12.ijaest vol no 7 issue no 1 comparison of different topographic correction methods using awifs...

8/6/2019 12.IJAEST Vol No 7 Issue No 1 Comparison of Different Topographic Correction Methods Using AWiFS Satellite Data

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Comparison of Different Topographic Correction

Methods using AWiFS Satellite Data

Sartajvir Singh1

1M-Tech Student, E.C.E Deptt.

R.I.E.I.T, Railmajra,

S.B.S. Nagar, Punjab, India

[email protected]

Prof. J.K. Sharma2

2Director, Engineering Deptt.

R.I.E.I.T, RailmajraS.B.S. Nagar, Punjab, India

[email protected]

Dr. V.D. Mishra3

3Scientist (E), R.S. Research Group

SASE, DRDO

Chandigarh, [email protected]

Abstract: - In general, the topographic effect is particularlyevident for steep sloped Himalaya terrain because irregular

shape of Himalaya causes variable illumination angles and

thus diverse reflection values within one land cover type as

low reflectance value in shadow areas and high reflectance

value in sun illuminated areas. Therefore, effective removal

or minimization of topographic effects is necessary in satellite

image data of mountainous regions. Topographic correction

methods try to compensate topographically induced

illumination variations effect. In this paper, differenttopographic correction methods such as cosine, C-correction,

smooth C-correction, cosine-C, SCS+C, C-Huang Wei, slope

matching techniques have analyzed using AWiFS satellite

imagery of Himalaya. The performance of different models is

evaluated using (1) visual analysis and (2) validation with in

situ observations of spectral reflectance. The objectives of this

study are to assess the effectiveness of different topographic

corrections on snow cover area of Himalaya terrain. The

result shows that slope matching is superb technique as

compared to the other topographic correction methods to

compensate the effects of variable illumination angles.

Keywords: - Topographic correction, Cosine-C, SCS+, Smooth

correction, Slope match.

I. INTRODUCTIONThe operational use of remote sensing techniques is often

obstructed by problems originating from topographic effects

on the sensor response. The topographic effect of satellite

imagery generally refers to the influence from the apparent

intensity of surface reflectivity, which is caused by the solar

incidence, terrain slope and viewing angle. Such influences

may be augmented when the terrain slope is steeper, especially

for mountainous terrains. Due to atmospheric scattering, the

sun elevation is also of importance. A surface perpendicular to

the sun at a low sun elevation will receive less radiation than asurface perpendicular to the sun at a high solar elevation [1].

In other words, sun-facing illuminated slopes (south aspect)

show more reflectance value, whereas the effect is opposite in

shaded area (north aspect) show less reflectance value [2].

Differential illumination results in considerable variation in

the spectral characteristics of similar snow and other land

covers. Therefore, different topographic correction methods

were developed to eliminate or at least reduce the topographic

influence.

A number of methods have been developed to correct the

effect of topographic variation on satellite images, mainly

divided into three main categories (1) Empirical approches

such as two stage normalization [3] etc. (2) Lambertains

methods such as cosine [3]-[5], cosine-T [4], C-correction[4], cosine-C [3], smooth C [2], SCS+ [6] etc. (3) Non-

lambertain methods such as Minnaret [7] etc. It was

concluded [8] that physically based cosine correction and SCS

correction would overcorrect the shaded area in an image

whereas the correction methods involving experimental

parameters such as the C, SCS+C correction perform better

and these empherical algorithms have been applied more

widely in practice. However it was found that these well

develop algorithms are problematic in operation, and some of

them cannot perform well enough in some situation [2], [6]. It

is reported [9] that slope matching technique superb

topographic correction technique in snow cover area of

western Himalaya, which was compared with cosine, C-correction, Minneart correction and two stage normalization

correction methods. Other topographic correction methods in

optical satellite imagery are not investigated very extensively

in the Himalayan terrain.

The purpose of this paper was to compare the different

topographic method such as cosine, C-correction, slope

matching, smooth C-correction, cosine-C, SCS+C, C-Huang

Wei on snow cover area of Himalaya terrain for topographic

effects. The results obtained using different topographic

methods are compared with the in-situ observations of spectral

reflectance. Results suggest that Slope matching is true

quantitative retrieval of spectral reflectance, especially inshady area on our study area where as other topographic

correction methods overestimate or underestimate the

parameters.

