Digital Airborne Camera

Digital Airborne Camera

Introduction and Technology

Edited by

Rainer SandauDLR, Berlin, Germany

With contributions by Ulrich Beisl, Bernhard Braunecker, Michael Cramer,Hans Driescher, Andreas Eckardt, Peter Fricker, Michael Gruber, Stefan Hilbert,Karsten Jacobsen, Walfried Jagschitz, Herbert Jahn, Werner Kirchhofer, FranzLeberl, Klaus J. Neumann, Rainer Sandau, Maria von Schönermark, and UdoTempelmann

123

EditorDr. Rainer SandauDeutsches Zentrum forLuft- und Raumfahrt e.V.(DLR)Rutherfordstr. 212489 BerlinGermanyrainer.sandau@dlr.de

This is a translation of the book in German “Digitale Luftbildkamera − Einführung und Grundlagen”,by Rainer Sandau, published by Wichmann Verlag, 2005; including some new additions in chapter 7(Examples)

ISBN 978-1-4020-8877-3 e-ISBN 978-1-4020-8878-0DOI 10.1007/978-1-4020-8878-0Springer Dordrecht Heidelberg London New York

Library of Congress Control Number: 2009940584

© Springer Science+Business Media B.V. 2010No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or byany means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without writtenpermission from the Publisher, with the exception of any material supplied specifically for the purposeof being entered and executed on a computer system, for exclusive use by the purchaser of the work.

Cover illustration: Transparent view of the ADS40 camera made by Leica Geosystems AG.

Printed on acid-free paper

Springer is part of Springer Science+Business Media (www.springer.com)

Preface

Digital airborne cameras are now penetrating the market of photogrammetry andremote sensing. Owing to rapid progress in the last 10 years in fields such as detec-tor technology, computer power, memory capacity, and measurement of positionand orientation, it is now possible to acquire, with the new generation of digitalairborne cameras, different sets of geometric and spectral data with high resolutionwithin a single flight. This is a decisive advantage over aerial film cameras. Thelinear characteristic of the optoelectronic converters is at the root of this transfor-mation from an imaging camera to a measuring instrument that captures images.The direct digital processing chain from the airborne camera to the derived prod-ucts involves no chemical film development or digitisation in a photogrammetricfilm scanner. Causes of failure, expensive investments and prohibitive staff costs areavoided. The effective use of this new technology, however, requires knowledge ofthe characteristics, possibilities and restrictions of the formation of images and thegeneration of information from them.

This book describes all the components of a digital airborne camera, from theobject to be imaged to the mass memory device on which the imagery is written inthe air. Thus natural processes influencing image quality are considered, such as thereflection of the electromagnetic energy from the sun by the object being imagedand the influence of the atmosphere. The essential features and related parame-ters of the new technology are discussed and placed in a system framework. Thecomplex interdependencies between the components, for example, optics, filters,detectors, analogue and digital electronics, and software, become apparent. Thebook describes several systems available on the market at the time of writing.

The book will appeal to all who want to be informed about the technology ofthe new generation of digital airborne cameras. Groups of potential readers include:managers who have to decide about investment in and use of the new cameras;camera operators whose knowledge of the features of the cameras is essential tothe quality of the data acquired; users of derived products who want to order oreffectively process the new digital data sets; and scientists and university students,in photogrammetry, remote sensing, geodesy, cartography, geospatial and environ-mental sciences, forestry, agriculture, urban planning, land use monitoring and otherfields, who need to prepare for the use of the new cameras and their imagery.

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vi Preface

This book is a translation of the publication in German, DigitaleLuftbildkamera − Einführung und Grundlagen, published in 2005 by HerbertWichmann Verlag in Heidelberg. Only Chapter 7 was extended to three examplecamera systems which are being marketed worldwide and are also roughly represen-tative of the bandwidth of the implementation variations. I would like to acknowl-edge Wichmann Verlag’s gracious agreement to transfer the English-language rightsto Springer.

I would like also to acknowledge the help that the contributors to this bookreceived from a number of individuals:

Ms. Ute Dombrowski (DLR, Berlin, Germany), who was very supportive in typ-ing large parts of the manuscript, dealing with figures and tables, editing the chaptersof the various authors, and combining the results into a book.

Dr. A. Stewart Walker (BAE Systems, San Diego, USA), who proof-read theentire manuscript in order to polish and homogenise the usage of the Englishlanguage in the translation from German carried out by the authors.

Dipl.-Ing. Dieter Zeuner (formerly Applanix, Toronto, Canada), who contributedto the translation of the German version.

Prof. Dr.-Ing. Hans-Peter Röser (Unversität Stuttgart, Institut fürPhotogrammetrie, Germany; formerly DLR, Berlin, Germany), who led theDLR team during the joint development of the ADS40 with Leica and LH Systems.

Ms. Petra van Steenbergen of the publisher, who supported the creation of thebook through pleasant, patient collaboration.

