r - V e r l a g , B e r l i n , H e i d e l b e r g , New York: pp. 84-109.
S o e r , G . J .R . , 1977. The T e r g r a Model, a M a t h e m a t i c a l Model f o r t h e S i m u l a t i o n of t h e D a i l y Rehaviour of Crop S u r f a c e Tempera ture and Actua l E v a p o t r a n s p i r a t i o n . NIWARS p u b l . 46, D e l f t , The N e t h e r l a n d s .
S o e r , G.J .R. , 1980. E s t i m a t i o n of R e g i o n a l E v a p o t r a n s p i r a t i o n and S o i l M o i s t u r e C o n d i t i o n s u s i n g Remotely Sensed Crop S u r f a c e Tempera tures . Remote S e n s i n g of Environment 9, E l s e v i e r N o r t h Hol land Inc. : pp. 27-45.
T a y l o r , S.E., 1979. Measured Emmiss iv i ty of S o i l s i n t h e S o u t h e a s t Uni ted S t a t e s . Remote S e n s i n g of Environment 8, E l s e v i e r N-Holland: pp. 359-364.
12.10. A d d i t i o n a l r e a d i n g
B l i a m p t i s , E.E., 1970. Nomogram R e l a t i n g T r u e and Apparent R a d i o m e t r i c Tempera tures of Graybodies i n t h e P r e s e n c e of a n Atmosphere. Remote S e n s i n g of Environment 1. h e r . E l s e v i e r Publ . Cy Inc . : pp. 93-94.
Feddes , R.A., 1971. Water , Heat and Crop Growth. Commun. Agric . Univ. Wageningen, The N e t h e r l a n d s : 184 ppp.
Fr iedman, J.D., 1970. The Airborne I n f r a r e d Scanner i s a Geophys ica l R e s e a r c h Tool . O p t i c a l S p e c t r a 1970 Vol 4 ; n r 6 : pp. 35-44.
Goddard Space F l i g h t C e n t e r , 1978. Heat C a p a c i t y ?Tapping Miss ion (HCMM) Data Users Handbook f o r A p p l i c a t i o n s E x p l o r e r Mission-A (AEM), NASA: 120 pp.
Hei lman, J .L . , Kanemasu, E.T., Rosenberg , N . J . and M a d , R.L.. 1976. Thermal Scanner Measurement of Canopy Tempera tures t o e s t i m a t e E v a p o t r a n s p i - r a t i o n . Remote S e n s l n g of Environment 5, Amer. E l s e v i e r Publ . Cy: pp. 137-145.
Heilman, J.L. and Moore, D.G. , 1980. Thermography f o r E s t i m a t i n g Near-Surface S o i l M o i s t u r e under Developing Crop Canopies . J o u r n a l of Applied Meteorology Vol. 19, No 3. Amer. M e t e o r o l o g i c a l SOC.: pp. 324-328.
Heilman, J.L. and Moore, D.G., 1982. E v a l u a t i n g Near-Surface S o i l Mois ture
312
using Heat Capacity Mapping Mission Data. Remote Sensing of Environment 12. Elsevier Publ. Co, New York: pp 117-121.
Hoop, D. de, 1977. Thermografie als hulpmiddel by Hydrogeologisch Onderzoek. Symposium Luchtwaarneming 1/2-09-1977, Delft, The Netherlands: pp. 89- 105.
Hoppe, G.D. (ed.), 1972. Microwave Radiometry and its Potential Application to Earth Resources Surveys. European Space Research Organisation RAC-03- R17: 104 pp.
Idso, S.B., 1982. Humidity Measurement by Infrared Thermometry, Remote Sensing of Environment 12, Elsevier Scce. Publ. Co, New York: pp. 87-91.
Kahle, A.B., Madura, D.P., Soha, J.M., 1979. Processing of Multispectral Thermal IR Data for Geological Applications. NASA, Jet Propulsion Lab., Pasadena, California, JPL Publ 79-89: 39 pp.
Kiefer, R.W., 1972. Sequential Aerial Photography and Imagery for Soil Studies. Highway Research Record 421. Remote Sensing for Highway Engineering: pp. 85-92.
Koolen, A.J., 1979. Temperatuurbeelden van onbegroeide grond. Op weg naar Landbouwpraktijk? Landbouwkundig Tijdschrift pt 91 nr 9, KGL, The Netherlands: pp. 258-264.
Kumai, R., Silva, LeRoy, F., 1973. Emission and Reflectance from Healthy and Stressed Natural Targets with Computer Analysis of Spectroradiometric and Multispectral Scanner Data. The Lab. for Applications of Remote Sensing. Purdue Univ., Indiana, LARS Information Note 072473: 211 pp.
LeSchack, L.A. and Kerr del Grande, N., 1976. A Dual-wavelength Thermal Infrared Scanner as a Potential Airborne Geophysical Exploration Tool. Geophysics, Vol. 41, No 6: pp. 1318-1336.
Loor, G.P. de, 1969. Possibilities and Uses of Radar and Thermal Infrared Systems. Photogrammetria 24. Elsevier Publ. Cy, Amsterdam: pp. 43-58.
Monteith, J.L., 1973. Principles of Environmental Physics. Wiliam Clower & Sons, Ltd., London: 241 pp.
Nieuwenhuis, G.J.A., 1980. Remote Sensing en het onderzoek naar de Waterhuis- houding van Landbouwgewassen. Cultuurtechnisch Tijdschrift 19/5: The Netherlands: 10 pp.
Oetjen, R.A., Bell, E.B., Young, J. and Eisner, L., 1960. Spectral Radiance of
Pratt,
Pratt,
Price,
Price,
Quiel,
Sky and Terrain at Wavelengths between 1 and 20 microns. Instrumentation. Journal of the Optical SOC. of America, Vol. 50, Nr 12: pp. 1308-1313. D.A., Ellyet, C.D., McLauchlan, E.c. and McNabb, P., 1978. Recent Advances in the Application of Thermal Infrared Scanning to Geological and Hydrological Studies. Remote Sensing of Environment 7. Elsevier North Holland Inc.: pp. 177-184. D.A., Foster, S.J . and Ellyett, C.D., 1980. A Calibration Procedure for Fourier Series Thermal Inertia Models. Photogrammetric Eng. and Remote Sensing Vol. 46, No 4: pp 529-538. J.C., 1980. The Potential of Remotely Sensed Thermal Infrared Data to infer Surfaae Soil Moisture and evaporation. Water Resources Research, Vol. 16 No 4: 787-795. J.C., 1981. The Contribution of Thermal Data in Landsat Multispectral Classification. Photogrammetric Engineering and Remote Sensing, vol. 47, No 2: pp. 229-236. F., 1975. Thermal/IR in Geology. Some Limitations in the Interpretation of Imagery. Photogrammetric Engineering and Remote Sensing, 1975: pp. 341-346.
Rosema, A., 1974. Simulation of the Thermal Behaviour of Bare Soils for Remote Sensing Purposes. 7th Int. Seminar Heat and Mass Transfer in the Environment of Vegetation, Dubrovnik: 13 pp.
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Rosema, A., 1975 a. A Mathematical Model for Simulation of the Thermal Behaviour of Bare Soils based on Heat and Moisture Transfer. NIWARS publ. No 11, Delft, The Netherlands: 92 pp.
Rosema, A., 1975 b. Heat Capacity Mapping, is it feasible? Proc. 10th Int. Symposium on Remote Sensing of the Environment: 12 pp.
Savigear, R.A.G. e.a., 1975. Multispectral Scanning Systems and their Potential Application to Earth Resources Surveys. Earth Science Applications ESROIESTEC Contract No 1673172, Neuilly, France: 202 pp.
Schaerer, G., 1974. Passive Sensing Experiments and Mapping at 3.3 mm Wavelength. Remote Sensing of Environment 3. her. Elsevier Publ. cy, New York: pp. 117-131.
Schneider, S.R., McGinnis, D.F. Jr. and Pritchard, J.A., 1979. Use of Satellite Infrared Data for Geomorphological Studies. Remote Sensing of Environment 8, Elsevier North Holland Inc.: pp. 313-330.
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Smith, J.A. e.a., 1981. Thermal Vegetation Canopy Model Studies, Remote Sensing of Environment 11, New York: pp. 311-326.
Spiro, I.J. (ed.), 1976. Modern Utilization of Infrared Technology 11. Proc. of the SOC. of Photo-Optical Instrumentation Engineers. August 26-27, San Diego, California: 230 pp.
Thackrey, D.E., 1973. Research in Infrared Sensing. In: The Surveillant Science. Remote Sensing of the Environment ed. by R.K. Holz, Houghton Mifflin Cy, Boston: pp. 209-219.
Torres, Cl., 1973. La Thermographie. Questions, Techniques et Problemes de l'hterpretation: Revue Photo-interpretation 1973-2/3, Editions technip, Paris: pp. 48-73 et pp. 32-55.
Verstappen, H.Th, 1977. Remote Sensing in Geomorphology. Elsevier Scientific Publ. Cy, Amsterdam: 214 pp.
Vincent, R.K., Rowan, L.C., Gillespie, R.E., Knapp, C., 1975. Thermal-Infrared Spectra and Chemical Analyses of twenty-six Igneous Rock Samples. Remote Sensing of Environment 4. her. Elsevier Publ. Cy Inc.: pp. 199-209.
Vincent, R.K., 1975. The Potential Role of Thermal Infrared Multispectral Scanners in Geological Remote Sensing. Proc. of the IEEE: pp. 137-147.
Watson, K., 1971. Geophysical Aspects of Remote Sensing. Proc. of the Int. Workshop on Earth Resources Survey Systems, NASA SP 28312: pp. 409-428.
Watson, K., 1974. Geothermal Reconnaissance from Quantitative Analysis of Thermal Infrared Images. Proc. 9th Int. Symposium on Remote Sensing of Environment, Univ. of Michigan, Ann Arbor: pp. 1919-1932.
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314
13. ACTIVE SENSOR SYSTEMS
Active sensors supply their own source of energy to illuminate features of
interest. A common example is a photocamera used with flash bulbs. The main
active systems for remote sensing are:
- Lidar or Laser systems;
- Radar (or Radio Detection And Ranging).
These active systems are like the thermal Infrared systems capable of day and
night operation.
Radar was extensively used by the military during World War I1 but its
application has spread since then to many purposes. There are two features that
distinguish Radar from other remote sensing techniques:
- it uses Microwaves which are capable of penetrating the atmosphere under
poor weather conditions (e.g. clouds, haze, rain and snow);
- the wavelengths used for radar are large when compared to Visible and
Infrared, and consequently surfaces have to be relatively rough to produce
diffuse reflection; surfaces that appear rough in the Visible may be
smooth for Microwaves.
13.l.Laser systems
The Laser systems or Lidars operate in the short wavelength portion of the
EMS: UV, Visible and NIR.
The information about Lidar systems given below is extracted from the review on
Remote Sensing Instrumentation by MacDowall (1972).
The radiation is emitted from a laser unit either in pulses or continuous
waves; the scattered radiation is collected by an optical system. The laser,
used as a source of radiation for the Lidar, produces a very narrow coherent
beam: a beam width of 0.1 mRad is not unusual. Consequently, a very high
resolution is achieved.
Since this is an active system, it is capable of day and night operation. For
day-time use, precautions must be taken to eliminate sunlight from the returns.
Since the laser light is monochromatic, sharp filters at the laser wavelengths
can be used for this purpose. However, owing to its short wavelength, lidar is
not able to penetrate clouds.
315
Three different types of aircraft Lidars can be mentioned:
- the Laser Profiler or Altimeter; the laser emits either a pulse or a
continuous wave of light which is directed straight down to the earth below
the aircraft; in this way a profile of the terrain can be obtained;
- Reconnaissance or Mapping Lidar; the laser beam is swept across a strip of
terrain either directly beneath, OK to the side of the aircraft and
perpendicular to the flight path; the scattered or reflected radiation is
measured and recorded in a way very similar to a scanner;
- Raman and Fluorescence Lidar Systems; the radiation from the laser is used
to excite the materials of interest; the resulting fluorescence and Raman
emissions are recorded, and are unique for each type of material; these
lidar systems generally operate in the UV range and therefore are seriously
hampered by haze.
C o l l i s and Russell (1976) report about applications of Lidar, being
profilometry for topographic mapping, bathymetry (see Hickman and Hogg, 1969-
1970), water turbidity observations and atmospheric probing.
For technical information, the reader is referred to Johnson (1970).
13.2.Radar systems
Radar is an active system which applies short pulses of energy in the
Microwave portion of the EMS. The Microwave region of the EMS extends from
wavelengths of 1 mm to several metres (see Fig. 2.2). Most radars operate in
the 0.75-100 cm wavelength zone. The band designations used in the USA are
listed in table 13.1. Also the frequencies are given, since they are applied
very often for designation of spectral bands in the Microwave region.
Table 13.1 Radar band designations after Long (1975).
Band Frequency Wavelength
P 300-1,000 MHz 30-100 cm L 1,000-2,000 MHZ 15-30 cm S 2,000-4,000 MHz 7.5-15 cm C 4,000-8,000 MHz 3.75-7.5 cm X 8,000-12,500 MHz 2.4-3.75 cm K, 12,500-18,000 MHz 1.67-2.4 cm
K 18.0-26.5 GHz 1.1-1.67 cm K, 26.5-40.0 GHz 0.75-1.1 cm
(12.5-18.0 GHz)
316
Radar systems may or may not produce images; they may be groundbased or
mounted in aircraft or spacecraft. A common form of non-imaging radar is the
Doppler radar system used to measure vehicle speeds.
The so-called Doppler effect concerns the alteration of frequency caused by
relative motion between observer and source. The observer receives re-radiation
at a different frequency (f') as compared to the (fixed) frequency of a moving
source (f): f' is greater than f for approaching sources and is smaller than f
for receding sources.
Another form is the "plan position indicator" radar. This system has a
display screen on which a radial sweep indicates the position of objects
producing radar echoes (Lillesand and Kiefer, 1979).
Many imaging radars used for remote sensing are real-aperture Side-Looking
Airborne Radars (SLAR). The antenna points to the side with a beam that is wide
vertically and narrow horizontally. A short pulse strikes a target and a signal
returns to the radar antenna. The time delay associated with the signal sent
and received (echo), gives the distance between target and radar. The picture
presented in fig. 13.1 illustrates a return for a particular instant of time of
strong signals coming from a.0. trees and a sloping edge, while no signal is
coming from a radar shadow area. In the imaging radar, the signal return is
modulated and transferred via a lens to a film. The film i s in the form of a
strip that moves synchronously with the motion of the aircraft, so that as the
aircraft moves forward the film also moves. When the aircraft has moved one
beamwidth forward, the return signals come from a different strip on the ground
and produce an image line on the film adjacent to the preceding line. The
images are comparable with those from a strip camera or an optical scanner.
The geometric aspects of SLAR operation are summarized in fig. 13.2.
The slant range (SR) to any given object is given by (Lillesand and Kiefer,
1979) :
(13-1) ct SR = - 2
where c = speed of Em,
t = time between pulse transmission and echo reception; the factor 2 is
introduced, because the time is measured for the pulse to travel both the
distance to and from the target.