Sartajvir Singh* et al. / (IJAEST) INTERNATIONAL JOURNAL OF ADVANCED ENGINEERING SCIENCES AND TECHNOLOGIESVol No. 7, Issue No. 1, 085 - 091

ISSN: 2230-7818 @ 2011 http://www.ijaest.iserp.org. All rights Reserved. Page 85
mailto:[email protected]:[email protected]:[email protected]:[email protected]


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II. STUDY AREAThe study area is a part of Lower and Middle Himalaya

and shown on AWiFS image (Advance Wide Field Sensor)

lies between latitude of 32.254 degree to 32.999 degree North

and longitude of 77.00 degree to 77.497 degree East with

Azimuth angle 155.69 degree, and Elevation angle 43.79

degree as shown in the Figure 1. The lower part of the area is

surrounded by forest and tree line exists up to 3100 m. Theupper part (Middle Himalaya) is devoid of forest. The average

minimum temperature in winter is generally observed to be -

12oC to -15oC in lower Himalaya (Pir-Panjal range) and -30oC

to -35oC in Middle Himalaya (Greater Himalaya range). Pir-

Panjal receives the highest snowfall (average 15-20 m) as

compared to Greater Himalayan range (12-15m) during the

winter period between October and May. The altitude in the

entire study area varies from 1900 m to 6500 m with a mean

value of 4700 m. The slope in the study area varies from 1-86

degree with mean value of 28 degree and aspect ranges from

0-360 degree with mean values of 180 degree. Most of the

slopes in the study regions are oriented to south aspect.

III. SATELLITE DATASETSA cloud free satellite images of AWiFS of 08 th January

2009 is used in the present work to study influence of different

topographic correction methods. The salient specifications of

AWiFS sensor are given in the Table 1.

IV. DIGITAL ELEVATION MODEL GENERATION ANDGEOMETRIC CORRECTION

A master scene of 56m spatial resolution of AWiFS

(Advance Wide field sensor) of study area is prepared after

rectification with high spatial resolution 23m of LISS-III

(Linear Imaging self-Scanning) with 1:50,000 toposheet. Asatellite image of AWiFS was than geo-coded with AWiFS to

the EVEREST datum by ERDAS/Imagine 9.1 (Leica

Geosystems GIS and Mapping LLC) software with sub pixel

accuracy. From the DEM dataset, information about the slope,

aspect and illumination according to the sun angle and

elevation were generated for input to the topographic

corrections algorithms. The Pre-processing and Topographic

correction steps Shown in Fig.2.

Figure 1 AWiFS image of study area (08 th January 2009)

Figure 2 Flow chart of Pre-processing and Topographic correction.

Table 2 Salient Specifications of AWiFS Sensor

Spectral

bands

Spectral

wavelength(nm)

Spatial

Resolution(m)

Quantization

(bit)

Maximum

Radiance(mw/cm2/sr/m)

Solar Exoatmostpheric

spectral Irradiance(mw/cm2/sr/m)

B2 520-590 56 10 52.34 185.3281

B3 620-680 56 10 40.75 158.042

B4 770-860 56 10 28.425 108.357

B5 1550-1700 56 10 4.645 23.786

AWiFS Image

Geo-referencing

Atmospheric Corrections

DEM

Slope, Aspect

Illumination Angle

Estimation of Reflectance Estimation of coefficients

Apply Different Topographically Corrections method

Different Topographically Corrected Reflectance




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V. TOPOGRAPHIC UNCORRECTED REFLECTANCE IMAGEGENERATION

Without topographic consideration, the atmospherically

corrected surface spectral reflectance under lambertian

assumption for AWiFS is computed using the following

equation [10, 11]:

( )

(1)

Where is the exo-atmospheric spectral irradiance (referTable1), is the solar zenith angle and calculated for eachpixel [12], d is the earth sun distance in astronomical units

and calculated using the approach of [13], is thedownwelling diffused radiation and assumed zero according to

[14]. is the path radiance which has computed using[14,15].

VI. TOPOGRAPHIC CORRECTION In this study, different topographic correction methods

were analyzed. The methods are the cosine, C-correction,smooth C-correction, cosine-C, SCS+C, C-Huang Wei, slope

matching correction techniques as explained in following

sections

A. Cosine correctionIn this method, the surface is assumed to have Lambertian

behavior, i.e. to be a perfect diffuse reflector, having the same

amount of reflectance in all view directions. Under the

assumption of Lambertian surfaces, the cosine correction [16],

[4] has been extensively used to correct for illumination

variations [2], [17].

= (2)

Where is spectral reflectance for horizontal surface, is spectral reflectance observed over the inclined terrain, issolar zenith angle and is illumination (IL) which iscalculated using (2), proposed by [3], [18], [2].