Berlin, Germany Rainer SandauApril 2009

Contents

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 From Analogue to Digital Airborne Cameras . . . . . . . . . . 11.2 Applications for Digital Airborne Cameras

in Photogrammetry and Remote Sensing . . . . . . . . . . . . . 81.3 Aircraft Camera or Satellite Camera . . . . . . . . . . . . . . . 13

1.3.1 Detection, Recognition, Identification . . . . . . . . . 161.4 Matrix Concept or Line Concept . . . . . . . . . . . . . . . . . 201.5 Selection of Commercial Digital Airborne Cameras . . . . . . . 27

1.5.1 ADS80 . . . . . . . . . . . . . . . . . . . . . . . . . . 271.5.2 DMC . . . . . . . . . . . . . . . . . . . . . . . . . . 291.5.3 UltraCam . . . . . . . . . . . . . . . . . . . . . . . . 29

2 Foundations and Definitions . . . . . . . . . . . . . . . . . . . . . . 312.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 312.2 Basic Properties of Light . . . . . . . . . . . . . . . . . . . . . 342.3 Fourier Transforms . . . . . . . . . . . . . . . . . . . . . . . . 412.4 Linear Systems . . . . . . . . . . . . . . . . . . . . . . . . . . 562.5 Sampling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 692.6 Radiometric Resolution and Noise . . . . . . . . . . . . . . . . 782.7 Colour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 892.8 Time Resolution and Related Properties . . . . . . . . . . . . . 952.9 Comparison of Film and CCD . . . . . . . . . . . . . . . . . . 99

2.9.1 Comparison of the Imaging Process and theCharacteristic Curve . . . . . . . . . . . . . . . . . . . 99

2.9.2 Sensitivity . . . . . . . . . . . . . . . . . . . . . . . . 1012.9.3 Noise . . . . . . . . . . . . . . . . . . . . . . . . . . 1022.9.4 Signal to Noise Ratio (SNR) . . . . . . . . . . . . . . 1022.9.5 Dynamic Range . . . . . . . . . . . . . . . . . . . . . 1032.9.6 MTF . . . . . . . . . . . . . . . . . . . . . . . . . . . 1042.9.7 MTF · Snr . . . . . . . . . . . . . . . . . . . . . . . . 1042.9.8 Stability of Calibration . . . . . . . . . . . . . . . . . 1052.9.9 Spectral Range . . . . . . . . . . . . . . . . . . . . . 1062.9.10 Summary . . . . . . . . . . . . . . . . . . . . . . . . 107

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viii Contents

2.10 Sensor Orientation . . . . . . . . . . . . . . . . . . . . . . . . 1072.10.1 Georeferencing of Sensor Data . . . . . . . . . . . . . 1072.10.2 Brief Review of GVP Concepts GPS . . . . . . . . . . 1162.10.3 Basics of Inertial Navigation . . . . . . . . . . . . . . 1212.10.4 Concepts of Inertial/GPS Integration . . . . . . . . . . 128

3 The Imaged Object and the Atmosphere . . . . . . . . . . . . . . . 1313.1 Radiation in Front of the Sensor . . . . . . . . . . . . . . . . . 1313.2 Radiation at the Sensor . . . . . . . . . . . . . . . . . . . . . . 1343.3 Contrast of a Scene at the Sensor . . . . . . . . . . . . . . . . . 1373.4 Bi-directional Reflectance Distribution Function BRDF . . . . . 138

4 Structure of a Digital Airborne Camera . . . . . . . . . . . . . . . 1434.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143

4.1.1 Example . . . . . . . . . . . . . . . . . . . . . . . . . 1494.2 Optics and Mechanics . . . . . . . . . . . . . . . . . . . . . . 151

4.2.1 Effect of Geometry . . . . . . . . . . . . . . . . . . . 1514.2.2 The Effect of the Wave Nature of Light . . . . . . . . . 1534.2.3 Space-Bandwidth Product . . . . . . . . . . . . . . . . 1534.2.4 Principal Rays . . . . . . . . . . . . . . . . . . . . . . 1544.2.5 Physical Imaging Model . . . . . . . . . . . . . . . . 1544.2.6 Data Transfer Rate of High Performance

Optical System . . . . . . . . . . . . . . . . . . . . . 1554.2.7 Camera Constant and “Pinhole” Model . . . . . . . . . 1564.2.8 Pupil Characteristics . . . . . . . . . . . . . . . . . . 1574.2.9 Design and Manufacturing Aspects . . . . . . . . . . . 1594.2.10 Summary of the Geometric Properties of an Image . . . 1604.2.11 Aberrations and Precision of Registration . . . . . . . 1694.2.12 Radiometric Characteristics . . . . . . . . . . . . . . . 1714.2.13 Ideal Optical Transfer Function . . . . . . . . . . . . . 1724.2.14 Real Optical Transfer Function . . . . . . . . . . . . . 1754.2.15 Field Dependency of the Optical Transfer Function . . 177

4.3 Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1804.3.1 Absorption Filters . . . . . . . . . . . . . . . . . . . . 1804.3.2 Interference Filters . . . . . . . . . . . . . . . . . . . 183

4.4 Opto-Electronic Converters . . . . . . . . . . . . . . . . . . . 1834.4.1 Operating Principle . . . . . . . . . . . . . . . . . . . 1844.4.2 CCD Architectures . . . . . . . . . . . . . . . . . . . 1884.4.3 Properties and Parameters . . . . . . . . . . . . . . . . 196

4.5 Focal Plane Module . . . . . . . . . . . . . . . . . . . . . . . 2104.5.1 Basic Structure of a Focal Plane Module . . . . . . . . 210

4.6 Up-Front Electronic Components . . . . . . . . . . . . . . . . 2124.6.1 CCD Control . . . . . . . . . . . . . . . . . . . . . . 2134.6.2 Signal Pre-Processing . . . . . . . . . . . . . . . . . . 2154.6.3 Analogue-Digital Conversion . . . . . . . . . . . . . . 217

4.7 Digital Computer . . . . . . . . . . . . . . . . . . . . . . . . . 221

Contents ix

4.7.1 The Control Computer . . . . . . . . . . . . . . . . . 2214.7.2 Data Compression . . . . . . . . . . . . . . . . . . . . 2274.7.3 Data Memory/Data Storage . . . . . . . . . . . . . . . 231