317
Recorder - Sloping Edge
Scrub Growth (Brush, Grass, Bare Earth, e t c )
Fig. 13.1 Principle of Side-Looking Airborne Radar after Ulaby et al., (1981).
swath
Fig. 13.2 SLAR geometry (modified) after Moore et al. (1975) . a = depression angle 9 = angle of incidence or grazing angle SR = slant raFge GR = (SR2-h2)
B = angular beam width. (Used by permission of Am. Soc. for Photogrammetry and Remote Sensing.)
For Microwaves, the resolution is usually meant to bethe half-power response
318
width of the measuring system. Fig. 13.3 illustrates the kinds of resolution
possible with Microwave sensors. The active systems can distinguish objects by
angle, range and speed resolution, whereas the passive system is restricted to
angle resolution alone. The angle resolution of a radar system is determined by
the angular beamwidth of the antenna.
According to Innes (1973) there is an easy rule which relates the aperture
(A), as expressed by the number of wavelengths ( N X ), with the angular
beamwidth ( 6 ) :
A = N. X than 6 = 1/N of a Radian. ( 13-2)
From (13-2) it can be concluded that in principle both shorter wavelengths and
larger antennas may be used for improvement of angular resolution.
The possibilities, however, are limited owing to atmospheric effects at shorter
wavelengths (see fig. 2.15 and 2.16) and problems connected with the
application of large antennas on aircraft.
The resolution of the system can be improved through application of angle and
range resolution together (fig. 13.3b). By comparing the frequency of the
transmitted signal with that of the received frequency, the Doppler frequency
shift, which is directly proportional to the relative speed of the aircraft and
the point on the ground, can be observed. Using angle and speed resolution
together, the size of the resolution cell becomes smaller (fig. 13.3~).
Fig. 13.3d shows furthermore the resolution cell reached when range and speed
resolution are combined.
The SLAR described in Fig. 13.1 is a Real Aperture Radar (RAR), where
resolution is determined by the actual length of the antenna aperture. Since
antenna length is physically limited when using aircraft, most of the real-
aperture SLAR use wavelengths between 3 and 0.8 cm to achieve beamwidths in the
order of milliradians (Moore et al., 1983). The resolution of these systems is
generally described by the so-called slant range or cross-track resolution and
perpendicular to the slant range direction by the along track or azimuth
resolution.
The pulse duration and depression angle determine the spatial resolution i n the
direction of wave propagation, the slant range direction. The ground resolution
319
! F i r s t null I \ \ contour I \ \
/ beam- contour- beam contour- \ - Angle and speed resolut ion. / Active sensors only.
Angle resolut ion alone, used by a l l passive and some a c t i v e sensors
A A
solu 11
1 / 2 power range response contour
/--- W 5 e s o l u \ 1 / - - -- cc c e l l /
power speed> response contouy. ,\ ____---- - _-//
2 power range 1- - 1 / 2 - - power - ' range Lresponse contour response contour
t ion
Angle and range resolut ion together . Active sensors only.
Range and speed resolut ion together . Active sensors only.
Fig. 13.3 Resolution techniques used in Microwave sensing (Moore, 1983). (Used by permission of Am. S O C . for Photogrammetry and Remote Sensine.)
in this direction (R,) is found from (Lillesand and Kiefer, 1979):
R =
where
cT 2cosa - (13-3)
T = pulse duration,
a - the line connecting the radar antenna and the object being sensed.
depression angle or angle between the horizontal platform plane and
320
The along track resolution is determined by the angular beam width of the
antenna ( 6 ) and the ground range (GR). As the antenna beam fans out with
increasing distance from the aircraft, the along track resolution (Rt)
decreases. It is given by (Lillesand and Kiefer, 1979):
Rt = GR.6 ( 13-4)
A typical resolution profile for a high resolution SLAR is given in fig. 13.4.
25
20
15
10
A l t i t u d e , 6150 m
0 5 10 15 20
Ground r a n g e (km)
Fig. 13.4 Typical resolution profile for high resolution SLAR after Moore et
(Used by permission of Am. SOC. for Photogrammetry and Remote Sensing.)
From this figure the following data are extracted:
al. 1975.
direction ground resolution at distance from aircraft of 5 km 10 km 15 km 20 km
slant range 15 m 12 m 11 m 10.5 m along track 8.5 m 10.5 m 13 m 16 m
The early radar systems made use of non-coherent radiation. The
application of radar in satellite systems made it necessary to develop coherent
radar with fine resolution. Furthermore, it became possible to use specific
signal processing techniques.
321
The resolution problems of real-aperture SLAR are overcome in Synthetic
Aperture Radar (SAR). These systems employ a very short antenna but through
modified data recording and processing techniques they synthesise the effect of
a very long antenna e.g. a 2 m antenna can be made effectively 600 m long. In
S A R , return signals from the center portion of the beamwidth are discriminated
by detecting Doppler frequency shifts. A Doppler shift is a change in wave
frequency as a function of the relative velocities of a transmitter and a
reflector. Within the wide antenna beam, returns from features ahead of the
aircraft will have upshifted (higher) frequencies, and returns from the area
behind the aircraft will have downshifted (lower) frequencies; returns from the
center portion of the beamwidth will experience little OK no frequency shift.
Through the use of range resolution by processing the return signals according
to their Doppler shifts, a very small effective beamwidth can be generated.
Consequently, larger wavelengths may be applied in SAR than in RAR.
Different modes of polarization may be applied in transmitting and
receiving. A radar signal can be transmitted either in horizontal (H), or
vertical (V) linear polarization. Also circularly polarized radar waves may be
produced. For linear polarization there are four different combinations:
- H send, H receive (OK HH); H send, V receive (OK HV);
- V send, H receive (OK VH); V send, V receive (OK VV).
HH and W data can be transformed in so-called like-polarized imagery, while
from HV and VH data so-called cross-polarized imagery can be produced.
The fundamental equation showing the amount of signal received by a radar
system from a particular target is called the radar equation, which may be
written as follows (Skolnik ed., 1970, Long, 1975):
P G aA
I- 4n(SR)’ - t t p =- K
( 13-4)
where Pr = power received, Wm-2,
Pt = power transmitted, Wm-*,
Gt = the gain of the transmitting antenna in the direction of the target,
SR = the slant range to the target (distance in m from radar to target),
= the effective aperture of the receiving antenna in m2,
U = the effective backscattering area of the target or radar cross-
section (RCS) in m2, that is the actual cross section of a sphere which,
322
when placed in the same position as the target, would scatter back to the
radar the same amount of energy as is returned by the target.
gives the power per unit area PtGt
In equation 13-4, the first quantity - 4n( SR)
transmitted to the target, the second quantity determines the energy re-
radiated by the target with a RCS u . All of the factors on the right hand side of eq. 13-4, except u , are under control of the radar designer; a describes
the target. Using the same antenna for transmission and reception, Gt and A,
are related by (de Loor, 1976):
( 13-5)
where X = wavelength.
Two definitions are in common use, being the differential scattering
coefficient ao and the return parameter y:
ao = 01s ( 13-6)
where uo is the RCS per unit illuminated surface-area S, which is determined
by the grazing angle ( 0 ) , the width of beam ( B ) , the slope and the orientation
of the target;
y = o/si ( 13-7)
where y is the RCS per unit projected area Si, being the area normal to the
direction of propagation of radiation illuminating the area. Both uo and y are
usually expressed in dB (x dB = 10 log x e.g. x = 1 or o dB, x = 1,000 or 30
dR). S as well as Si are considered to be planes, u can be understood to
be composed of S enlarged by the surface roughness of the target (considering
surface scattering only).
Some examples of SLAR and SAR systems are given below (see Ulaby et al., 1981-
82) :
323
System wavelength (cm) Pixel (m) at 6 km altitude G R = 5 k m GR = 20 km
Real-aperture SLAR: ANIAPQ-97 0.86 8.6 x 14.1 23.0 x 9-4 Motorola ANIAPS-14D 3.2 60.1 x 46.8 161 x 31.3
SAR: Good year GEMS 3 15 x 15 Seasat S A R 25 6.25 x 25
nominal pixel dimension (m)
13.3. Interaction of Microwaves with objects at the earth's surface
The target properties that determine the reflection of radar waves are:
surface roughness, slope and orientation, and dielectric properties.
Moore (1976) points to the great influence of resonant sized objects. For
example, gratings or fences may produce strong radar signals.
Surface roughness
The so-called relative surface roughness has been defined by the smooth
criterion of Rayleigh (2-23). Ulaby et al., (1982) propose the so-called
Fraunhofer criterion to explain the scattering behaviour of natural surfaces in
the Microwave region. According to this criterion a surface is smooth if
( 13-8)
This criterion appears to be consistent with experimental observations, while
the Rayleigh criterion is not.
Surface roughness may be described by the standard deviation of surface
relative to a reference surface (x-y plane). Consider a surface height
with a point that has a height z (x, y) above the x-y plane.
The standard deviation of the surface height,
(uz)
uz , is then given by:
(13-9)
- where Z is the mean height of the surface and y2 is the second moment.
Angular response curves for uo (scattering coefficient, 13-6) based on
measurements at 1.1 GHz for five bare-soil fields with approximately the same
soil-moisture content but with different u are given in fig. 13.5.
The effect of surface roughness on uo is evident: the smoothest surface (field
1) shows a rapidly decreasing with increasing angle of incidence, the
roughest surface (field 5) exhibits only a small variation between nadir and
324
30" incidence.
20
h 15
10
r 5
; ; o
0 -5
'i: -10
-15
-20
-25
M -0 v
0 0
+J a V
re a 0
.r
cn S
a, + c,
v)
Pol ari za t Frequency
0 5 10 15 20 25 30
Angle o f incidence (degrees)
Fig. 13.5 Angular response curves of the scattering coefficient at 1.1 GHz for five bare-soil fields with different surface roughness (Ulaby et al., 1978). (Copyright 1978 IEEE. )
If a smooth surface happens to be perpendicular to the incident radar
beam, then the return signal is intense. However, if a smooth surface is at any
other angle to the radar beam, none of the energy is returned to the antenna,
but is specularly reflected into space.
Conversely, rough surfaces of land as well as water scatter the incident energy
in all directions, thus returning some of it to the antenna.
Agricultural fields ploughed in one direction show a regular surface
roughness. In that case, the orientation of the furrows is decisive for the
roughness experienced by the incoming radar waves and the intensity of the
return signal.
325
Slope/orientation
It can be concluded, that the surface illuminated (S) is determined by the
sensor parameters (direction of illumination and depression angle) as well as
by the slope and orientation of the target.
The surface illuminated is relatively small when slopes are pointing
towards the sensor and relatively large when slopes are facing away from the
sensor. Hence, in the former case the energy will be piled up in the reflected
signal, while in the latter case it will be spread out. Therefore, the former
results in a strong return signal and the latter in a weak. Orientation plays
an important part in scattering from vegetation canopies. Large leaves of which
the surface normals are turned towards the radar will exhibit a relatively
large scattering coefficient.
Dielectric properties
General considerations
The dielectric properties of terrain features are important in determining
the intensity of radar returns.
From the data in table 13.2, the strong influence of the moisture condition of
soil on the conductivity values and dielectric constants is evident.
The results obtained by Cihlar et al., (1974) and Schmugge et al., (1978)
are given in fig. 13.6(a) and (b) respectively.
Fig. 13.6(a) indicates that an increase in soil moisture leads to an increase
of the dielectric constants. Also the scattering coefficient (0') of radar
energy (f = 4 GHz or X = 7.5 cm) increases with the soil moisture content
(fig. 13.6b).
The radar energy, being incident upon the surface of a homogeneous soil
medium, which is not reflected at that surface, is travelling through the
medium; energy is lost by absorption as well as scattering.
The so-called extinction coefficient, or power attenuation coefficient (Ke), is
the sum of the power absorption coefficient (K,) and the power scattering
coefficient (Ks):
K = K + K e a s (13-10)
P - P e -
P D where K = o
0
326
Table 13.2 Conductivity (.a) and dielectric contents (E' and E") of soil and water at different wavelengths of EMR ( A ) after Long (1975, adapted from Kerr, 1951).
Medium x U E' E"
mho /m
Sea water 3 m - 20 cm 4.3 80 774 52
20' - 25°C 10 cm 6.5 69 39 28'C 3.2 cm 16 65 30.7 Distelled water, 23°C 3.2 cm 12 - 3 - 2 67 23 Fresh-water lakes l m 10 -10 80 0.06
0.60 Very dry sandy loam 9 cm 0.03 2 1.62 Very wet sandy loam 9 cm 0.64 24 32.4 Very dry ground l m 10-2 4 0.006 Moist ground l m 10 30 0.06 Arizona soil 3.2 cm 0.10 3.2 0.19 Austin, Tex., soil, very dry 3.2 cm 0.0074 2.0 0.014
Note: for laboratory measurements of the complex dielectric constant of soils, the reader is referred to Wiebe (1971).
P = power at depth D (m).
Other concepts are the penetration depth and Skin depth. The penetration
depth u may be defined as the depth at which the power has been reduced to
l / e of its original value. If scattering in the soil medium is ignored:
1 = - N
Ke = Ka = 2 a and 6 P 2a
( 13-1 1)
2n where the field attenuation coefficient a = - Im [GI ,
xO
Xo is the wayelength in free space and E is the relative complex dielectric
constant (h = imaginary part of).
For materials with E " / E ' < 0.1 (see 2-11 up to and including 2-16) , Ulaby e t
al. (1982) give the following formula for 6 : P
6 - a @ P =- 2nE" (13-12)
327
2 2 8 - lu CI
S 0
V
c, V
W
VI 2 6 -
2 4 -
x 22 - 2 2 0 -
1 8 -
.? 1 6 -
2 1 4 -
12 - 10 - 8 -
6 -
W
-P
W tx
Frequency: 4.0 GHz So i l type: - sand - - loam ----- clay
/ I
I I
I
= Imaginary par t
. . ..
-15 Polar izat ion: H H Frequency (GHz) : 4.25
Angle o f incidence ( ) =10
RMS Height d : 1.1 - 4.1 cm
0
3 s o i l moisture content (g/cm ) 3 Soil moisture (g/cm
Fig. 13.6 Dielectric constants and scattering coefficient as a function of soil moisture content. a) dielectric constant values after Cihlar et al., (1974) b) scattering coefficient as a function of Moisture content for
bare soil with different surface roughness after Schmugge et al.. (1978).
which is applicable to most natural materials except for water.
The penetration depth should not be confused with the skin depth
= 2 6 = l / a (see 2-13) . P
The measured scattering coefficient oo is plotted in fig. 13.7 against skin
depth and the corresponding effective attenuation coefficient a (In Nepers
cm-I or Ln A1/A2 per cm-' where A1 is amplitude of the original signal and A2
of the return signal; 1Np=8,685dB). It can be concluded that oo increases
almost linearly at all incidence angles with the attenuation. The increase is
highest at low incidence angles (measured from the vertical).