(3)Where is the slope of the surface, aspects of the surfaceand is the solar azimuth angle.

Although the Lambertian assumption is simple and

convenient for topographic correction, there is a recognised

problem in the corrected images. Thus when correcting the

topographic effect under a Lambertian surface assumption,

images tended to be over-corrected, with slopes facing away

from the sun appearing brighter than sun-facing slopes due to

diffuse sunlight being relatively more influential on the shady

slope.

B. Cosine-C correctionDue to the problem of overcorrection in cosine correction

an improved version has been proposed by [3], which

considers the average IL conditions.

= * + (4

Where is mean of illumination of study area.

These models are wavelength independent, since the

correction is based on the same factor for all the bands. This

assumption is not appropriate as far as diffuse irradiance

concerns. Therefore, it should be more appropriate to propose

band-dependent factors of topographic correction as pe

reported in [2].

C. C-correctionTeillet [4] proposed the addition of a semi-empirica

moderator (C) to the cosine correction. In this method, C is

introduced to the cosine correction model as an additive term

in (2). C-correction is calculated using (5).

= (5

Based on an examination of image data, a linear relationship

exists between and in the form (6), called regressionequation.

(6The parameters C are a function of the regression slope (m)

and intercept (b)

(7

The parameter C is said to be analogous to the effects o

diffuse sky irradiance, although the analogy is not exact. The

C value, which may also be obtained from the slope and

intercept of the regression line from the statistical-empirical

approach, exerts a moderating influence on the cosine

correction by increasing the denominator and reducing theovercorrection of faintly illuminated pixels. The C-correction

method has been shown to retain the spectral characteristics of

the data and improve overall classification accuracy in areas of

rugged terrain, and it can be derived easily [2], [17].




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D. Smooth C-correctionIt is reported [2] that best results can be obtained with a

variation of the C method, which takes into account the

overcorrection of low illuminated slopes by the original C

method. Smooth C is a variation of C-correction method based

on a smoothed IL value. Most methods produce an

overcorrection in those pixels where IL is low. Therefore, a

variation in the calculation of the IL was carried out, bysmoothing the original slope with a smoothing factor of 3, 5,

and 7. Previously slope is calculated using (8),

= arc (8)

This is transformed into (9)

= arc (9)

Where X=3, 5, 7 is a smooth factor. After obtained the slope

of corresponding factor, put it in (5) to calculate smooth C-

correction. A smoothed correction does not alter reflectancevalues significantly, whereas a more extreme correction could

introduce additional errors.

E. SCS+C : A Modified Sun-Canopy-SensorTopographic Correction

The SCS correction [19] improves on the cosine

correction by normalizing the illuminated canopy area. It is

reported [6] that SCS correction is equivalent to projecting the

sunlit canopy from the sloped surface to the horizontal, in the

direction of illumination. The cause of the overcorrection in

the SCS model is similar to that with the cosine correction. As

the angle of incidence approaches 90 degree, the correction

factor becomes excessively large. In the C-correction, the

parameter C has been shown to have a moderating influence

on the cosine correction by emulating the effect of diffuse sky

illumination [4], [17]. Soenen [6] proposed the SCS+C

correction where the moderator C is derived using (6) and (7)

but within the improved physical context of the SCS model.

This addition is intended to be an improvement to the SCS

correction in a similar way as the C-correction improves on

the cosine correction. The formulation for this new SCS+C

correction is defined by (10)

= (10)

Where is terrain slope [19] and all other parameter areconsidered as in [section 2(C)].

F. C-Huang WeiIt is reported [8] that C-Huang Wei method is used for

topographic correction under Lambertain methods developed

by Huang Wei. It can be calculated using (11).

= ( ) + (11

Where minimum value of spectral reflectance, isa minimum value of illumination.

G. Slope match Nichol and others [20] was proposed slope-matchin

method who introduced certain modifications to Civcos

(1989) model and considered the topographic corrections in

two stages because they observed that Civcos [3] not provide

the well results in shadow areas as per reported in [9]. Thefinal reflectance for topographic correction is estimated using

(12) proposed by Nichol and others [20].

(12)

Where is topographically corrected spectral reflectance, is spectral reflectance on the tilted surface, and ismaximum and minimum spectral reflectance and estimated

from topographically uncorrected reflectance image is mean value of illumination on the southaspect. is normalization coefficient for different satellite bands and estimated using equation given in the literatur

[20].