4.8 Flight Management System . . . . . . . . . . . . . . . . . . . 2324.8.1 Flight Planning . . . . . . . . . . . . . . . . . . . . . 2334.8.2 Flight Evaluation . . . . . . . . . . . . . . . . . . . . 2344.8.3 Flight Execution . . . . . . . . . . . . . . . . . . . . . 2344.8.4 Operator and Pilot Interface . . . . . . . . . . . . . . . 2364.8.5 Operator Concept . . . . . . . . . . . . . . . . . . . . 237

4.9 System for Measurement of Position and Attitude . . . . . . . . 2384.9.1 GPS/IMU System in Operational Use . . . . . . . . . 2384.9.2 Integration of GPS/IMU Systems with Imaging Sensors 245

4.10 Camera Mount . . . . . . . . . . . . . . . . . . . . . . . . . . 2504.10.1 Rigid Mount . . . . . . . . . . . . . . . . . . . . . . . 2504.10.2 Frequency Spectrum in Aircraft and MTF . . . . . . . 2504.10.3 Uncontrolled Camera Mount . . . . . . . . . . . . . . 2574.10.4 Controlled Camera Mount . . . . . . . . . . . . . . . 258

5 Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2615.1 Geometric Calibration . . . . . . . . . . . . . . . . . . . . . . 2615.2 Determination of Image Quality . . . . . . . . . . . . . . . . . 2675.3 Radiometric Calibration . . . . . . . . . . . . . . . . . . . . . 268

6 Data Processing and Archiving . . . . . . . . . . . . . . . . . . . . 273

7 Examples of Large-Scale Digital Airborne Cameras . . . . . . . . . 2797.1 The ADS40 System: A Multiple-Line Sensor

for Photogrammetry and Remote Sensing . . . . . . . . . . . . 2797.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 2797.1.2 The Digital Control Unit . . . . . . . . . . . . . . . . 2867.1.3 Sensor Management . . . . . . . . . . . . . . . . . . . 2907.1.4 The Flight Planning and Navigation Software . . . . . 2927.1.5 The Position and Attitude Measurement System . . . . 2937.1.6 The Gyro Stabilized Mount for the ADS40 . . . . . . . 2947.1.7 The Radiometric und Geometric Calibration . . . . . . 2957.1.8 Data Processing . . . . . . . . . . . . . . . . . . . . . 2977.1.9 Images Acquired with the ADS40 . . . . . . . . . . . 299

7.2 Intergraph DMC Digital Mapping Camera . . . . . . . . . . . . 3077.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 3077.2.2 Lens Cone – Basic Design of the DMC . . . . . . . . . 3087.2.3 Innovative Shutter Technology . . . . . . . . . . . . . 3097.2.4 CCD Sensor and Forward Motion

Compensation . . . . . . . . . . . . . . . . . . . . . 3097.2.5 DMC Radiometric Resolution . . . . . . . . . . . . . 3117.2.6 DMC Airborne System Configuration . . . . . . . . . 3117.2.7 System Calibration and Photogrammetric Accuracy . . 312

x Contents

7.3 UltraCam, Digital Large Format Aerial Frame Camera System . 3137.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . 3137.3.2 UltraCamX Produces the Largest Format

Digital Frame Images . . . . . . . . . . . . . . . . . . 3147.3.3 UltraCam Design Concept . . . . . . . . . . . . . . . 3177.3.4 Geometric Calibration . . . . . . . . . . . . . . . . . . 3207.3.5 Geometric Accuracy at the 1 μm Level . . . . . . . . . 3237.3.6 Radiometric Quality and Multispectral Capability . . . 3277.3.7 The Potential of Digital Frame Cameras . . . . . . . . 3287.3.8 Microsoft Photogrammetry . . . . . . . . . . . . . . . 329

Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341

Contributors

Editor

Dr. Rainer Sandau

List of Authors

Dr. Ulrich Beisl SectionLeica Geosystems AG, Heerbrugg, Switzerland 2.9

Dr. Bernhard BrauneckerLeica Geosystems AG, Heerbrugg, Switzerland 4.2, 4.3

Dr. Michael CramerUniversität Stuttgart, Institut für Photogrammetrie, Stuttgart, Germany 2.10, 4.9

Dr. Hans DriescherDeutsches Zentrum für Luft- und Raumfahrt (DLR), Berlin, Germany 4.5

Dr. Andreas EckardtDeutsches Zentrum für Luft- und Raumfahrt (DLR), Berlin, Germany 2.8

Dipl.-Ing. Peter FrickerLeica Geosystems AG, Heerbrugg, Switzerland 7.1

Dr. Michael GruberMicrosoft Photogrammetry, Graz, Austria 7.3

Dipl.-Ing. Stefan HilbertDeutsches Zentrum für Luft- und Raumfahrt (DLR), Berlin, Germany 4.4, 4.6

Dr. Karsten JacobsenLeibniz Universität Hannover, Institut für Photogrammetrie undGeoInformation, Hannover, Germany 2.10

Dipl.-Ing. Walfried JagschitzLeica Geosystems AG, Heerbrugg, Switzerland 4.10

xi

xii Contributors

Prof. Dr. Herbert JahnDeutsches Zentrum für Luft- und Raumfahrt (DLR), Berlin, Germany 2,