In nature, both surface and volume scattering are usually present and
contribute to the return signal of incident radar energy. However, it may be
328
24
20
16
12
8
4
0
-4
-8
-12
-16 C
Frequency 7.1 GHz P o l a r i z a t i o n HH 0
I nc idence ang le
O 0
. 20° -- 30°
f _ _ _ _ _ _ 60° / . /'.
1 oo / oo
40' 0 //. l o o 50' /' /
0 - ..
/. 0 /
//'
../, A -. a --
V- 70' / /" /' /
/'
/. /.. / /o
I 1 J
I 0 . 5 1 . o 1 . 5 A t t e n u a t i o n ae i n Nepers (cm)
8.0 4.0 2.0 1 . o 0.7 6 Sk in depth (cm)
I I
Fig. 13.7 Scattering coefficient as a function of attenuation and skin depth after Ulaby et al. ( 1 9 7 4 ) .
convenient to ignore one or the other of these. For example, in the Microwave
region, sea-water has a large E and is treated as a homogeneous medium capable
of surface scattering only. At optical wavelengths, E of sea water is much
smaller and dust particles in the water can make volume scattering important.
Also wet soil may be assumed to show mainly surface scattering.
In surface scattering, the scattering strength is proportional to E of
the medium at the surface and the angular scattering pattern is governed by the
surface roughness. In volume scattering, the scattering strength is proportion-
al to the average E of the volume and to the discontinuities inside the
329
medium, the angular scattering is determined by the roughness of the boundary
surface, the average E of the medium and the geometry of inhomogeneties (see
Ulaby et al., 1982).
A qualitative illustration of the dependence of u0 in volume scattering on the
average dielectric constant of media is given in fig. 13.8. Both a small and
large E show a lower uo at high angles of incidence but the angular
backscattering curve for volumes with large E drops faster than for small E
media. 0 0
u
I
m
0 20 40 60 80
Angle o f i nc idence 8 (degrees)
Fig. 13.8 Dependence of the volume backscattering coefficient on the average dielectric constant (after Ulaby e.a., 1982).
For the radar frequencies of 1.3 GHz, 4.0 GHz and 10.0 GHz, Ulaby et al.,
(1982) present some curves that provide understanding of the lower boundary of
moisture content, at which surface scattering dominates over volume scattering
(fig. 13.9). The 4- and 10-GHz ( A = 7.5 and 3 cm) curves show that surface
scattering is the main contributor to scattering of this radiation at moisture
conditions above 0.05 g/cm3. Greater penetration is reached with 1.3 GHz radar
waves even at relatively high moisture contents.
Determination of Soil moisture
Fig. 13.5 showed for 1.1 GHz that uo of the rough surface (field 5) is
approximately independent of the angle of incidence. Analyses in the 1-8 GHz
region indicated that for 5 GHz ( A = 6 cm) , either HH or W polarization, the effect of surface roughness as well as the vegetation cover is at a minimum in
the 7-17" range (angle of incidence) while the sensitivity of uo to soil
330
I I I
Fig. 13.9 Penetration depth in loamy soil as a function of moisture content (after Ulaby e.a., 1982).
moisture content is strong (Ulaby e.a., 1982). Therefore, this range is
suitable for measurements of soil moisture. Soil moisture content should be
expressed in mf, the percent of field capacity (here moisture at 1/3 bar soil
tension) :
m m
mf 100 x -+ = 100 x g FCV
(13-13)
where the graviometric (g) and volumetric (v) moisture contents are given for
the actual moisture contents (m) and at field capacity (FC).
Empirical expressions were derived by Schmugge (1980) relating FCg and FCV to
the soil texture of his sample set:
FC = 25.1 - 0.21s + 0.22C percent by weight (13-14) g
FC,,= 0.30 - 0.0023s + 0.005C g (13-15)
where S and C are the percentages of sand and clay particles in the soil
331
samples.
Fig. 13.10 shows the response of uo to mf of the top 5 cm layer of bare soil.
18
1 2
- 6 m U v
owl 0 0
-6
-12
-18
Frequency (GHz) : 4.5 Polar izat ion : HH Angle of incidence 8 (degrees) : 10 Bare s o i l data: I 1 f i e l d s with d i f f e r e n t Soil types and surface roughnesses
Multiple data
0 (dB)=0.148 mf-15.96 1974 A 1975 N=181
p=O .85 1977
points 2 :+ -..'
I I I - 24 0 25 50 75 100 125 150
Soi l moisture of Top 5 cm layer , mf ( % o f f i e l d capac i ty)
Fig. 13.10 Measured backscattering coefficient of bare soil as a function of mf for a variety of soil surface-roughness conditions and soil textural compositions (Ulaby et al., 1982).
The data shown were measured at 0 =loo and f around 4,5 GHz and include a wide
variety in surface roughness conditions as well as in soil textural
composition. The last square linear regression between uo (d B) and mg ( X ) is
given by:
uz(d B)= 0.148 mf- 15.96 (13-16)
where uo is uo of bare soil and the linear correlation coefficient is equal to 0.85.
Similar studies were conducted for fields planted in milo, corn, soybeans
and wheat. Data of these four types of crops observed over a wide range of soil
moisture conditions and plant-moisture and plant-height variations, are given
in fig. 13.11. The least square linear regression is given by:
332
u0 (dB)= 0,133 mf- 13.84 can
18
12
6 -
0 -
-6
-12
(13-17)
- -
-
-
where uo
to 0.92.
is uo of the canopy and the linear correlation coefficient is equal can
- 1 8 -
M -0
b
v
0
Angle o f i nc idence 0 (degrees) : 10- N = 143 p = 0.92 Oo(dB) = 0.133 mf - 13.84
I I I I 1 I *
I I 1 I I I
Vegetat ion data A Corn -
Frequency (GHz) : 4.5
P o l a r i z a t i o n : HH
13.4 Ground penetrating radar.
Johnson et al., (1980) report about the application of the GSSI
(Geophysical Survey Systems Inc.) radar in soil survey, also indicated as
ground penetrating radar OK GPR. The GSSI system is an impulse radar which
radiates repetitive pulses at frequencies between 80 and 1000 MHz ( A = 30 - 375 cm) into the earth. The transmitted radar signals are scattered from
various interfaces within the ground and picked up by the radar receiver. The
interfaces may be different soil horizons, soil/rock interfaces, or other
materials with contrasting dielectric properties. Organic matter, salt content,
clay mineralogy, particle size and moisture content are some soil properties
affecting the dielectric properties.
A s the antenna is moved along the surface, a recorder produces a graphic record
along a traverse. For rapid exploratory work the antenna may be towed at speeds
up to 8 km/hr.
333
The choice of frequency is an important consideration. Generally, low frequency
radiation propagates to the greatest depth, but high frequency radiation
produces better resolution. The choice depends on the soil conditions and
purpose of study.
The GPR signals commonly penetrate to depths of 3 to 10 m, but at some
sites penetration as deep as 20 m has been achieved. The depth of penetration
is reduced if the soil is saturated with water and/or contains an appreciable
amount of silt OK clay. Soils with a high content of montmorillonite are highly
attenuative and penetration may not exceed 1 m. Similarly radar does not
penetrate deeply in soils with a high salt content.
The GPR signal StKUCtUKe consists of the following basic components:
- the transmitted pulse, which serves as a time reference; - a strong surface reflection immediately following the transmitted pulse; - the reflection of an interface at a time equal to the pulse travel time from
the surface to the interface and back to the antenna.
The graphic recorder produces an image by printing strong signals in black and
weak signals in the grey range. The travel time (t) may be converted into a
depth scale if the velocity of propagation in the penetrated material (Vm) is
known ( s e e also 13-1):
( 13-8)
where D = depth in m, c = velocity of EMR m s-l,
t = pulse travel time in ns
Vmr = velocity of propagation in the material = c/ 5 m s - l .
f = relative dielectric constant of material Fm-l,
The GPR has been found to be capable of detecting changes of some diagnostic
soil horizons such as albic, spodic and argillic horizons
A slight increase of texture, however, was not recorded. The same applies to
the capillary fringe, forming the upper edge of the water table. However, a
water table in coarse, sandy and gravelly soils is usually detected.
334
The 300 MHz frequency ( A = 100 cm) provided excellent data. Yet, the
properties of the upper 38 cm, including the A horizon were masked by the first
strong surface reflection. Higher frequencies can be used to minimize this dead
zone.
13.5. Vegetation backscattering.
The canopy backscattering coefficient includes contributions from the
vegetation cover and the soil surface as well as from multiple scattering
caused by interactions between the vegetation volume and soil surface. Attema
and Ulaby (1978) proposed that the canopy volume can be represented by a cloud
of water particles per unit volume with mass %. The extinction
coefficient K (m ) may then be expressed by: -1
K = A m e 1 v
(13-19)
where A1 is a constant at a given frequency which is different for different
crop geometries and is the sum of the volume absorption and scattering
coefficients. The latter is a function of the shape and size of the real
scattering elements (leaves, stalks and fruit).
Van Kasteren and Smit (1977) discuss measurements on the backscatter of X-
band radiation of a number of crops. They concluded that only a complex of
(mainly geometrical) parameters (e.g. leaf size and distribution in space, row
distance, amount of soil surface not covered by crops) can explain the
scattering differences found between crops. Comments are given on the
dependence of scattering from crop canopies as related to soil tillage and
growing stage. Some of these are quoted below:
- potatoes grown in rows (the incident waves directed perpendicular to the
direction of rows); at the start of the growing season, the waves are
scattered back by the walls of the ridges and a high reflection is obtained,
especially at high grazing angles; later on an irregular structure of the
canopy arises and angular dependency disappears;
- cereals (at the start of the growing season); the scattering for all angles
is nearly the same; as the height and coverage of thz crop increase, a
scattering pattern arises that is more angular dependent.
Radar may be used for classification of crops. Bush and Ulaby (1978)
suggest, that for the best classification accuracy of crops, the band of
335
approx. 14 GHz, a dual polarized system, and viewing fields at off nadir angles
in the 40" to 60" range, should be employed. To attain classification
accuracies exceeding go%, multidate acquisition is required.
Furthermore, the radar system has to be accurate (precision of 1 dB or better)
and differences originating from speckle have to be avoided. This can be done
by the calculation of average reflected levels per agricultural field in data
processing (Hoogeboom, 1982).
13.6. Radar image characteristics.
Radar records the distance of the radar source to a reflecting object e.g.
the distances OS, OT, OV and OW in fig. 13.12. The image is constructed by
circling each object-point, taking the radar source as a centre and the
intersections with a l i n e as the image-points.
radar imaqe l i n e S ' T' U ' V ' W ' X '
T U W X
Fig. 13.12 Flagpole-effect and shadow in radar imagery. a = angle of radar beam with horizontal, or depression angle.
In radar imagery there are typical effects: a.0. the fold-over, or
flagpole-effect, and the radar shadow. The flagpole-effect causes the top of a
high object to be registered before the bottom, hence the synonym of fold-over.
In fig. 13.12, two flagpoles are drawn: ST and mi. S is located higher than T ,
therefore nearer to the radar source and will be recorded first; S I T ' is the
echo difference of top and bottom. The echo difference increases when Z or h
increases, but it decreases at a larger distance to the radar (SR = slant
range): V'W' < S 'T ' .
T ' U ' and W'X' are the so-called radar shadows. In these zones behind the
336
obstacles (ST and VW), no details of the terrain are registered. At a greater
distance of the radar source the length of the radar shadow increases ( W ' X ' > T'U'). When comparing distances, the nearby distances appear to be suppressed
in real aperture SLAR. The radar image from a far distance approaches the real
terrain configurations more accurately (Fig. 13.13).
Ob jec t space
( a )
Image space
( b )
Fig. 13.13. Deformation in radar images after Innes (1973) .
Airborne photography and mirror scanning have their imaging domain in the
area within 45" from nadir, that is up to a distance of 1.00 Z; radar is
complementary with regard to imaging when compared with these systems. In
Fig. 13.14, the coverage of the systems is compared; radar covers an area of
4.67 Z.
In Fig. 13.15, a number of radar imaging aspects are given schematically.
Fig. 13.15 (a) compares the perspective projection (using an optical centre)
with the radar projection. Deformation in perspective projection (e.g. aerial
photography) increases radially from the optical centre. The deformation in
radar projection at large a (= 30-45") is clearly demonstrated; at small
a (=10-20"), a more accurate projection of the terrain is derived. Note also
the "shaded" area E'H' (F and G are in this area).
Piling up of energy takes place at slopes facing the radar, while slopes facing
away from the radar show a spreading of energy. Compare: A'B' with B'C' (A'B' < B'C'). The slopes facing the radar are pictured in bright tones, the slopes
facing away from the radar are presented in grey or black tones.
337
0 1.00 2 2 . 7 5 Z 5 . 6 7 Z
-1.00 Z--1.75 Z- 4 4 . 6 7 Z 4
Fig. 13.14 Terrain coverage with aerial photography and airborne scanning (1.00 2) and radar (4.67 2 ) after Innes (1973) .
Parallax is demonstrated in Fig. 13.15 (b). The radar source is at the same
altitude and has the same scan direction, but is at a different distance from
the terrain. For comparison the image line of R" is given above that of R' for
a = 20-45" with B ' , and for a = 10-20" with G', as fixed points; such radar
images may be studied stereoscopically.
Fig. 13.15 (c) gives a schematic picture of the influence of slope on radar
projection in relation to a ; steep slopes show a fold-over in projection at
large a values.
Stereo SLAR imagery is discussed by Koopmans (1974) ; to obtain a stereo
image a 60 Z sidelap is desirable. When using two overlapping strips with same
scan directions but different altitudes, or one positive and one negative of
two strips with opposite scan directions and from different altitudes, it is
possible to fuse the images and to obtain a three-dimensional picture (an
alternative way is given in fig. 13.15 b). Koopmans (1974) gives formulae to
calculate the height from the parallax difference, making an approximation by
considering the wave front as being straight instead of spherical.
From fig. 13.16 the following equations can be derived to calculate the height
(h) of vertical objects from stereo imagery:
a) with same scan directions
1 P -P = AP = h tg a2 - h tg a
2 1
AP
2 h =
1 tga - tga (13-20)
338
photo 1 photo 2 photo 3 photo 4
pe r s pec t i ve p r o j e c t i on h l J ,J / jo4
r a d a r p r o j e c t i o n B' B ' D ' F' G' J '
A ' C ' A' C ' E ' K ' K ' R H ' I ' J ' K ' L'
(a 1 a =10-20° -
E 'I A I 1 B I 1 C I 8
=20-45' I I I 1
R " R '
B ' C' D ' B '
R
( c >
A A D A Fig. 13.15Radar projection of different terrains: (a) compared with
perspective projection, (b ) from same altitude but at different distances, (c) fold-over of steep slopes (schematically).
339
for explanation see 13-21
b) with opposite scan directions
2 AP = h tga + h tga
1
AP tga + tga
1 2 h = (13-21)
where AP is the parallax difference, and a and a2 are the depression
angles towards the top of the object. 1
Fig. 13.16 Radar parallax and slope measurement after Koopmans (1974) . a) scanned from the same direction b) scanned from opposite directions
Equations can be derived to calculate the angle of slope of the objects.