(13

Where is the mean reflectance value on sunlit slopes afterfirst stage normalization, is the mean reflectance value onshady slopes in uncorrected image and is the meanreflectance value on shady slope after first stage

normalization. All parameter required to calculate coefficient

is shown in Table 2.The advantage of this method is that reflectance values in

the corrected image are normalized to the mean illumination

level of pixels on the sunny aspect rather than the overall

mean illumination value of the entire image [20]. The slope-

matching method adjusts the brightness between northern andsouthern slopes. As such, its parameters depend on the image

itself as reported in [21].




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TABLE 2PARAMETERS FORCALCULATION OF (COEFFICIENT) FOR SLOPE MATCHINGSpectral Reflectances in AWiFS bands

Parameters Band 2: 520590 (nm) Band 3: 620680 (nm) Band 4: 770860 (nm) Band 5: 15501700 (nm

South Aspect (after 1stnormalization) 0.824 0.810 0.814 0.139

North Aspect (after 1stnormalization) 0.866 0.847 0.830 0.235

North Aspect 0.461 0.442 0.425 0.068

VII. RESULTS AND DISCUSSIONA. Estimation of Coefficient for Topographic Correction

methods

The coefficients for different topographic correction

method (C-correction, smooth C with factor 3, smooth C with

factor 5, Smooth C with factor 7 and slope match) have shown

in Table 3.

B. Model ValidationThe results obtained using different topographic models

are compared with the in-situ observations of spectral

reflectance recorded at the time of satellite pass at Indian

standard time (1130 IST) on 08th January 2009 for mode

validation. The pixel location of AWiFS imagery of 08 th

January 2009 was latitude (32.358791o) and longitude

(74.119792o). The comparative analysis of different

topographic results with in-situ observations in Table 4 shows

that some of topographic correction methods overestimate and

some of topographic correction methods underestimate but

only slope matching method is unique among all the methods

and is more suitable for snow cover area of Himalayan terrain

In literature [9], Slope match method performed superb as

compare to cosine, C-correction, two stage normalization and

Minneart.All topographic correction methods output images have

shown in Fig. 3.

TABLE 3COEFFICIENTS FORDIFFERENT TOPOGRAPHICNORMALIZATION MODELS.

Coefficients for AWiFS imagery of 08th January 2009

C-correction/SCS+C Smooth C (with factor 3) Smooth C (with factor 5) Smooth C (with factor 7) Slope match

16.84 5.990 3.475 2.350 0.8962

15.94 5.679 3.267 2.206 0.9086

15.25 5.396 3.098 2.083 0.9604

16.66 5.529 3.142 2.10 0.4251

TABLE 4VALIDATIONS OF TOPOGRAPHICNORMALIZATION MODELS WITH FIELD RESULTS OF SPECTRAL REFLECTANCE USING

SPECTRORADIOMETER.

AWiFS Date: 08 th January 2009, pixel location: latitude (32.358791o) and longitude (74.119792o).

Spectral reflectances in AWiFS bands

Topographic Model Band 2: 520590 (nm) Band 3: 620680 (nm) Band 4: 770860 (nm) Band 5: 15501700 (nm)

Cosine-C 0.896 0.895 0.909 0.142

C-correction 0.979 0.978 0.977 0.150

Smooth C (with factor 3) 0.978 0.982 0.976 0.149



SCS+C 0.979 0.956 0.979 0.149

C-Huang Wei 0.685 0.661 0.663 0.109

Slope match 0.929 0.928 0.923 0.139

Field observation 0.928 0.912 0.909 0.149




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Figure 3 Topographic corrected image (a) cosine, (b) cosine-C, (c) C-correction, (d) smooth C with factor 3, (e) smooth C with factor

5, (f) Smooth C with factor 7, (g) SCS+C, (h) C- Huang Wei, (i) slope match.

(a) (b)

(e)

(c)

(f)(d)

(g) (h) (i)




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VIII. CONCLUSIONIn this paper, we have compared different topographic

correction methods and concluded that all C methods do not

provide well results as compare to slope matching in snow

cover area of Himalaya terrain. We observed that slope

matching method has advantages in the true quantitative

retrieval of spectral reflectance, especially in shady area,

compared to C-correction, cosine, cosine-C, smooth C,SCS+C and C-Huang Wei topographic correction methods.

Topographic corrections are very useful for further

applications as snow cover monitoring, change detection

analysis, etc. Further research is needed with imagery on a

global basis to derive guidelines on which method performs

best under which situation.

ACKNOWLEDGEMENT

The authors would like to thank Director, Snow Avalanche

Study establishment, Department of Defence Research and

Development Organization.

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