2.1−2.7

Dipl.-Ing. Werner KirchhoferLeica Geosystems AG, Heerbrugg, Switzerland 4.7, 4.8

O. Univ.-Prof. Dipl.-Ing. Dr. techn. Franz LeberlTechnische Universität Graz, Austria 7.3

Dipl.-Ing. Klaus J. NeumannIntergraph AG, Aalen, Germany 7.2

Dr. Rainer SandauDeutsches Zentrum für Luft- und Raumfahrt (DLR),Berlin, Germany 1, 4,

4.1–4.3,4.10, 7

Dr. Maria von SchönermarkUniversität Stuttgart, Institut für Raumfahrtsysteme, Germany 3

Dipl.-Ing. Udo TempelmannLeica Geosystems AG, Heerbrugg, Switzerland 5, 6

Chapter 1Introduction

1.1 From Analogue to Digital Airborne Cameras

The use of aerial photography dates back to the middle of the nineteenth century.By studying applications during this period, one can easily identify the level oftechnology at each particular time. Continuous efforts have been made to employthe best technologies available in either the area of photographic technique or themethods of getting the camera airborne.

It is interesting that around 1,500 Leonardo da Vinci designed the first flyingsystems and also described the process of a “Camera Obscura”, which were quiteremarkable instruments for their time and indicative of astounding foresight. Theirimplementation, however, had to wait. The technical possibilities were limited, sincethe components to build these systems were not yet available, owing to the lack ofdifferentiated natural and engineering sciences.

Three hundred years went by before further progress was made. In 1783the first hot-air balloon was successfully flown by the Montgolfiers brothers. In1837 Daguerre was able to produce the first images. Then in 1858 the FrenchDaguerrotypist and writer Gaspare Tournachon, also called Nadar, took the firstaerial photographs, over Paris from a balloon at an altitude of 300 m (Albertz, 2001).Balloons were used for reconnaissance purposes until the middle of the twentiethcentury.

Kites were also soon utilized to take photos from an unmanned platform and in1888 Arthur Batut in France was able to take aerial photographs in this way for thefirst time. The time release for this camera was arranged by a fuse line.

Even carrier-pigeons were used to take photographs from the air. In 1903Dr. Julius Neubauer patented a miniature camera to be strapped to pigeons’ bod-ies, activated by a timer mechanism (Fig. 1.1-1). Rockets were also used as carriersof small cameras. In 1897 Alfred Nobel secured a patent for a “Photo Rocket”. Asearly as 1904, Alfred Maul, an engineer from Dresden, deployed the first “PhotoRockets”, which lifted cameras to an altitude of 800 m.

Due to progress made in the field of aviation technology, the aircraft became auseful platform from which to take aerial photographs. The first aerial photographacquired from an aircraft – an oblique – was taken in 1909 over Centocelli in Italy

1R. Sandau (ed.), Digital Airborne Camera, DOI 10.1007/978-1-4020-8878-0_1,C© Springer Science+Business Media B.V. 2010

2 1 Introduction

Fig. 1.1-1 Carrier pigeonwith miniature camera(source: Archive DeutschesMuseum)

by Wilbur Wright. Four years later, also in Italy, the first maps were produced fromaerial photographs (Falkner, 1994).

During World War I these cameras were developed even further and in 1915 thefirst cyclical camera system for systematic serial photographs was developed byOskar Messter (Albertz, 1999). This system could produce photographs at a scaleof 1:10,000, covering an area of 400 square km, taken at an altitude of 3,000 m andusing no more than 1.5 h of flying time (Willmann, 1968).

After World War I the first commercial companies to make maps using aerial pho-tographs as the major source of information were established. Colour film was soondeveloped and slowly introduced into photogrammetry. In 1925, the Wild companyproduced the C2 camera, which used panchromatic glass plates with a format of10 × 15 cm. It was used as a handheld camera (Fig. 1.1-2) or installed as aconvergent dual camera system by means of a special mount.

Before the beginning of World War II the standard format in aerial photographyboth for film and plates was 18 × 18 cm. During the Second World War aerialphotography underwent rapid development. Infrared film was introduced for thepurpose of detecting enemy positions.

During the 1970s, with the introduction of electronic computer-controlled tech-nology, manual, graphical methods of map production were replaced by computer-assisted mapping technology, which opened up tremendous possibilities. Therefinement of these developments has been an ongoing process that still contin-ues today. The 1980s and 1990s were characterised mainly by their steady progressin the application of computers to both the stereo plotter itself and map-makingsystems in general.

Analogue aerial photography and photogrammetry were developed over manydecades and have now reached a very high standard. This very mature developmenthas included the introduction of large format aerial cameras, analytical and digitalstereo restitution systems and photogrammetric scanners, all of which are describedin the appropriate literature and are considered to be well known to the reader.Examples are highly efficient analogue aerial camera systems, the Leica RC30 fromLeica Geosystems and the RMK TOP from Carl Zeiss. Today we live in a world ofdigital map production and of integration of digital map data into digital databases.

1.1 From Analogue to Digital Airborne Cameras 3

Fig. 1.1-2 Use of the Wild C2 handheld aerial camera

This facilitates merging of this data with data from other sources and data that hasbeen generated with other remote sensing sensors, opening the opportunity to meetnew requirements and generate new products.