Depression angles are calculated from the flying-height and ground range
towards the end of shadow. An error will be introduced when the shadow does not
lie in the reference plane. Therefore, one is measuring an apparent slope which
has to be corrected to a true slope.
13.7. Interpretation of radar imagery.
Landscape analysis with radar imagery is described by Nunnally (1969) .
Banyard (1979) uses aerial photographs of forest types as a photo-truth key for
radar interpretation in training exercises for tropical foresters.
Koopmans (1973) discussed drainage system analysis on radar images. He con-
340
cluded that stereo radar is more reliable for this purpose than monoscopic
radar. In studying radar imagery, he found that the drainage density obtained
by monoscopic interpretation may be only 2 /3 of that obtained from the study of
stereo-radar. Furthermore, the junctions of tributaries to main rivers as well
as the tracing of water-divides on monoscopic radar images is susceptible to
relatively large errors and their delineation is best done with stereo-radar.
The synoptic view offered by radar imagery is very valuable for geology,
since the analysis of drainage pattern (and density) and geological structure
may be performed over large areas. For geological interpretation of radar
images the reader is referred to Mekel (1972).
A s an example of physiographic interpretation, the monoscopic
interpretation of the radar image of fig. 13.17 is given in fig. 13.18. A first
division in landtypes is made, mainly based on the appearance of high lights
and radar shadows, or contrast in the images. The shadows are evaluated
according to their length. The high lights (as a result of piling up of energy)
are related to slopes facing the radar and may be used together with the
shadows in tone contrast. Rough terrain will be characterized by a high tone
contrast. To avoid misunderstanding: also agricultural fields with different
types of crops may be characterized by a high tone contrast. However, in fig.
13.18, we are concerned with a relatively homogeneous dense cover of natural
vegetation. Further subdivision appeared to be possible in this case on the
basis of ridge pattern and river system; drainage pattern was used here as a
land characteristic not leading to further subdivision.
The following conclusions are drawn on the basis of the data on the maps
constructed by the Ministerio das Minas E Energia of Brasil (Projeto Radam,
1975) at a scale 1:1,000,000:
- geology - the area consists mainly of rocks such as migmatites, gneisses,
granites, schists, quarzites; the parallel orientation of the ridges and the
angulate drainage pattern are witness of metamorphic pressure at many places
in the area during its geological history;
- geomorphology - a table mountain and many areas with inselbergs bear witness
to strong erosion in the past;
- soils - mainly Ultisols and locally Oxisols; Entisols and Inceptisols are found in the valleys and on the footslopes.
The scale of the final maps of the Radam Project does not allow a more detailed
discussion on the value of the interpretation units for soil survey but it will
341
Fig. 13.17 Semi-controlled radar mosaic of part of SB.21-2-C. Radam Project, Rrasil (Ministerio das Minas E Energia, 1975). (Reproduction Projeto RADAM BRASIL.)
be obvious that the interpretation units are meaningful for a first description
of the land. Furthermore the interpretation can be made in a relatively short
time .
342
Legend of Fig. 13.18. I n t e r p r e t a t i o n of p a r t of a semi-cont ro l led r a d a r mosaic
of t h e Radam P r o j e c t ( B r a s i l ) .
B. S t eep ly d i s s e c t e d l and 1. v h 2. h
C . Ro l l ing t o h i l l y land 1. v h 2. h 3. m
D. Undulating l and ad jac- v l e n t t o R ive rva l l ey land
E. R ive rva l l ey l and -
Ridge p a t t e r n Tone c o n t r a s t
1.1. p a r a l l e l v h 1.2. speckled v h 2.1. p a r a l l e l v h 2.2. speckled v h
...........................
speckled h pa tchy m ( i s o l a t e d h i l l s )
DrainaEe p a t t e r n ------ --------- a n g u l a t e m a n g u l a t e m a n g u l a t e 1
1 -
Rive r systems
1. t r i b u t a r y v 1 v a l l e y s wi th ad- j a c e n t f o o t s l o p e s 2. main r i v e r v 1 v a l l e y s
-------------
Abbrevia t ions : v h ve ry h igh , h h igh , m moderate, 1 low, v 1 ve ry low.
Fig. 13.19 shows a Seasa t - 1 image of p a r t of The Nether lands . Seasa t
opera ted i n t h e pe r iod between 26 June 1978 and 21 November 1978.
Techn ica l a s p e c t s Seasat-1: wavelength of r a d a r = 23.5 c m , r a d a r beam width =
6" , IFOV= 25 m, swath wid th = 100 km, dep res s ion a n g l e about 70'.
A po lde r a r e a wi th h igh c o n t r a s t i n g p a r c e l s i s c l e a r l y marked a s oposed t o
g ra s s l and wi th medium g rey tone and f o r e s t a r e a s wi th l i g h t grey tone .
The d i f f e r e n c e s i n grey tone can be r e l a t e d t o d i f f e r e n c e s i n roughness and i n
d i e l e c t r i c p r o p e r t i e s .
F o r e s t a c t s a s a ve ry rough s u r f a c e , r e s u l t i n g i n i d e a l d i f f u s e r e f l e c t i o n and,
as a consequence, a s t r o n g r e t u r n s i g n a l t o t h e r a d a r an tenna .
Smooth s u r f a c e s showing s p e c u l a r r e f l e c t i o n w i l l r e f l e c t t h e energy away from
t h e sende r / an tenna e.g. s o i l s u r f a c e s wi th fur rows p a r a l l e l t o t h e d i r e c t i o n of
t h e i n c i d e n t r a d i a t i o n and p e r f e c t l y calm wa te r su r faces .
The o r i e n t a t i o n and d i e l e c t r i c p r o p e r t i e s of t h e o b j e c t s a r e impor tan t . A h i g h
343
t . m . = t a b l e mounta in
Fig. 13.18 I n t e r p r e t a t i o n of p a r t of a semi-cont ro l led r ada r mosaic SB.21-Z-C of t h e Radam P r o j e c t ( B r a s i l ) s c a l e 1: 250.000. For legend s e e t e x t .
r e t u r n s i g n a l has been de r ived from r a i l - r o a d s and roads d i r e c t e d perpendicular
t o t h e i n c i d e n t r a d a r waves. Apparently a h igh s p e c u l a r r e t u r n s i g n a l i s
344
Fig. 13.19 Seasat-1 ( s a t e l l i t e ) S A R mosaic from o r b i t 1493 of 9 October 1978.
produced by t h e l i n e a r components of t h e s e o b j e c t s , e s p e c i a l l y of r a i l s , bu t
a l s o s t e e p w a l l s of d i t c h e s a long roads . Specular as w e l l a s d i f f u s e r e f l e c t i o n
may t ake p l ace on v e g e t a t i o n s u r f a c e s such as g ras s l and o r on modera te ly smooth
water s u r f a c e s bo th wi th a secondary r e l i e f caused by wind a c t i o n a t t h e t i m e
345
Fig. 13.20 Land-use and soils in the central part of the Netherlands. Interpretation of the Seasat mosaic of Fig. 13.19.
of acquisition.
Furthermore, roads may produce radar returns due t o diffuse reflection by
planting at their sides. A summary is given in table 13.3.
The capability of radar to discriminate different land-use types is illustrated
in fig. 13.20.
346
Table 13.3. Interpretation of grey tones on Seasat-1 imagery(fig. 13.19).
grey tone reflection/ roughness moisture objects scattering condit-
ion
white specular diffuse diffuse specular
light grey specular diffuse
smooth' rough rough smooth
d rY dry moist wet
rail roads, roads 1 town's soil surface furrows 1 forest ditches canals 1
smooth rough
diffuse rough
diffuse + specular moderate diffuse + specular moderate
dark grey specular smooth' specular + diffuse moderate
black specular smooth specular smooth no reflection - (radar shadow)
medium grey specular smooth'
dry moist
wet
moist wet dry moist moist wet
dry
-
rail roads II forest, arable land with beets water surface roads It , rail roads II grassland water surface roads ' soil surface furrows ' soil surface water surface eastern side of dikes
orientation of objects in relation roughness : to incident radiation: soil surfaces - furrows 1 perpendicular water surfaces - waves tl parallel ' oblique a certain roughness
+ planting at road sides induce
Legend fig. 13.20
Land use
A Arable land
Soils - 0 Alluvial soils* (sands excluded)
GA Grassland and Arable land Predominantly calcareous sand soils
G Grassland Complex of podzols, old arable land,
F Forest
N Nature areas
Gley soils and inland dunes
Peat, mucky clay, shallow clay soils
H Heath over peat
@ Built-up area
0 Lake area * a.0. loamy sands, clays, clay over
peat, peaty clay
Note: In a number of instances, the distribution of soils is found to be closely related to parcelling (size, shape and arrangement of parcels) as it is visible on the radar imagery.
341
13.8. Remote sensing with radio waves.
The frequency band designations of the International Telecommunication
Union are given i n table 13.4. (see also Fig 2.2).
Barringer (1976) discussed the use of VLF (Very Low Frequency) radiowaves for
geophysical mapping. Most radio-geophysical systems take advantage of the
stations operated by various government agencies. The frequencies are in the
vicinity of 20 kHz and skin depths vary from 15 m up to 150 m depending on the
conductivity of the materials of the earth's surface. The atmospheric
Table 13.4. Frequency band designations of International Telecommunications
Union after Beckman (1975).
Abbrev. Frequency f Wavelength, A Name
VLF
LF
MF
HF
VHF
UHF
SHF
EHF
3 - 30 kHz
30 - 300 kHz
300 - 3,000 kHz 3 - 30 MHz
30 - 300 MHz
300 - 3,000 MHz
3 - 30 GHz
30 - 300 GHz
~ ~~~ ~~~
100 - 10 km
10 - 100 km
1,000 - 1 m
100 - 10 m
1 0 - l m
1,000 - 100 mm
100 - 10 mm
1 0 - l m m
Very Low Frequency
Low Frequency
Medium Frequency
High Frequency
Very-High Frequency
Ultra-High Frequency
Super-High Frequency
Extremely High Frequency
transmittance of VLF signals is such that they can be employed up to a distance
of 5,000 km from the source.
Instrumental approaches to the utilization of VLF signals have included
measurements of the absolute field strength and the tilt angle of the magnetic
component perpendicular to the direction of propagation.
The so-called Radiophase employs the vertical electric field as a phase
reference for measuring the in-phase and out-of-phase components of the
horizontal magnetic field. The results of modeling with this system have
indicated that the amplitudes of the in-phase and out-of-phase magnetic
components are indicative of conductivity contrasts.
The flow of electrical currents in the ground is highly sensitive to certain
types of geological structure such as stress-metamorphism and shearing.
348
Radiophase measurements in zones of deep tropical weathering, showed that the
major structures are still present (in relict form) in the weathered zone and
can be detected by this method.
The Radiophase system described above, makes use of the electric as well
as the magnetic field components. A new method, the so-called E-phase, operates
entirely on the electric field components.
It has been shown that when a radiowave propagates over homogeneous earth, the
horizontal currents generated at the earth-air interface are phase shifted by
45" with respect to the propagating field. The resultant electric field is
tilted slightly forward in the direction of propagation. The horizontal
electric field amplitude is related to the square root of the resistivity of
the underlying terrain, and the tilt varies at VLF from a few minutes of arc
over highly conductive terrain, to 1" or more over resistive ground.
An E-phase installation can be mounted on aircraft such as helicopters.
Resistivity maps produced by E-phase are contoured in ohm-meters,
indicating apparent resistivity, and according to Barringer (1976) they are not
dissimilar from resistivity maps produced by conventional ground methods.
In general, gravel and sand are relatively resistive unless they are saturated
with saline water. Clay materials are normally relatively conductive as a
result of ion-exchange effects.
Frozen grounds tend to be much more resistive than thawed grounds. Conversely,
heated grounds are likely to be more conductive than cooler grounds.
It is possible to operate at higher frequencies than the VLF range in order to
restrict the measurements to shallower penetrations which will be important for
soil survey.
13.9. Applications and future developments.
De Loor (1976) and other authors indicate several application fields for
radar, namely:
- geological mapping; - hydrology (see Foster, 1981) e.g. drainage basin analysis, riverbasin
morphology;
- sea, coastal and oceanographic studies e.g. mapping of sea and swell waves,
mapping of ice, detection and control of oil pollution;
- vegetation studies (e.g. forest regrowth monitoring, see Hardy, 1981);
349
- agriculture e.g. crop identification and soil moisture studies.
For the use of radar imagery in land-use interpretation, the reader is
referred to Henderson (1977). Simonet (1970) reports about crop identification.
Some of his comments are given below:
- Some crops depolarize an incident polarized beam to a different degree than
others, hence, polarized radar may be used in crop discrimination;
- the use of more than one frequency and multitemporal observation enhance the accuracy of crop discrimination;
- colour combining of multiple polarization imagery will be an aid in crop
discrimination.
The application of radar in environmental studies in South America is well
known. We only mention the "Projeto Radam" in Brasil (Ministerio das Minas E
Energia of Brasil, 1975 and other reports) and the "Proyecto Radargrametrico
del Amazonas" in Colombia (Instituto Geografico Agustin Codazzi, et al., 1979).
In these projects geological maps, soil maps, vegetation maps, land use maps
and potential land use maps at a small scale have been produced with the aid of
radar imagery and field survey. Owing to the unfavourable weather for aerial
photography in these areas (limited number of flight days), radar is an
important tool for mapping of the environment, since it is independable on
weather conditions.
For this reason, radar is also an important aid in regional inventarisation of
disasters (e.g. flooding) in that it enables a rapid and reliable acquisition
of remote sensing data.
The use of stereoradar and the application of COlOUK imagery for the
enhancement of the representations are some of the most promising developments.
Furthermore, significant advances in radar capability can be expected as a
result of the improvement of spatial resolution and multispectral approaches in
data collection, as well as from the application of multipolarization.
The potential of operating at longer wavelengths is afforded by the technology
of SAR:However, a boom in the application of radar may be expected through
their implementation in spaceborne systems (Lillesand and Kiefer, 1979).
Aeroresistivity maps produced by E-phase Radio Field methods have a number of
significant geological applications (Barringer, 1976), these being:
- mapping of sedimentary strata e.g. gravel deposits;
- exploration for kaolin;
350
- mapping of ice lenses in discontinuous permafrost zones; - exploration for geothermal areas; - hematite and manganese exploration.
13.10. Conclusions
A number of systems can be distinguished a.0.: Lidar or Laser Radar,
Radar, Radiophase and E-phase.
The Lidar systems operate in the short wavelength portion of the EMS.
Three different types of Aircraft Lidars can be mentioned: the Laser Profiler
OK Altimeter, the Mapping Lidar, the Raman and Fluorescence Lidar.
The Radar systems operate in the Microwave portion of the EMS in different
bands e.g. X = 0.75-1.1 cm (Ka-band), X = 2.4-3.75 cm (X-band) up to X = 30-100
cm (P-band), and different modes of polarization can be applied. Sidelooking
Airborne Radar (SLAR) and Synthetic Aperture Radar (SAR) are the main systems
for reconnaissance and exploratory mapping.
The properties of a target that determine the radar echo are: roughness,
slope, orientation and dielectric properties, as well as the presence of
resonant-sized objects.
Ground penetrating radar (GPR) may be used for the detection of boundaries
of soil horizons which show strong differences e.g. albic and spodic horizons,
OK the soil - rock boundary. Traverses with a maximum penetration depth of 3 to
10 m may be produced by moving the sender and the antenna along the surface.
Radar imagery shows some defects e.g. the fold-over of steep slopes, and
the occurrence of black radar shadows behind high objects, thus entirely
masking terrain features (shadows on airphotos show detail to some extent,
owing to scattering of low intensity diffuse sky light).
Radar imagery may be regarded as complementary to aerial photography in having
imaging capability in the domain between a =45' and a =lo".
Very Low Frequency (3-30 kHz) radiowaves may be used for conductivity and
resistivity mapping with penetration depths between 15 m and 150 m. At higher
frequencies, the measurements will be restricted to shallow penetration, which,
however, is important for soil survey.
Radar is extensively applied in environmental studies in South America.
The capability of radar to produce imagery independent of weather conditions
makes it an important aid in the making of a regional inventory of tropical wet
351
areas, and when a rapid recording of a terrain is required e.g. during or just
after flooding.
It is expected that the application of radar will be promoted through the
implementation of it in spaceborne systems and by the improvement of spatial
resolution. Research is needed to determine the capabality of remote sensing
with radiowaves for soil survey.
13.11 References.
Banyard, S.G., 1979. Radar Interpretation based on Photo-truth Keys. ITC Journal 1979-2, Enschede, The Netherlands: pp. 267-276.
Barringer, A.R., 1976. Airborne Geophysical and Miscellaneous Systems. In: Remote Sensing of Environment Ch. 8 (ed. by Lintz, J.Jr. and Simonett D.S.), Addison-Wesley Publ. Cy, London: pp. 291-322.
Beckman, J.A., 1975. Communications for Imaging Systems. Chapter 11 in Manual of Remote Sensing Vol I (editor Reeves, R.G.). her. SOC. of Photogrammetry, Virginia: pp. 589-609.
Bush, J.F. and Ulaby, F.T., 1978. An Evaluation of Radar as a Crop Classifie Remote Sensing of Environment, Elsevier North Holland: pp. 15-36.
Cihlar, J. and Ulaby, F.T., 1974. Dielectric Properties of Soils as a Function of Moisture Content. Remote Sensing Laboratory. Univ. of Kansas: 61 pp.
Collis, R.T.H. and Russell, P.B., 1976. Laser Applications in Remote Sensing In: Remote Sensing for Environmental Sciences. Ecological Studies 18, Springer Verlag, Berlin: pp. 110-146.
Foster, J.L., 1981.Multisensor Analysis of Hydrologic Features with Emphasis in the Seasat S A R . Photogrammetric Engineering and Remote Sensing. Vol. 47, No. 5: pp. 655-664.
Hardy, N.E., 1981. A Photo Interpretation Approach to Forest Regrowth Monitoring using Side-looking Airborne Radar Grant County, Oregon. Int. J. Remote Sensing, Vol. 2. no. 2: pp. 135-144.
Henderson, F.M., 1977. Land Use Interpretation with Radar Imagery. Photogram- metric Engineering and Remote Sensing, Vol. 43, No. 1: pp. 95-99.
Hickman, C.D. and Hogg, J.E., 1969-1970. Application of an Airborne Pulsed Laser for Nearshore Bathymetric Measurements. Remote Sensing of Environment, Vol. I. her. Elsevier Publ. Cy, Inc. New York: pp. 47-58.
Hoogeboom, P., 1982. Classification of Agricultural Crops in Radar Images. Int. Geoscience and Remote Sensing Symposium, Munich, June 1-4, 1982: 5 pp.
Innes, R.B., 1973. An Interpreter's Perspective on Modern Airborne Radar Imagery. In: The Surveillant Science. Remote Sensing of the Environment (ed. Holz, R.K.), Houghton Mifflin Cy, Boston: pp. 282-290.
Instituto Geogrsfico "Agustin Codazzi" et al., 1979. La Amazonia Colombiana y Sus Recursos. RepGblica de Colombia. Proyecto Radargrametrico del Amazonas, BogotL: 590 pp. y mapas.
Johnson, C.M., 1970. Laser Radars. In: Radar Handbook (ed.-in-chief Skolnik, M.I.), McGraw-Hill Book Cy, New York: pp. 37-1137-69.
Johnson, R.W., Glaccum, R. and Wojtasinski, 1980. Application of Ground Penetrating Radar to Soil Survey. Soil and Crop Science Society of Florida, Proc. Vol. 39: pp. 68-72.
Kasteren, H.W.J. van, Smit, M.K., 1977. Measurements on the Backscatter of X- band Radiation of Seven Crops throughout the Growing Season.
352
NIWARSfPubl. nr. 47, The Netherlands: 37 pp. and appendices. Kerr, D.E., 1951. Propagation of Short Radio Waves. Massachusetts Institute of
Technology, Radiation Laboratory Series, Vol. 13, McGraw-Hill Book Cy, New York.
Koopmans, B.N., 1973. Drainage Analysis on Radar Images. ITC Journal 1973-3, Enschede, The Netherlands: pp. 464-479.
Koopmans, B.N., 1974. Should Stereo SLAR Imagery be preferred to Single Strip Imagery for Thematic Mapping? ITC Journal 1974-3., Enschede, The Netherlands: pp. 424-444.
Lillesand, T.M. and Kiefer, R.W., 1979. Remote Sensing and Image Interpreta- tion. John Wiley & Sons, New York: 612 pp.
Long, M.W., 1975. Radar Reflectivity of Land and Sea. Lexington Books, D.C. Heath and Cy, London: 306 pp.
Loor, G.P. de, 1976. Radar Methods. In: Remote Sensing for Environmental Sciences, Springer Verlag, Berlin: pp. 147-186.
Loor, G.P. de, 1977. Microgolven en Gewassen. Symposium Luchtwaarneming. TH Delft, sept. 1977. Ned. Ver. voor Fotonica, "s-Gravenhage, The Netherlands: pp. 57-87.
MacDowall, J., 1972. A Review of Satellite and Aircraft. Remote Sensing Instrumentation. 1st Canadian Symposium on Remote Sensing: pp. 39-68.
Mekel, J.F.M., 1972. The Geological Interpretation of Radar Images. ITC Textbook of Photo-Interpretation Vol. VIII, Enschede, The Netherlands:
Ministerio das Minas E Energia of Brasil, Departamento Nacional Da Produsao Mineral, 1975. Projeto Radam. Folha SB 21 Tapajbs. Levantamento de Recursos Naturais Vol. 7. Rio de Janeiro: 409 pp. e mapas.
Moore, R.K. et al, 1975. Microwave Remote Sensors, Chapter 9 in Manual of Remote Sensing Vol. I (editor Reeves, R.G.). Amer. SOC. of Photogrammetry, Virginia: pp. 399-537.
Moore, R.K., 1976. Active Microwave Systems. In: Remote Sensing of Environment (ed. by Lintz, J.Jr. and Simonett, D.S.). Addison-Wesley Publ. Cy, London: pp. 234-290.
Moore, R.K., 1983. Radar Fundamentals amd Scatterometers. Chapter 9 in Manual of Remote Sensing, 2nd edition Vol. I. (editor Colwell, R.W.), Amer. SOC. of Photogrammetry, Virgina: pp. 369-427.
Moore, R.K. et al., 1983. Imaging Radar Systems. Chapter 10 in Manual of Remote Sensing 2nd edition Vol. I. (editor Colwell, R.N.), Amer. SOC. of Photogrammetry, Virginia: pp. 429-472.
Nunnally, N.R., 1969. Integrated Landscape Analysis with Radar Imagery. Remote Sensing of Environment 1, Amer. Elsevier Publ. Cy, New York: pp. 1-6.
Schmugge, T., Ulaby, F.T. and Njoku, E.G., 1978. Microwave Observations of Soil Moisture: Review and Prognosis. Goddard Space Flight Center, Greenbelt, Maryland, Soil Moisture Workshop, South Dakota State University: 28 pp.
Simonett, D.S., 1970. Remote Sensing with Imaging Radar: a Review. Geoforum 2 Journal of Physical, Human and Regional Geosciences. Pergamon, Vieweg Braunschweig, Germany: pp. 61-74.
61 PP.
Skolnik, H.I. ed., 1970. Radar Handbook. McGraw-Hill Book Cy. New York. Ulaby, F.T., Cihlar, J. and Moore, R.K., 1974. Active Microwave Measurement of
Soil Water Content. Remote Sensing of Environment 3, her. Elsevier Publ. Cy: p. 185-203.
Ulaby, F.T. Aslam, A. and Dobson, M.C., 1981. Effects of Vegetation Cover on the Radar Sensitivity to Soil Moisture. Remote Sensing Laboratory, Techn. Rep. 460-10, Univ. of Kansas, Lawrence, Kansas.
Ulaby, F.T., Moore, R.K., Fung A.K., 1981-82. Microwave Remote Sensing. Vol I and 11. Addison-Wesley Publ. Cy., London: 1064 pp.
353
Wiebe, M.L., 1971. Laboratory Measurements of the Complex Dielectric Constant of Soils. Texas A & M University, Remote Sensing Center. Techn. Report RSC-23: 19 pp. (fig. excluded).
13.12. Additional Reading.
Alexander, L. and Kritikos, H., 1980. An Investigation of the Autocorrelation Function of Radar Images. 6-th Canadian Symposium on Remote Sensing, May, 1980: pp. 154-158.
Attema, E.P.W. and Ulaby, F.T., 1978. Vegetation Modeled as a Water Cloud. Radio Sci, 13: pp. 357-364.
Attema, E.P.W., 1980. Satelliet Aardobservatie in het Microgolfgebied. Ruimtevaart. Orgaan van de Nederlandse Vereniging voor Ruimtevaart (NVR) POB 3166, 2601 DD Delft: pp. 68-83.
Dabrowski, H. et Rebillard, P., 1982. Applications, du Radar lat6ral a l'observation des Ph6nomSnes G6ologiques dans les Alpes Occidentales Francaises. Bull. SOC. G6ol. France, 1982 ( 7 ) , t. XXIV no 1: pp. 87-95.
Davies, D.H., 1970. Radar- a New Mapping Device. De Ingenieur Jrg. 82, nr. 33. Technisch Wetenschappleijk Onderzoek 6, Kon. Inst. V. Ingenieurs, The Netherlands: pp. 71-80.
In: SLAR Systems and Their Potential Applications to Earth Resources Surveys, Vol. 2. Prepared by EASAMS for ESRO, ESTEC Contract 1537/71 EL.
Elachi, C.L.A, 1982. Shuttle Imaging Radar Experiment. Science Vol. 218, No. 4576. Washington her. Ass. Adv. Sci: pp. 996-1003.
Haralick, R.M., Caspall, F. and Simonett, D.S., 1970. Using Radar Imagery for Crop Discrimination: A Statistical and Conditional Probability Study. Remote Sensing of Environment 1. Amer. Elsevier Publ. Cy: pp. 131-142.
Hirosawa, H., Komiyama, S. and Matsuzaka, Y., 1978. Cross-polarized Radar Backscatter from Moist Soil. Remote Sensing of Environment 1. Elsevier North-Holland: pp. 211-217.
Janse, A.R.P., 1974. Radarflecties van Gewas, Bos en Bodem. Landbouwkundig Tijdschrift/pt 86-12: pp. 316-321.
Janse, A.R.P., 1975. Reflections of Radar Waves by Soils, Crops and Forest: A Review of Some Recent Dutch Work. Neth. J. Agric. Sci 23: pp. 308-320.
Janse, A.R.P. en Bouten, W., 1980. Radarreflecties van Bodemoppervlakken. Cultuurtechnisch Tijdschrift Jrg. 19, Nr. 5., Utrecht, The Netherlands: pp. 268-270.
Jensen, H., Graham, L.C., Porcello, L.J. and Leith, E.N., 1977. Side-looking Airborne Radar. Scientific American, October 1977: pp. 84-96.
Koolen, A.J., Koenigs, F.F.R. and Bouten, W., 1979. Remote Sensing of Surface Roughness and Top Soil of Bare Tilted Soil with an X-band Radar. Neth. J . Agric Sci 27, Wageningen: pp. 284-296.
Leberl, F., 1974. Evaluation of SLAR image quality and geometry in PRORADAM. The ITC Journal 1974-4. Enschede, The Netherlands: pp. 518-546.
Lewis, A.J., MacDonald, H.C., 1970. Interpretive and Mosaicing Problems of SLAR Imagery. Remote Sensing of Environment 1, Amer. Elsevier Publ. Cy: pp. 231-236.
Loor, G.P. de, 1969. Possibilities and Use of Radar and Thermal Infrared Systems. Photogrammetria 24. Elsevier Publ. Cy Amsterdam: pp.43-58.
Peake, W.H. and Oliver, T.L., 1971. The Response of Terrestrial Surfaces at Microwave Frequencies, Ohio State Univ. Electroscience Lab. Techn. Rep. AFAL-TR-70-301.
Rao, R.G.S. and Ulaby, F.T., 1977. Optimal Spatial Sampling Techniques for
Deane, R.A. and Donville, A.R., 1972. Radar Scattering from Natural Surfaces
354
Ground Truth Data in Microwave Remote Sensing of Soil Moisture. Remote Sensing of Environment 6. Elsevier North Holland: pp. 289-301.
Rudd, R.D., 1974. Remote Sensing. A Better View. Duxbury Press, North Scituate Massachusetts: 136 pp.
Smit, M.K., 1977. Radarreflectie van Gewassen. Symposium Luchtwaarneming. TH Delft, sept. 1977. Ned. Ver. voor Fotonica, Is-Gravenhage, The Netherlands: pp. 156-166.
Tricart, J.L.F., 1979. Comparaison des Informations "Ecographiques" fournie par trois types de Radar. ITC Journal 1979-4, Enschede, The Netherlands: pp. 535-547.
Uenk, D. and Kasteren, H.W.J. van, 1978. Radarvluchten 1977. Oost- en Zuid Flevoland. Centrum voor Agrobiologisch Onderzoek CAB0 Int. Rep., Wageningen, The Netherlands: 18 pp.
Vermeer, J., 1970. Interpretatie van Radar- en Infraroodbeelden. De Ingenieur JKrg 82, nr. 33. Technisch Wetenschappelijk Onderzoek 6. Kon. Inst. V. Ingenieurs, The Netherlands: pp. 87-91.
White, L.P., 1977. Aerial Photography and Remote Sensing for Soil Survey. Clarendon Press, Oxford: 104 pp.
355
14,IMPLICATIONS OF REMOTE SENSING
Remote sensing is becoming more and more complex due to the increasing
number of acquisition and processing techniques. This complexity may cause it
to become less accepted and less used. However, some of the techniques have
found a definite place in environmental survey (par. 14.1).