With the beginning of photography from space, the attempt was soon made toeliminate film as the medium to “store” data. The problem of returning the filmto Earth proved to be complicated and onerous. To eliminate this, digital scannerswere developed, which allowed transmission of the image signal directly and indigital form from the satellite back to Earth. Starting from single-detector whiskb-room scanners, rapid development took place, which eventually brought us viamulti-element whiskbroom scanners to pushbroom scanners and matrix systems,technologies which are still used today in space-based photogrammetry and remotesensing worldwide. They allow the generation of multispectral and stereo imageswith a high degree of geometric and radiometric resolution. ERTS (Earth ResourceTechnology Satellite) was the first civil Earth observation satellite, launched in1972 to acquire images from the Earth’s surface. Later this system was renamedLandsat-1. Its sensor system MSS (Multispectral Scanner System) consisted ofa single-detector whiskbroom scanner. In 1980 the first CCD lines for satelliteimage acquisition were implemented on METEOR-PRIRODA-5. The sensor systemMSU-E (Multispectral Scanning Unit-Electronic) worked in a pushbroom mode. In1986 SPOT-1 became the first satellite to acquire time-generated stereo images via“off-track imaging”. To generate stereo images the single line pushbroom scannerHRV (High Resolution Visible) took two strips of images from two neighbouring

4 1 Introduction

orbits oriented towards the area which was to be photographed in stereo. MOMS-02 was the first sensor system to use the three-line stereo method (In-Track-Stereo)patented by Otto Hofmann in 1979 (Hofmann, 1982). In 1993 MOMS-02 was flownon the Space Shuttle Mission STS 55 and in 1996 it was installed in the PRIRODA-Module of the MIR Space Station. MOMS-02 used one objective lens for eachstereo channel. The first space-based mission of a Three-Line Stereo System, whichhad the three stereo lines arranged on the focal plane behind one single wide-angleobjective lens, was achieved with BIRD (Bi-Spectral Infrared Detection) in 2001(Briess, 2001). WAOSS-B (Wide-Angle Optoelectronic Stereo Scanner-BIRD) isthe modified version of WAOSS, a sensor system on the Russian Mars 96 Missionthat was designed to observe the dynamics in the atmosphere and on the sur-face of Mars (Sandau, 1998). Unfortunately this mission failed in its initial launchstage.

Most of the sensor systems which were developed for space-based applicationsgave rise also to versions developed for use in aircraft [for example, Sandau andEckardt (1996)]. As a result they have been used for test purposes or/and for scien-tific or commercial applications. Examples of a number of different German sensorsystems are:

• MEOSS: the satellite version was also used on aircraft• MOMS-02: DPA (Digital Photogrammetry Assembly) as the airborne version• WAOSS: WAAC (Wide-Angle Airborne Camera) as the airborne version• HRSC: HRSC-A and HRSC-AX as airborne versions (HRSC – High Resolution

Stereo Camera – was the second German stereo camera for the failed Mars 96Mission; it is now part of the ESA-Mission Mars Express, launched in 2003).

The development of these different techniques and sensors evolved in parallelwith the increased utilisation of aerial photographs in digital map production. Iffilm images are to be entered into digital databases, they must be converted intodigital form using photogrammetric scanners. Owing to the development of space-based sensor technologies as mentioned above and the strong development trendsin other high technology fields essential to this application, it eventually becamepracticable and economically feasible to go beyond scanning and replace the con-ventional film used in aerial photography with direct digital imagery. Owing to themany significant advances in key technological disciplines such as optics, mechan-ics, critical materials, micro-electronics, micro-mechanics, detector and computertechnologies, signal processing, communication and navigation, we now havefinancially realistic solutions for digital airborne camera systems accepted on themarket.

One concept considered for a digital camera system is to replace the conventionalfilm by suitable digital matrices or blocks of matrices. Another is to implement sin-gle or multiple detector lines to create the digital image data. The first ideas alongthese lines were indicated in a dissertation at the University of New Brunswick(Derenyi, 1970). Independently from this, Otto Hoffmann developed and patentedthe Three Line Concept of a Digital Airborne Camera system (Hofmann, 1982,

1.1 From Analogue to Digital Airborne Cameras 5

1988). This Three Line Concept has already been utilized in spaceborne camera sys-tems (e.g. MOMS-02, WAOSS) and for experimental purposes in airborne cameras(e.g. MEOSS, DPA, WAAC, HRSC).

The first commercially available digital airborne camera systems, the ADS40from Leica Geosystems (formerly LH Systems) and the DMC from Intergraph (for-merly Z/I Imaging), were introduced in the year 2000 at the ISPRS Congress inAmsterdam. Other digital airborne camera systems were introduced into the marketlater. Section 1.5 gives examples of commercial systems presently available on themarket.

Reasonably priced digital airborne camera systems which immediately deliverthe image in digital form are only one attractive reason to switch from conventionalfilm cameras to digital camera systems. There are other significant economic rea-sons for doing so as described in Fig. 1.1-3. The direct digital approach using thedigital airborne camera system eliminates the processes of developing the conven-tional film and scanning each individual photograph into digital form. This directapproach eliminates sources of errors and inaccuracies. Most importantly, it resultsin significant savings in investment and costs related to personnel.

If the correct design concept is applied, the digital airborne camera system isable to deliver stereo information, RGB data RGB data and IR data simultaneouslyduring one flight. With conventional analogue aerial cameras it is necessary to flythe area more than once owing to different film requirements (panchromatic, colourand FCIR), or to have multiple cameras in the aircraft.

Fig. 1.1-3 Comparison between the workflows for analogue and digital airborne cameras

6 1 Introduction

The thematic interpretation of image data can be significantly improved too,because with digital technology the filter values required for specific applicationscan be taken into consideration at the time of the design of the system.