For environmental inventories, the use of remote sensing tools is a
logical decision. Analysis of the environmental remote sensing data and the
field observations enables land evaluation as a step in the planning of
alternative ways of land use. The latter normally requires specific
interpretation aspects to be emphasized more than the normal aspects cansidered
for soil survey, and may be supported well by modern remote sensing techniques
(par. 14.2).
Methodology of environmental research, aided by remote sensing, should be
further developed with respect to data handling and field description
techniques (par. 14.3) . This is even more true, since many new techniques have
been created the last decade.
A view on near-future developments in remote sensing is presented in par. 14.4.
Finally, attention is paid in par. 14.5 to various political and legal
aspects, and in 14.6 to education and training in remote sensing.
14.1. Summary on applications
The conclusions given in the chapters 9 through 13 are summarized below.
Black- and -white panchromatic airphotos are the common tool for soil survey in
offering large, to medium-scale imagery with low cost stereoscopy. Black- and
-white Infrared airphotos may be used for showing differences in soil moisture
condition and vegetation cover types. To get even clearer imagery of the
latter, application of false colour aerial photography offers good
possibilities.
Multispectral photography is accepted as a research tool for agricultural
remote sensing projects, but is also promising for soil survey in regions with
large areas of bare soils.
The application of multispectral scanning in the Visible and near Infrared
is most promising i n arid areas and other areas where much bare soil
356
surface is present, at least during some time of the year. Satellite MSS e.g.
Landsat provides a synoptic view and has a multitemporal capacity. The latter
is very important for studies of the dynamics of the environment. The TM with
its better spectral and spatial resolution, broadens the application field of
the Landsat series.
Scanning techniques are also applied for sensing the thermal Infrared. The data
may be used for studies of soil moisture balance and evaporation.
Radar may be applied in reconnaissance and exploratory mapping. The
capability of radar to produce imagery independent of weather conditions makes
it an important aid in regional inventorying of tropical rain-forest areas. The
so-called ground penetrating radar may be used in the terrain for detection of
boundaries between s o i l horizons which show strong differences in texture or
moisture content.
14.2. Land evaluation
Besides airphoto-interpretation (par. 9 . 4 ) , other remote sensing
techniques may be applied in studies on land evaluation, such as:
-airborne MSS using bands in the NIR and Visible; for determination of terrain
features;
lnultitemporal satellite MSS data; for identification and mapping of land use,
crops and natural vegetation by using crop OK natural vegetation calendars;
-thermal IRLS; for studies of crop or soil temperature and moisture balance
(see Rose and Thomas, 1968);
-radar; for determination of terrain features, the acquisition being not
dependent on weather conditions.
It has been emphasized that multitemporal studies are of great value, since
land evaluation is concerned with the ecology of the agricultural and natural
environment. The dynamics of the environment influence the growth of plants
enormously. It is the influence of the environment as shown by the growth of
natural vegetation or crops during a period of time, which is a major subject
of study.
Satellite MSS (especially TM) can be applied to obtain estimates on
biomass throughout time. Thus, different land units can be compared and
evaluated with regard to their productivity.
The following examples of environmental mapping which are aided by remote
sensing techniques, illustrate once more the potential of remote sensing as a
351
tool in land evaluation studies:
-monitoring of natural processes aided by the detection of changes;
-surfacial water mapping for flood conditions (flood hazard); sequential
observations (time difference: hours or days) may provide estimates on run-off
OK intake rate;
-soil mapping; more specific information about soil moisture condition or
about roughness of the soil surface may be obtained; in this connection the
area of eroded or bare land is important, too;
-land use mapping and soil management; e.g. acreage of land under cultivation
and fallow land, OK conservation measures;
-vegetation mapping; e.g. areas of green vegetation; vegetation damage by
fire, wind, water, hail OK diseases.
Finally, attention is drawn to the application of large-scale airphotos in
studies of landscape design. Airphoto-interpretation enables a first inventory
of features which can be used for an evaluation of the actual physiognomy.
Some important features, which can be studied for this purpose by airphoto-
interpretation, are:
-the distribution of high objects (e.g. houses, dykes and dunes or vegetation
higher than 2 m);
-the surface area, form and distribution of waterbodies, of marsh and dry
land ;
-the type and distribution of vegetation cover types;
-the expected transparency of tree OK shrub TOWS.
14.3. Methodology
It is no secret that many advanced high resolution systems as well as data
processing systems are only available for military use and that security
ratings have a negative effect on the development of remote sensing for
peaceful purposes.
However, the systems available for civilian use already produce quantities
of data, too large for the processing facilities. A first generation Landsat
MSS produces 15 megabit s-l while the TM generates at least lo4 megabits s-' .
Some authorities consider that a data stream below 5 megabits s-l would he most
suitable for a remote sensing system. It is evident that there is a need for
studies on data compression (Barrett and Curtis, 1982), and that we should be
careful with application of high resolution systems which produce tremendous
358
amounts of data.
Compression of MSS data may be reached in processing on different ways,
such as:
-ratios enhancing certain phenomena of the land surface;
-PCT of a sample set;
-multitemporal combinations.
Normally, there is a phase of visual interpretation and a first approach
to physiographic description and classification of the area. The physiographic
units are characterized by their relative location and landsurface properties.
The land surface properties may be classified using certain algorithms; the
results have to be checked in the field.
Furthermore, change detection may help in a number of cases to characterize
processes, and pattern recognition aids to describe the distribution of objects
OK phenomena in the units.
The data accumulated from remote sensing systems can be put in systems
capable of efficient data storage and expedient data processing and retrieval,
the so-called Geographic Information Systems ( G I S , Simonett et al,, 1983). GIS
is an information system which enables assembling and analyzing diverse data of
specific geographic areas, using the spatial locations of the data as a basis.
The data can be channelled to the level at which decisi.on making takes place.
Remote sensing data may improve the information on natural resources and as
such they are essential as an input to the G I s .
Models are needed to explain the complex natural soil system. The models
are used to build up a hypothesis during the interpretation of remote sensing
data. Dijkerman (1974) has given a characterization of models according to
their nature, function and design (see table 14.1)
Some notes are given for explanation of table 14.1 (for more information, the
reader is referred to the original publication).
Concrete models consist of real physical objects (soil column or soil samples)
that stand model for the system under study.
Conceptual models use abstract concepts created in the human mind.
Scale models are models in which the system to be studied, is scaled down (OK
up) to a size or number convenient for study or comprehension.
359
Table 14.1 Characterization of models after Dijkerman (1974).
Characterzation of models Nature of models 1. concrete model
2. conceptual model a. mental model b. verbal model C. structural model d. mathematical model
Function of models 1. observation model 2. experimental model 3. descriptive model 4 . explanatory model 5. predictive model
Design of models 1. scale model 2. idealized model 3. analogue model 4. computer simulation model
The models used in remote sensing studies may be characterized according to:
- their nature in conceptual models (mental, verbal or structural);
- their function in observation, descriptive, explanatory and predictive
models;
- their design in scale and analogue models.
The modern remote sensing techniques, e.g. the TM, make a quantitative
correlation of field data with remote sensing data within reach. For this,
knowledge of the interaction process of EMR with objects at the earth's surface
is needed.
Since most remote sensing techniques have a limited penetration capability, we
may concentrate at this stage on the properties of the landsurface.
A first subdivision of parameters of the land surface which are important
for the interaction process can be made as follows:
1) reflective and absorptive properties of the surface
a) roughness producing shadow in forward (and reflecting surfaces in
backward) direction
soils and rocks - soil texture, surface texture of minerals,
- structure, slaking, tillage,
- stoniness, rock outcrops,
- micro-relief, meso-relief,
- height, structure, type, X of coverage; vegetation
360
b) contribution of the reflecting surface
soils and rocks - colour and mineralogical composition,
- organic matter content,
- moisture content,
vegetation - green vegetation %,
- dead foliage %, and other remains,
- COlOuK,
free water and ice,
c) contribution of shadow areas through scattering of skylight;
2) slope and orientation
- slope (angle, form, length) and exposition,
- orientation of objects e.g. strike of slopes, vegetation, dunes or
furrows.
Consideration of these parameters and convential ways of describing the
soil and land surface (Guidelines, FAO, 1977) reveals that generally the degree
of detail does not enable a proper correlation of field data with remote
sensing data (Mulders, 1986).
More quantitative ways of describing the land surface have to be developed.
Generally spoken, real percentages of sand, gravel etc. have to be taken into
account in stead of broad classes. All parameters of the land surface including
dunes, live vegetation and vegetation remains have to be quantified with regard
to their nature, distribution , coverage and orientation.
If correlation of land surface parameters and remote sensing data is made
possible, the basic maps for the GIS can be improved and dynamic features can
be monitored with the aid of satellite systems. One can reach the phase of
understanding processes in a quantitative way and the models can be predictive,
thus serving decision making and appropriate action.
An example of the use of satellite remote sensing in environmental management
is the FA0 Development Project on Remote Sensing Applications for Desert Locust
Survey and Control (Hielkema, 1982).
14.4. Recent and future developments
Below the recent and future developments are summarized by taking regions
or nations involved in the developments of systems as a starting point.
361
1.
a.
b.
C.
USA
Organisations such as National Aeronautics and Space Administration or
NASA, U.S. Geological Survey, EOSAT EKOS Data Center (Sioux Falls),
Optical Systems Division of Information Technology (ITEK) and GEOSAT
(Committee industries and companies mainly from USA) provide for
continuing efforts in:
the Landsat and TM series,
the Oceanographic Research Satellites (the first one was the Seasat 1 in
1978 using Infrared and Microwaves),
the Space Shuttle manned space flight (the first launch of a Space
Shuttle Vehicle was in 1981; see Simonett et al., 1983).
---
The Shuttle Imaging Radar (SIR) may be taken as an example for the
diversity in research of the Shuttle Missions (see Koopmans, 1983):
SIR-A, 1981 with L band S A R and horizontal polarization,
SIR-B, 1984 item SIR A but with selectable radar look angles,
SIR-C, 1987 with L band and C band SAR and multiple frequencies and
polarizations.
!e_w-c2nce!cs The U . S . Geological Survey is examining the feasibility of a new
satellite system, the so-called Mapsat (U.S. Geological Survey, 1981).
Mapsat is based on the Landsat mission, including the original Landsat
orbit and data communication system. The Mapsat concept incorporates
capabilities such as:
a 10 m resolution,
spectral bands 0.47-0.57 mn, 0.57-0.70 um and 0.76-1.05 m, stereoscopic coverage on a demand bases.
The Geosat committee examines the feasibility of Stereosat, a linear
array sensor system with spatial resolution of 15 m, temporal resolution
of 48 days and along track stereoscopic coverage (Hempenius et al.,
1982).
!?theE-Res?SG Since 1969 research has been conducted to develop a technique using
natural gamma radiation attenuation to measure snow water equivalent and
362
soil moisture from low-flying aircraft. The gamma flux from the soil is a
function primarly of the water content and radio-isotype concentration
( 4 0 K, 238 U and ' 0 8 T1) near the surface.
The gamma radiation technique is capable of measuring soil moisture
values in the upper 20 cm of the soil surface with the accuracy (RMS of
3.9 %) required for operational hydrologic and agricultural applications
(Jones et al., 1983).
2. Western Europe
a. European Space Agency OK ESA. ESA has developed a launch vehicle called
ARIANE, which is capable of delivering a payload of 1700 Kg into a
geostationary orbit.
A joint venture between NASA and ESA is the development of Spacelab, to
he transported by the Space Shuttle orbiter (Spacelab 1, 1983).
Of particular interest in Spacelab are the Metric Camera Facility (MC)
and the Microwave Remote Sensing Experiment (MRSE). The MC is a standard
Zeiss 30/23 aerial camera with a 30 cm focal length and a 23 x 23 cm
format. The images cover an approximate ground area of 190 x 190 km with
a ground resolution of approximately 20 m. An eighty percent overlap of
consecutive photographs is obtained. For first results of interpretation,
see Girard (1985).
Later on, a camera with 60 cm focal length is planned as well as mounting
on free-flying satellites.
The MRSE operates as a two-frequency scatterometer to measure hackscatter
from the ocean surface at two adjacent frequencies and as a thermal
radiometer to measure surface temperature (Simonett et al, 1983).
--------------
New concepts are: the ESA Resources Satellite-1 (ERS-1) and Advanced ESA
Resource Satellite (AERS).
The ERS-1 is directed to ocean observation and is planned for launch in
1987. The sensor payload aims the following:
- C-band S A R with 30 x 30 m ground resolution and a 80-100 km swath,
- an Infrared radiometer with channels at wavelengths of 3.7 ~nn and 12 Inn
and IFOV of 1 x 1 km,
- a Microwave Radiometer with two channels at 23.8 GHz and 36.5 GHz, - a three beam C-band scatterometer for measuring wind direction and
velocity,
363
- a radar altimeter a.0. for sea-state determination (Haskell, 1983).
The AERS is directed to land observation and has been proposed for launch
around 1989. Its payload is to include the S A R , from ERS-1, an Optical
Imaging Instrument (011) with six spectral bands in the range between
0.52-2.35 um and and IFOV of 30 m; furthermore, one panchromatic band
with a 15 m IFOV, and a 175 km swath (Simonett et al., 1983).
b. France a.0. Centre Nationale Etude Spatiale or CNES (Toulouse).
In 1986, the French* earth observation satellite or Systsme Probatoire
d'observation de la Terre (SPOT-1) was launched by the ARIANE.
This satellite was placed in a sunsynchronons orbit at a mean altitude
(45' Northern latitude) of 832 km. The orbit has an inclination of
98.70', the mean local solar time at descending node is 10:30 hrs. The
temporal resolution of 26 days can be enlarged using the steerability of
the socalled HRV instruments (Chevrel et al., 1981). The HRV or High
Resolution Visible imaging instruments comprise a pushbroom scanner with
linear arrays which operate in either of two modes:
- a three-band multispectral mode with the bands 0.50-0.59 rn , 0.61- 0.68 um and 0.79-0.89 Um (for selection see Begni, 1982), having a
ground resolution of 20 m;
- a black- and -white panchromatic mode (0.51-0.73 m ) with a ground
resolution of 10 m.
The steerable HRV instruments enable off-nadir viewing. Thus they offer
the possibility of obtaining stereoscopic pairs of images by the lateral
stereoscopy principle. Two images can be obtained of a given scene on
successive satellite passes on either side of the vertical. This
improvement is very important for the application of SPOT in landscape
analysis.
There will be no complete world wide SPOT coverage. The user has to
request for acquisition of unique, multitemporal OK stereoscopic coverage
(Rivereau, 1984).
C. The Netherlands Agency for Aerospace Programmes (NIVR), in cooperation
* Sweden and Belgium participate in the program.
364
with Indonesia, have planned the development of a Tropical Earth
Resources Satellite (TERS) which would carry a multispectral linear array
sensor. An equatorial orbit and orbital altitude of 1680 km, besides a
so-called cloud detector in forward direction to select cloud free areas
for data acquisition, are planned. The TERS will have a very high
temporal resolution being 11 times per day. Furthermore, three spectral
bands with a ground resolution of 16 m and a panchromatic band with a
ground resolution of 8 m are part of the proposed system (Van
Konijnenburg, 1984).