These last two arguments in favour of a digital image generated directly by thedigital airborne camera system strongly indicate that photogrammetry and remotesensing continue to coalesce. In many cases topographic information (e.g. digitalterrain models) is essential to expedite thematic interpretation (remote sensing) ofthe data within a specific area; for photogrammetric applications, such as cartogra-phy, the colour information is often necessary for a finished product. With the newtask of preprocessing the flight data in digital form, the interface between the com-pany flying the imagery and the company processing the digital imagery into a finalproduct may now shift in such a way that the former takes over more processingactivities than ever before (see Chapter 6). The future will show whether the flyingoperation becomes involved in the overall process of generating the final product,and to what extent it is willing to do so or capable thereof.

Working directly from digital imagery instead of film is opening up other verysignificant possibilities in remote sensing. As can be seen from Fig. 1.1-4, filmrecords light rays in an s-shaped logarithmic curve. This so called DlogE curveshows the relationship between the relative illumination (exposure) and the result-ing density in the photograph, the density D as a function of the logarithm of theexposure E. The term relative illumination is used because the value depends on theexposure setting (exposure time, aperture, etc.) and the film processing (developing,fixing, washing etc.). The CCD elements, which function as optoelectronic convert-ers, present themselves in a linear curve. This opens up the possibility of measuringwithin the spectral ranges selected by different filters. The photons hitting the detec-tor elements within a specific, selected filter range can be counted and therefore canbe interpreted as an actual physical measuring unit.

Fig. 1.1-4 Characteristics of CCD detectors and film materials (qualitative)

1.1 From Analogue to Digital Airborne Cameras 7

Modern electro-optical converters allow dynamic ranges of 1:4,000 (12-bitdynamic capacity) or better. With this capability it is possible to span illuminationranges from high reflectance to very low reflectance apparent in deep shadows in asingle image (see Fig. 1.1-5). This is also relevant in the matching procedures of dig-ital image processing. The histograms in Fig. 1.1-5 represent the number of pixelswithin the respective illumination ranges. If one “zooms” in radiometrically withinspecific areas, details will be very recognisable. The high dynamic range combinedwith the linear “curves” are characteristic of the quality of modern electro-opticalconverters (CCD detectors) and therefore also the quality of the new digital airbornecamera systems.

The digital image technology used in modern airborne camera systems, throughappropriate system design and configuration, enables speedy transition from thetraditional photographic camera to a measuring system that captures images. Thisopens up completely new application areas for digital airborne imaging sensors. Thefact that the new digital airborne cameras can be used for classical photogramme-try as well as for airborne remote sensing creates opportunities in market segmentswhich so far have not been explored. This will also result in a significant increasein the processing of such digital imagery and will result in the development of com-pletely new “intelligent” methods to deal with such data. This trend is stronglysupported by ongoing development of and improvement to existing and newly avail-able digital photogrammetric workstations, on which software to deal with thesedigital images is being installed (Ackermann, 1995). The introduction and progress

Fig. 1.1-5 The large dynamic range of the digital sensor provides the unique opportunity to resolvedetails in the dark as well as the bright areas of the image (Fricker et al., 2000)

8 1 Introduction

of digital airborne camera systems in photogrammetry and remote sensing, facil-itated by the immense progress in diverse fields of technology, obviously has farreaching consequences in these respective fields, which no doubt will also have asignificant influence on education, on the structure of companies active in thesefields and on the development of new job opportunities.

1.2 Applications for Digital Airborne Camerasin Photogrammetry and Remote Sensing

Geometric data are derived with the aid of photogrammetry through measure-ment in image material. The task of digital photogrammetry lies in the use ofmethods of image processing, such as automatic point measurement, co-ordinatetransformation, image matching to derive elevation data and differential imagerectification to produce orthoimages with a cartographically compatible geometry.Remote sensing is the contact-free imaging or measurement of objects for generat-ing qualitative or quantitative data on their occurrence, their state or changes in theirstate. Further comments and remarks can be found in Albertz (2001), Hildebrandt(1996), Konecny (2003), Kraus (1988, 1990) and others. New digital sensor systemscan provide all data for

• determining the sizes and shapes of objects with the aid of photogrammetry,• making the photographed content accessible to thematic evaluation through

analysis and interpretation for a specific purpose,• determining the meaning of the recorded data through semantic evaluation.

Two parameters are particularly characteristic of photogrammetry and remotesensing: geometric resolution, which is best expressed by ground sample distance(GSD) in the case of digital systems, and radiometric resolution. Figure 1.2-1 showswhich spectral resolutions and GSDs are required for topographic mapping and forselected thematic (remote sensing) applications (Röser et al., 2000). Spectral reso-lution is shown only in qualitative terms. The following is a rough classification ofthe different types of imagery and their suitability for various tasks:

• panchromatic imagery to recognise and survey the structure of the earth’s surfaceand objects located on it

• multispectral imagery for making a rough classification of the chemical andbiophysiological properties of the earth’s surface and of objects situated on it

• hyperspectral imagery for identifying and making a refined classification of thegeological, chemical and biophysiological properties of the earth’s surface and ofobjects situated on it.

A principle that applies to all applications is that as few spectral channels aspossible should be used.