3. U.S.S.R.
The Salyut 6, placed in orbit in 1977, has carried several multispectral
film camera systems for earth observation.
Certain missions in the Cosmos series were also designated as Earth
Resource Observation Spacecraft. The latter have low orbital altitudes
(220-270 km) and are recovered after 15-30 days of operation (U.S. Geol.
Survey, 1982).
In June 1980, the "Meteor" satellite was launched including a.0. a sensor
package known as "Fragment". It consists of an optical-mechanical
scanning unit with 80 m ground resolution at nadir and the following
spectral bands:
0.4-0.8 pm, 0.5-0.6 um, 0.6-0.7 pm, 0.7-0.8 pm, 0.7-1.1 !.nn, 1.2-1.3 m, 1.5-1.8 um and 2.1-2.4 pm (Sirnonett et al., 1983).
4. N _ a t i ~ " a l - ~ E ~ ~ e - _ A 9 e ~ ~ ~ - ~ ~ - ~ ~ ~ _ a ~ - ~ ~ - ~ ~ ~ ~ ~ NASDA plans the launch of the MOS-1 or Marine Observation Satellite 1 at
the end of 1986. The orbital altitude is 909 km. It carries a payload of
three instruments:
- a Multispectral Electronic Self Scanning Radiometer (MESSR) with four
spectral bands between 0.51 and 1.10 um, a 50 m IFOV and a 100 km swath;
- a Visible and Thermal Infrared Radiometer (VTIR) with a 500 km swath, one
band in the Visible with a 0.9 km IFOV and three bands in the Infrared
between 6.0 and 12.5 pm with an IFOV of 2.6 km;
- a two-frequency Microwave Scanning Radiometer (MSR).
If this satellite is successful, a second and third spacecraft may be
launched. Furthermore, an earth resources satellite is planned which will
365
Carry a linear-array stereo camera and an SAR (Simonett et al., 1983).
5.
6 .
7.
Some
Canada
The Canadian Radarsat is scheduled for launch in 1990. It is planned to
carry a C-band or L-band SAR. It is designed to provide information on
the ocean as well as the land surface (Raney, 1982).
------
Indian Space Research Organisation ( ISRO)
The ISRO developed an earth observation satellite (e.g. Bhaskara-2
launched in 1981) which carries a two-band television camera system and a
two-frequency Microwave radiometer system.
.........................................
The Peoples Republic of China
Several satellites have been launched since 1975. Chinasat 10 was to
Carry a two channel meteorological radiometer with Visible and Infrared
bands. A 11-band multispectral scanner, linear array sensor and S A R were
announced to be developed in 1984 (Simonett et al., 1983).
.............................
general trends are likely to continue in future (Barrett and Curtis
1982) :
- national and international commitments to remote sensing will increase
the ground receiving stations for satellite data will become more
numerous, often linked to centralized data-processing facilities;
- more new satellite series and concepts will be designed and tested;
- more nations will join the once select club of the USA and USSR operating
environmental satellites of their own;
- satellite data analyses will increasingly combine data from different
satellite systems and convential sources for maximum benefit to the user.
More specific with regard to the remote sensing systems, the following trends
can be observed:
- the development of systems with higher spatial resolution;
- improvement of the radiometry and spectral resolution;
- the increased application of S A R and thermal Infrared radiometers in
satellite systems;
- emphasis on data compression techniques;
366
- research in multidirectional information to obtain a.0. stereo images;
- more research after selection of spectral bands providing for specific
information.
Research in the Infrared has to be directed to spectral signatures. The
spectral features in the mid and far Infrared (Tables 2.3 and 2.4), and the
position of the atmospheric windows (Fig. 2.12) indicate potential information
in the following bands (Mulders, 1986):
bands-!!?--!%- 3.40 - 4.10
4.50 - 5.10
9.00 - 10.00 10.00 - 13.00
potential information
C-H, C-H2, C-H3 (organic matter)
oxides, Si-0
phosphates, sulphates, Si-0
A1-OH, carbonates, H-0-A1,
Si-0-Si, A1-0-Si
___-_---__-----------
14.5. Political and legal considerations
There is nothing inherently bad, immoral, or unlawful about remote sensing
unless the products produced are used detrimentally against anyone. However,
the potential for the above by using remote sensing information does exist
(Lins, 1985).
Since the invention of the aircraft, we have assumed that property rights do
not extend into the space over the land. No permission is needed to fly over
one's land holdings. However, an individual, a company or government would be
held liable for damage caused by the aircraft.
In using satellites for earth observation, legal questions of surveillance are
disregarded and it is considered to be permissible to gather data about another
country. However, these data can be interpreted into terms of natural resources
e.g. the potential occurrence of petroleum and mineral resources OK may be used
for global crop forecasting (Mac Donald et al., 1985).
As noticeable a.0. in the United Nations Committee on the Peaceful Uses of
Outer Space, several nations (e.g. Brazil and Argentina) have become seriously
concerned about international regulations.
The Soviet Union and France have proposed the following set of governing
principles (Lins, 1985):
a) any remote sensing state must transmit to a sensed state, on mutually
367
acceptable terms, information the former obtains regarding the natural
resources of the latter;
b) no state which obtains, through remote sensing, information concerning
the natural resources of another state shall make that information public
without the prior consent of the latter state;
c) remote sensing of earth resources shall respect the principle of
permanent sovereignty of states over their wealth and resources.
14.6. Education and training
Technology transfer may be defined as the process by which scientific
knowledge and the skills to apply that knowledge, are transferred. The transfer
is often a complex process that involves significant differences in perceived
needs, institutional structures and available resources.
Many technicians in advanced countries are familiar with the principles
underlying remote sensing, so that the users' community realizes its potential
and limitations. This may be different in developing countries (Simonett et
al., 1983).
Specialists of almost 120 countries have purchased Landsat data from the
EROS Data Center. Of these countries, roughly two-thirds belong to the
developing world (National Academy of Sciences, 1977). In a number of these,
institutions or other government agencies have the task to conduct or control
remote sensing operations. These centres are of great importance to the
development of remote sensing.
The National Academy of Sciences (1977) has formulated the following
requirements for remote sensing centres:
a) a remote sensing centre should employ trained personnel with a
concentration of scientific skills;
b) data analysis should be conducted through an interaction among personnel
with diverse disciplinary training;
c) there should be strong ties between the remote sensing centre and the
users' agenciee, concerning the level of data flow, and the priorities of
data collection and processing;
d) the remote sensing centre should have ground truth studies for
confirmation of remote sensing studies;
e ) the centre should be capable of handling remote sensing data from a
variety of platforms;
368
f) the centre should have the facilities for efficient data storage and
retrieval;
g) the centre should have the capacity for making an overview analysis on a
national OK regional scale.
The centres can be of great importance in education and training as to remote
sensing, but there is still a need for courses on remote sensing for students
of developing countries (Mulders, 1978).
Although students of developing countries can take classes at the various
universities (entrance levels often differ per country and/or per university),
they generally prefer to attend courses specially organized for this purpose,
such as:
- the courses at the International Institute for Aerial Survey and Earth
Sciences (ITC/Unesco Centre) in Enschede, The Netherlands;
- the courses at the IPI, Indian Photo-interpretation Institute (Dehra
Dun),
the CIAF (Centro Inter-American0 de FotointerpretaciBn) in Bogota
(Columbia) OK at the Regional Centre for Training in Aerial Surveys in
Ile-If e (Nigeria).
In this connection, MSc-courses (including training on airphoto-interpretation
and often also other remote sensing techniques) should be mentioned e.g.:
- Land Resource Management or Planning at the Land Resource Division,
Tolwooth, United Kingdom;
- Pedology and Soil Survey, Univ. of Reading, United Kingdom;
- Geomorphology, Univ. of Sheffield, United Kingdom;
- Soil Survey and Land Evaluation, Agricultural Univ., Wageningen, The
Netherlands.
In other cases special training programmes may fulfil the specific needs.
Such programmes are offered by various organizations, e.g. the FA0 (Rome), the
EROS DATA CENTRE (U.S.A.) and SOGESTA Cy (Urbino, Italy). The latter course is
organized in cooperation with UNEP, the United Nations Environment Programme.
Another form of contribution towards the needs of developing countries in
educating specialists in remote sensing, are the shortterm training seminars,
courses and workshops organized under the United Naffons Programme on Space
369
Applications. The Committee on the Peaceful Uses of Outer Space plays a co-
ordinating role. The awarding of fellowships is possible in connection with
this programma.
14.7. References
BaKKett, E.C. and Curtis, L.F., 1982. Introduction to Environmental Remote Sensing ( 2 nd. ed.). Charman and Hall, London: 352 pp.
Begni, G., 1982. Selection of the Optimum Spectral Rands for the SPOT Satellite. Photogrammetic Engineering and Remote Sensing Vol 48., No. lo. , Amer. SOC. of Photogrammetry: pp. 1613-1620.
Chevrel, M., Courtois, M. and Weill, G., 1981. The SPOT Satellite Remote Sensing Mission. Photogrammetric Engineering and Remote Sensing Vol. 47, No. 8, Amer. SOC. of Photogrammetry: pp. 1163-1171.
Dijkerman, J.C., 1974. Pedology as a science: the Role of Data, Models and Theories in the Study of Natural Soil Systems. Geoderma, 11, Elsevier Scient. Publ. Cy, Amsterdam: pp. 73-93.
FAO, 1977. Guidelines for Soil Profile Description. Girard, M.C., 1985. InterprQtation PQdologique des Photographies prises par
Spacelab 1. ITC Journal PKOC. 4th Symp. of Isss. Working Group Remote Sensing for Soil Survey (Wageningen and Enschede, The Netherlands).
Haskell, A., 1983. The ERS-1 Programme of the European Space Agency. ESA Journal 1983, Vol. 7. ESTEC, Noordwijk, The Netherlands: pp. 1-13.
Hempenius, S.A., Marwaha, B.S., Murialdo, A. and Wang Ren-Xiang, 1982. The second generation of Earth Observation Satellites. Communication ITC Enschede, The Netherlands.
Hielkema, J.U., 1982. Satellite Remote Sensing, A new Dimension in international Desert Locust Survey and Control. FAO, Rome, 010680: 10 pp.
Jones, W.K. and Carroll, T.R., 1983. Error Analysis of Airborne Gamma Radiation Soil Moisture Measurements. Agricultural Meteorology, 28. Elsevier Scient. Publ. Cy, Amsterdam: pp. 19-30.
Koopmans, B.N., 1983. Space-borne Imaging Radars, present and future. ITC Journal 1983-3, Enschede, The Netherlands: pp. 223-231.
Lins, H.F. JK., 1985. Some legal considerations in Remote Sensing. In the Surveillant Science: Remote Sensing of the Environement (R.K. Holz ed.) John Wiley & Sons, New York: pp. 382-388.
Mac Donald, R.B. and Hall, F.G., 1985. Global Crop Forecasting. In the Surveillant Science: Remote Sensing of the Environment (R.K. Holz, ed.), John Wiley & Sons, New York: pp. 389-406.
Mulders, M.A., 1978. Education and Research on Remote Sensing for Soil Survey. A first approach to Inventory. ISSS Working Group Remote Sensing for Soil Surveys. Agric. Univ. of Wageningen, The Netherlands. Dept. of Soil Scce. and Geology, Publ. nr. 669: 35 pp.
Mulders, M.A., 1986. The Significance of detailed Description of the Land Surface for understanding of Remote Sensing Data. Transactions ISSS Congress Hamburg 1986: pp. 1220-1221.
Mulders, M.A., Schurer, K., Jong, A.N. de and Hoop, D. de, 1986. Selection of bands for a newly developed Multispectral Airborne Reference-aided Calibrated Scanner (MARCS). Proc. of 7th ISPRS VII) SYmP. on Rem. Sens. for Res. Devel. and Envir. Management. Enschede, The Netherlands: pp. 301-303.
National Academy of Sciences, 1977. Remote Sensing from Space: Prospects for Developing Countries. Report of the Ad Hoc Committee on Remote Sensing.
370
Raney, R.K., 1982. Radarsat-Canada's National Radar Satellite Program. Inst. of Electr. and Electronics Eng., Geoscience and Remote Sensing SOC. Newsletter, Vol. X X I , no. 1: pp. 5-9.
Rivereau, J.C., 1984. Access to SPOT Data and Product Distribution. ITC Enschede, The Netherlands, Seminar on SPOT Technology and Applications 25-26 January 1984: p. 8.
Rose, C.W. and Thomas, D.A., 1968. Remote Sensing of Land Surface Temperature and some Applications in Land Evaluation. Paper of CSIRO. Symposium 26-31 August 1968: 9 pp.
Simonett, D.S. et al., 1983. The Development and Principles of Remote Sensing. Chapter 1 in manual of Remote Sensing 2nd edition (R.N. Colwell, editor). her. SOC. of Photogrammetry. Falls Church, Virginia: pp. 1-35.
U.S. Geological Survey, 1981. Landsat Data Users Notes Issue No. 17, Eros Data Center, Sioux Falls: pp. 2-4.
U.S. Geological Survey, 1982. Landsat Data Users Notes Issue No. 21 and 24, Eros Data Center.
Van Konijnenburg, R., 1984. Stand van zaken in het TERS Project. Ruimtevaart, Orgaan v.d. Nederlandse Vereniging voor Ruimtevaart (NVR) Delft, The Netherlands: pp. 44-46.
14.8. Additional reading
Hempenius, S.A., 1974. How can ecology prepare itself for remote sensing? ITC
Kinnucan, P., 1982. Earth-scanning satellites lead Resource Hunt. High
Voute, C., 1983. Education and Training in Remote Sensing for Resource
Journal, Enschede, The Netherlands: pp. 561-571.
Technology Vol. 2, No. 2. Techn. Publ. Cy. Boston, USA: pp. 53-60.
Development. ITC Journal, 1983-1: pp. 34-42.
371
Plate 1.
Plate 2.
False colour airphoto of an area in the Netherlands (Graafschap) Z= 1520 m, scale 1:10,000. Camera Wild RC8, wide angle c= 152.35 nun, lenstype UAg 432, AV filter 1.4X, Wratten 12. Film: Ektachrome Infrared 2443. Acquisition KLM Aerocarto, The Netherlands.
Multemporal band 5 combination of 1st generation Landsat; Calatayud area, Spain. Diazo: yellow January '75
ma gent a June ' 7 5 cyan September '75
Plate 3.Fragment of the ITC Colour Chart (derived from the Ostwald Colour System). The colours are composed by colour dots. The sequence, in which colours are indicated, is as follows: first figure yellow, second figure magenta, third figure cyan. Colour code numbers: O= O X , 1= lo%, 2= 20%, 3= 35%, 4= 50%, 5= 70%, 6= 100%. Example: 561= 70% yellow + 100% magenta + 10% cyan.
Plate 4. 1st generation Landsat. PC1 (green) and PC2 (red) colour combination of 4 September '76 of the Calatayud area, Spain (courtesy: ITC).