Revisit rate is another parameter that affects the monitoring of application-specific changes. Figure 1.2-2 shows the required revisit rates for selectedapplications. Figures 1.2-1 and 1.2-2 show that topographic maps with a revisit

1.2 Applications for Digital Airborne Cameras in Photogrammetry and Remote Sensing 9

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al- Hydrology- Agriculture- Resource monitoring- Environmental monitoring- Forestry- Intelligence services

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Fig. 1.2-1 Spectral and geometric resolutions required for various applications (Röseret al., 2000)

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Fig. 1.2-2 Required geometric resolutions and revisit rates (Röser et al., 2000)

10 1 Introduction

Table 1.2-1 Ground pixelsize and achievableplanimetric mappingscales

GSD Mapping scale

5 cm 1:50010 cm 1:1,00025 cm 1:2,50050 cm 1:5,0001 m 1:10,0002.5 m 1:25,0005 m 1:50,00010 m 1:100,00050 m 1:500,000

rate of 1–10 years with a GSD in the range of 5 cm–50 m are required. Theassociated map scales for selected applications are in the 1:500–1:500,000 range(Table 1.2-1).

The stereo angles achieved with an airborne camera influence the accuracyof object point determination. Larger stereo angles correspond to larger potentialheight resolution but may lead to problems as a result of the larger radial offset inthe image.

Experience gained with analogue airborne cameras has shown that differentstereo angles are required to achieve optimum results for topography or for objectextraction applications. It was found that large stereo angles often do not yield thedesired precision in hilly or mountainous, built-up or wooded areas. Good imagesthat can be readily correlated are required in digital photogrammetry. Table 1.2-2shows the stereo angle ranges for various terrains and situations.

Table 1.2-2 Stereo angles for various applications

Topographic applications Stereo angleFlat terrain and high height accuracy 30◦–60◦Hilly terrain 20◦–40◦Mountainous areas 10◦–25◦

Object extraction applicationsNatural landscape 30◦–50◦Suburban areas 20◦–40◦Urban areas 10◦–25◦Woodland 10◦–25◦

Remote sensing applications give rise to a modified filter design with regard tothe spectral requirements. This is illustrated in Fig. 1.2-3.

The blue spectral channel with 460 ± 30 nm is placed in the weak absorptionrange of chlorophyll of green vegetation in water or on the surface (maximumbetween 430 and 450 nm). This channel is important for observing water bodies.The 560 ± 25 nm green spectral channel lies in the reflectance maximum of green

1.2 Applications for Digital Airborne Cameras in Photogrammetry and Remote Sensing 11

Fig. 1.2-3 Illustration of a filter design mainly for observing vegetation

vegetation and is also used to detect chlorophyll in water bodies. The second absorp-tion band of chlorophyll lies in the 635 ± 25 nm red spectral channel (maximum at650 nm).

At 860 ± 25 nm, the NIR channel lies on the plateau of vegetation curves and, inconjunction with the red channel, which ends in front of the vegetation edge (“rededge”), provides data on the state of the vegetation.

The spectral responsivity of colour film is broad-banded for the various spectralchannels, and the spectral channels overlap (Fig. 1.2-4). This overlap of the spectral

Fig. 1.2-4 Spectral responsivity of colour film material and of a detector system designed forphotogrammetry and remote sensing (Leica, 2004)

12 1 Introduction

channels is good for the colour film impression or infrared colour film impression,but it does not support remote sensing applications. The central wavelengths and thespectral bandwidths for multispectral and true-colour images differ. Multispectralapplications require non-overlapping, narrow spectral bands, and, for observing veg-etation, also an infrared channel near the vegetation edge (red edge). In contrast, thetrue-colour channels are rather more adjusted to spectral visual sensitivity and forthis reason are broad-banded and overlapping.

Hence, a sensor system or digital airborne camera for photogrammetry andremote sensing must be equipped with filters that generate narrow spectral channelswhich are separated from each other. The true-colour images can be derived fromthe RGB channels designed in this manner using a process of colour transformation,possibly in conjunction with a panchromatic channel (see Section 2.7).

The absorption filters mounted during the manufacture of CCD matrices are alsonot so well suited to the multispectral applications discussed above.

The bandpass response of typical narrow-band absorption filters is shown in theright-hand part of Fig. 1.2-5. Absorption filter Absorption filters cannot be producedas perfectly and with such narrow bands as interference filters (see Section 4.3.2).The transitions are not sufficiently steep. For instance, the green filter does not com-pletely absorb the red and blue parts of the spectrum. The interference filters shownon the left-hand sides of Figs. 1.2-4 and 1.2-5 can be implemented with much greaterprecision. It should be mentioned, however, that a considerable amount of effort isinvolved in manufacturing them (many metal oxide layers have to be vapour-platedon to the glass bases in a vacuum).

Summing up, it can be said that modern digital detector components enable dig-ital airborne cameras for photogrammetry and remote sensing to be developed andmanufactured. Often they make it possible to improve the quality of the resultsachieved using analogue airborne cameras and to expand the range of applications.

Fig. 1.2-5 Comparison of spectral responsivities of detectors fitted with absorption filters and adetector system designed for photogrammetry and remote sensing (Leica, 2004)

1.3 Aircraft Camera or Satellite Camera 13

1.3 Aircraft Camera or Satellite Camera

Digital airborne sensors suitable for photogrammetry and remote sensing applica-tions currently occupy a position between analogue airborne cameras, which poten-tially have higher geometric resolution but limited spectral variability, dependenton the available film material, on the one hand, and satellite systems, which have alower geometric resolution, but in many instances a higher spectral resolution, onthe other.

Figure 1.3-1 is a schematic representation of the performance of sensor sys-tems based on the key parameters: geometric and spectral resolution. Analogueairborne cameras can provide virtually any resolution down to about 1 cm. Digitalairborne cameras are already capable of a ground sample distance (GSD) below5 cm. Satellite systems using panchromatic systems (roughly comparable to black-and-white film) have reached a GSD below 0.5 m. Figure 1.3-2 illustrates thedevelopment of GSD of satellite systems. From 80 m GSD achieved by ERTS (laterrenamed Landsat-1) – the first satellite launched for civil earth observation in 1972 –we have advanced to 0.41 m GSD.