Plate 5.Classification using Ward's clustering method (digital data of 1st generation Landsat of June '76) Legend: white= gypsiferous areas with extremely low vegetation coverage very dark green= moderate coverage of Quercus ilex or Pinus
dark green= low to moderate coverage by low shrubs and herbs olive green= grapes, wheat, bare brown soil or greyish soil and
light green= mainly orchards red= badlands with marl or gypsiferous material, moderate coverage by
light blue= water
halepensis
almonds
lichens and extremely low coverage by low shrubs and herbs
372
373
374
ABBREVIATIONS, SYMBOLS, UNITS OF MEASl GENERAL
AEM Application Explorer Mission ATS Application Technology Satel-
C-band Microwaves A = 3.75-7.5 cm CCD Charge Coupled Device CCI Charge Coupled Imager CCT Computer Compatible Tape EM Electromagnetic EMR Electromagnetic Radiation EMS Electromagnetic Spectrum ERS ESA Resources Satellite ERTS Earth Resources Technology
ESA European Space Agency GOES Geostationary Operational
GPR Ground Penetrating Radar GR Ground Range HCMM Heat Capacity Mapping Mission HF High Frequency 3-30 MHz IFOV Instantaneous Field of View IR Infrared IRLS Infrared Line Scanning L-band Microwaves A = 15-30 cm MSP Multispectral Photography MSS Multispectral Scanning MTF Modulation Transfer Function NASA U.S. National Aeronautics and
Space Administration NIR Near Infrared NOAA National Oceanographic and
Atmospheric Administration PC Principal Component PCT Principal Component Transform Radar Radio Detection and Ranging RAR Real Aperture Radar RBV Return Beam Vidicon RCS Radar Cross Section pixel Picture element
lite
Satelite
Environmental Satellite
JRE
SAR Synthetic Aperture Radar SLAR Side Looking Airborne Radar SMS Synchronous Meteorological
Satellite SPOT Systeme Probatoire d'0bservation
de la Terre TIROS Television Infrared Observation
Satellite TM Thematic Mapper W Ultraviolet VHF Very High Frequency 300-3000 MHz VLF Very Low Frequency 3-30 kHz X-ray Rijntgen X-hand Microwaves A = 2.4-3.75 cm
SYMBOLS PHYSICAL ASPECTS
A f h I LE
mf
m
n Tc
L
E
E
€0
amp 1 it ude frequency (s-l) height (m) above reference plane intensity of radiation (W) Latent heat flux, evapotranspi- ration (wm-2) soil moisture as X of field capacity actual gravimetric moisture content index of refraction crop surface temperature emissivity (0-1) dielectric constant (Fm- )
relative dielectric constant
1
E for vacuum
E ' real part of dielectric constant E" imaginary part of dielectric
0 angle of incidence constant
i
375
angle of refraction wavelength of EMR (m) reflectance % surface component of reflectance internal component of reflectance reflectance horizontally polarized radiation reflectance vertically polarized radiation
SYMBOLS A S P E C T S A E R I A L PHOTOGRAPHY
B B*
C
D E h N
RS
S V Z
air base (m) reflecting power of image components (W) focal length (mm) photographic density exposure (cd s-l) height difference (m) nadir point system resolution in line pairs per mm scale vertical exaggeration flying altitude
a angular field o f view Y slope of D - E curve Ap parallax difference (mm)
SYMBOLS T E C H N I C A L A S P E C T S
effective aperture of receiving antenna (m) gain of transmitting antenna in direction of target (m)
4
Gt
a grazing angle 9 depression angle a effective back scattering
area (m*) a differential scattering
coefficient (dR) 0
U N I T S OF MEASURE
Basic units and symbols of SI (Systgme International d'Unit6's) : length meter m mass kilogram kg time second s electric current ampdre A temperature kelvin K luminance candela cd amount of substance mol mo 1 The two supplementary units are: angle radian rad solid angle staradian sr
From the basic units the following SI-units are derived: pressure force energy power frequency elect ri ca 1 charge electr. tension electr. resistance e 1. conductivity electr. capacity
magnetic induction temperature
pascal Pa =N.m-' newton N =Kg.m.s joule J =N.m watt w =~.s-l hertz Hz =s-l coulomb C =A.s volt V -1J.A-l ohm =V.A-' siemens s = n -1 farad F = C . T 1
tesla T=kg.s-2A-1 degree Celsius " C Kelvin K
-2
The following prefixes and factors are used :
giga G lo9 deci d 10-1 micro P mega M 106 centi c 10-2 nano n 10-9 kilo k l o3 milli m lod3 pic0 p
376
I N D E X
absorptance 37 absorption bands (0.4-2.5 m ) 48-50 absorption factor 25 absorptivity atmosphere 41 accessability of terrain 231 actinolite 56 additive colour viewing 153 aerial film speed 169-170 AERS 365 age of soil (interpr.) 207-208 Agfacontouring 153 airbase 158 airborne line scanner 109-110
airphoto-interpr. legends 219-222,
amphibole 56 anastomotic drain. p. 193 anisotropic crystals 22 annular drain. p. 198-199 antenna temperature 39 antivignetting filters 100 ARIANE 364 ASA 169 aspect analysis 182-183, 267 atmospheric correction 267
- platforms 112-113
226
- influence 1 16 windows 40-41, 45, 249- -
250 automated classification 278-2817
backscattering maximum 36 basic aspects interpr. 182 batch processing 132 Bhaskara-2 367 biotite 56 blue grama grass 250 Roltzmann's constant 16 Brasil 340-343 Rrewster angle 3 1 brightness 143
Calatayud &sin interpr. 267-280 calcite 57 carbonate 58 characteristic curve (film) 126-127 charge coupled device 111 Chinasat 367
chloroplasts 76 chlorophyll 76, 78 colinear drain. p. colour vision 98-101 complex reflactive index 26 compound aspects interpr. 182 cones (eye) 94-95 Cosmos series 366 cotton leaf temperature 84-86 crab 160 crop calendar 269 drops (interpr.) 203
datastream 359-360 decibel 44-45, 322 dendritic drain. p. 198-199 density (film) 126
slicing 152 deranged drain. p. 193 detectahility 142 dielectric constant 23, 326-329 - relative 23-25
diazo-film 129-131 dichotomic drain. p. 194-195 differential scattering coefficient
322 diffraction 32-33 dimensional stability (film) 128 directional reflectance soils 64-69
dodging 128 Doppler effect 316, 321 drainage condition 205
drift 160 earth emittance 18-19 education, training 369-371 electronic energy state 20 ellipsometer 119 elongated bay type 194-195 emissivity 17, 39, 58-59, 70, 83 EM spectrum 14-16 EM waves 12-13 E-phase system 348, 349-350 erosion interpr. 208, 227-228 ERS-1 364-365 extinction coefficient 42, 325 eye, aberrations 97
-
- plants 81-82
- density 195-197
371
facet model 33-34 false colour photography 105-109,
feature plane plot 133-134 feldspar 55 field atennuation coefficient 326 field work 223-225 - tropical forest 225 filter factor 102 fluorescence 37 - lidar 315 forest damage 80 forward scattering maximum 36 fragment sensor 366 frame aerial mapping camarea 157-158 Fraunhofer criterion 323 frequency 14 Fresnel reflection factors 29-30 f-stop 170
gamma radiation techn. 363-364 geographic information systems 360 geological structures 206-207 granite 58 granularity 127 grey tone analysis 218-219 ground penetrating radar 332-334 ground resolution 141-142 gypsum 57
236-239
Hasselblad camera 170 HCMM 290-291 histogram equalisation 133 hot spot 83, 161 hypersthene 56
image contrast 143-144 - features pattern 146 - structure 144-146 - texture 144-146
- quality 143 - restoration 131, 152-153 index of refraction 25 inferred aspects interpr. 182 Infrared bands 368 - imagers 289 - photography 176-177, 235 - radiometer 306-307 - scanners 289 - techniques history 288
instantaneous field of view 142 interactive processing 132-135 Intercosmos programme 115 interference 13 - filters 100 internal reflectance 32 interpretation flow chart 183-185 ionic crystals 21 iris (eye) 94 IRLS application 305-306 isotropic crystals 22
kaolinite 56-57 Kenia interpr. 213, 215-218 kettle-hole drain. p. 197-198 Kirchhoff's law 16 Kodak-Path6 masking 153
Lambert's cosine law 33 Lambert's law 25 land complexity 228-229
Landsat imagery 148, 149, 272 - MSS 259-260 - notations 263-266 - RBV 259, 262 - status 263 land surface 361-362 landtype 186-189 land use 203-204 large scale 7 Laser 314-315 legal considerations 368-369 limburgite 58 limestone 57 limonite 57 line scanners 246-248 luminiscence 37
Mapsat 363 medium scale 7 metals 2 1 Meteosat 290 Meteor 366 Metric camera 364 Microwaves (passive) 307-308 - MRSE 364
mid Infrared 253 Mie scattering 41-42 mirror effect 22 MKF (Sojus-22) 115
evaluation 226-227, 358-359
378
models 360-361 modulation transfer function 126-127 montmorillonite 57 morphogenetic analysis 1 8 3 MOS-1 366 MSS channels 247-248, 250 multispectral photography 177-178,
muscovite 56 2 39- 2 40
nadir-point 162 Negev 305 net-radiation 46-48
pyroxenes 5 6
Quantimet 137-138 quantum-type detectors 111 quartz 5 5 , 5 8 Quercus alba 78-80
radar anal. drain. p. 339-340 - applications 348-349 - bands 3 1 5 - equation 321-322 - flagpole effect 335
Nimbus meteorological sat. progr. 257, - image characteristics 335-339
NQAA 290 - parallax 337, 3 3 9 non-selective scattering 41-42 - polarization 321 normal angle camera 167-168 - resolution 318-320
290 - image interpr. 339-346
- shadow 335-336 - vegetation backscatter 334-335
oblique airphotos 155-156 opacity 125 opaque bodies 37 Radarsat 367 organic matter content 251-252 radial drain. p. 197-198 orthophotographs 172 radians 142
radiometer 111 radiometric temperature 39, 289 ra d i ophas e s y s t ems 347 - 3 4 8 panoramic camera 170-171
parallax 165-166 radiowaves frequency 1 5 , 347 parcelling 203, 205 ratio's 135-136, 266 , 275 parent material interpr. 207 Rayleigh's criterion for roughness 34 pedon 4 Rayleigh scattering 41-42 penetration depth 326 rectangular drain. p. 198-199 permanent dipole 21 reference objects 121 photographic film 104-105 reflectance (spectral) 48 photobase 158-159 - field measurements 119-121 photomosaics 172 refraction 28 physiographic analysis 18 3 relative turgidity (plants) 84-86 Planck's constant 14 relief classes 1 9 0
plant leaf structure 76
polarization 13-14, 22-23, 28, 68-69, - scheme 116
Planck's law 17-18 - displacement 164-165
plastid pigment 76 - courses 370-37 1
- filters 100, 102 resolving power (eye) 97
remote sensing centres 369-370
81-83, 321 resolution (film) 129, 141
political considerations 368-369 (film) 127 polypedon 4 reststrahlen bands 5 8 power absorption coefficient 325 retina (eye) 94 - scattering coefficient 325 retinex theory 9 5 principal component transform 134-135, return parameter
276-278 rods (eye) 94-95 pinnate drain. p. 198-199
-
379
r o t a t i o n a l e n e r g y s t a t e 20
S a l y u t 366 sample areas 224-225 S A R 321 scale of maps 7
s c a n n e r imagery d i s t o r t i o n s 148-149 s e q u e n t i a l p h o t o g r a p h y 240-241 s h o r e l i n e t y p e s 193-194 S h u t t l e Imaging Radar 363 s i l i c a t e s 58 S i n a i 305 S k y l a b 257-258, 290 S k i n d e p t h 26 , 327 SLAR 316-317 small sca le 7 SMIRR 257 S n e l l ' s l a w 2 9 , 3 1 S o i l c o m p a c t i o n 304 - c o n c e p t 4 - c r u s t i n g 251 - d e p t h i n t e r p r . 208 - map 5 - m o i s t u r e 61-62, 251 , 329-332,
- r o u g h n e s s 64-65 - s t r u c t u r e 63-64 - s u r f a c e 206 - s u r v e y s 230 - s u r v e y p l a n n i n g 233-234
- a i r p h o t o s 141
36 3- 36 4
- p r o g r e s s 232 - r e p o r t 234-235 - t e m p e r a t u r e 74-75 - t e x t u r e 62-63 - v a r i a b i l i t y 225-226 S o l a r i r r a d i a n c e 18-19 - r e f l e c t i o n p o i n t 161 s p a c e h o r n e p l a t f o r m s 113-115 S p a c e l a b 257 s p e c i f i c h e a t 3 9 , 72 s p e c t r a l f e a t u r e s I n f r a r e d 51 - f i l t e r s 100
s p e c u l a r r e f l e c t i o n 27-28 SPOT-1 209, 365 S t e f a n - R o l t z m a n n ' s l a w 16 s t e r e o p s i s 97 S t e r e o s a t 3 6 3 s t e r e o s c o p e s 162-164 s t e r e o t r i p l e t s 172-173 s t r e a m f o r m s 192-193
- s e n s i t i v i t y I R f i l m 108
stream o r d e r s 195-196 s t r i p camera 170 s u p e r v i s e d c l a s s i f i c a t i o n 137 s u p e r w i d e a n g l e camera 167-168 s u r f a c e r o u g h n e s s 323-324 Suriname i n t e r p r . 212-215 swal low-hole d r a i n . p. 197-198
T e l l - u s model 299-303 T e r g r a model 298, 301 termite mounds 207 TERS 366 t e s t s i tes 117 T h e m a t i c Mapper 261-262, 281-284, 291 The N e t h e r l a n d s 304 , 342-246 t h e r m a l c a p a c i t y 39
- d e t e c t o r s 110 - c o n d u c t i v i t y 3 9 , 72-73
- d i f f u s i v i t y 39-40, 72 - i n e r t i a 40 , 59-60, 300, 302-303 - i n f r a r e d imagery 291-296 - models 297-300 t h e r m o k a r s t d r a i n . p. 194-195 119 t h e r m i s t o r 119 t i l t 157, 161 t r a f f i c a b i l i t y 229 t r a n s m i t t a n c e 3 8 , 125 t r e l l i s d r a i n . p. 198-199 t r e m o l i t e 56 t r i m e t r o g o n camera 170 t r u e c o l o u r p h o t o g r a p h y 105-106, 174-
T u n i s i a 281-284 176, 235
U l t r a v i o l e t 1 0 9 , 178, 248 u n s u p e r v i s e d c l a s s i f i c a t i o n 1 0 9 , 178 ,
248
v a l e n c e c r y s t a l s 21 van d e r Waals c r y s t a l s 21 v e g e t a t i o n c o v e r 201-202, 331-332 v e r t i c a l a i r p h o t o s 155
v i b r a t i o n a l e n e r g y s t a t e 20 V i d i c o n 111 v i s i b l e r a d i a t i o n 16
- e x a g g e r a t i o n 166-1 6 8
wide a n g l e camera 167-168 I J i e n ' s d i s p l a c e m e n t l a w 17
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