Fig. 1.3-1 Performance for sensor systems

Table 1.3-1 shows characteristics of selected satellite systems, such as the coarserGSD of multispectral channels, swath width, scene size and revisit time (time inter-val until the next opportunity to photograph the same area), indicating the potentialgeometric and time coverage.

14 1 Introduction

QuickBird

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SPOT-1 ADEOS

IRS-1C

IKONOS

EO-1

EROS-A1SPOT-5

IRS-1A

Resurs-O1-1

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0.5WorldView-1

1970 1975 1980 1985 1990 1995 2000 2005 2010

Fig. 1.3-2 GSD development of civil satellite systems in the panchromatic channel

Table 1.3-1 Selected imaging satellite systems

GSD [m]

Satellite LaunchOrbit altitude(km) PAN

MS (R, G, B,SWIR)

Swathwidth (km)

Revisit(days)

Scene size(km × km)

Landsat-7 1999 705 14 28 185 16 185 × 185SPOT-5 1999 832 5/3.5a 10 60 5 60 × 60IKONOS 1999 680 1 4 13 1–3 11 × 11QuickBird 2001 450 0.62 2.5 16.5 1–3.5 16.5 × 16.5WorldView-1 2007 496 0.5 − 17.6 1.7–4.6 Max. 60 ×

110

a In “supermode” with staggered line array, GSD = 3.5 m.

The connection between GSD and repeat rate is represented in Fig. 1.3-3(Konecny, 2003). Every 30 min, such geostationary satellites as Meteosat andGOES, orbiting the earth at an altitude of roughly 36,000 km, supply images ofa complete hemisphere in three spectral channels (one of them in the thermal IR)with a GSD of 5 km. NOAA satellites circling the earth in polars orbit at an altitudeof 850 km provide images in five channels with a GSD of 1 km once every 12 h formeteorological purposes.

Owing to the high probability of an overcast sky, sun-synchronous satellites, forexample, Landsat, SPOT and IRS, which have repeat rates of less than one month,

1.3 Aircraft Camera or Satellite Camera 15

Fig. 1.3-3 Connection between repeat rate and ground resolution (Konecny, 2003)

can supply images of intermediate resolution (5–14 m pan and 10–28 m MS) only afew times a year. But coverage of large areas is possible only at intervals of severalyears. High-resolution satellite systems (IKONOS with 1 m GSD or Russian pho-tographic systems with a resolution of 2 m) are approaching the resolution rangeof aerial images obtained from high-flying aircraft. The highest resolutions in thedecimeter to centimeter range are obtained with low-flying airborne cameras orground surveys at correspondingly longer time intervals.

Figure 1.3-4 illustrates the huge differences in altitude from which civil earthobservation systems and aircraft systems carry out imaging operations. The differ-ence of about 1:200 (3–600 km) illustrates, in qualitative terms at least, that satellitesystems are much more complex and costly to make than aircraft systems to achievecomparable GSDs. This is also reflected in the costs of the image products andexplains why more than 80% of the earth is mapped with airborne cameras. Themain reason lies in the ratio between the focal lengths, which, like the altitude ratio,is 1:200. Figure 1.3-4 gives an impression on the flight hight ranges of airborne andspaceborne sensors. Speed differences also play a role. An aircraft, for instance, fliesat a speed of 70 m/s, whereas the ground track of an LEO satellite at an altitude ofroughly 600 km is approximately 7 km/s. The speed ratio and hence the ratio of theintegration times is 1:100.

16 1 Introduction

Fig. 1.3-4 General situationfor flighing hight of airborneand space borne sensors

1.3.1 Detection, Recognition, Identification

The information the human brain is able to derive from an image depends on thenumber of picture dots (pixels) in a pixel conglomerate. Image interpreters typicallyuse the following decision levels:

• Detection: discovering the existence of an object• Recognition: classifying the object as belonging to a type group• Identification: identifying the object type.

The number of pixels occupied by the object determines the certainty of the deci-sion regarding the existence of an object or even its identification. Information aboutthe object type is not substantially improved, nor the likelihood of identification ofa certain object type substantially increased, if, for instance, a the number of pixelsviewed is a 100 times the number required to reach a decision. In other words, theobject’s size and structure determine the required pixel size or GSD. In this respect,there are optimal applications for high-resolution sensors with small GSDs and forsensors with larger GSDs. The critical question is how many pixels are needed toachieve a certain decision quality. Figure 1.3-5 illustrates the issue sketched in theforegoing.

Figure 1.3-6 is an example in which the identification of a car about 5 m in lengthis used to illustrate the relationships. The component pictures in Fig. 1.3-7 whichare to be recognised and identified are once again highlighted.

Figure 1.3-8 shows the situations in which decisions would have to be made whenviewing the image material obtained by the QuickBird satellite with GSD = 0.8 m,

1.3 Aircraft Camera or Satellite Camera 17

Fig. 1.3-5 GSD and object identification (Leica, 2004)

Fig. 1.3-6 GSD and object identification using a car about 5 m long (Leica, 2004)

a digital airborne camera with GSD = 0.2 m and an analogue airborne camera witha simulated GSD = 0.1 m.

The number of object pixels required for the three decision levels is not consis-tently defined. Practitioners sometimes refer to the Johnson criteria (Johnson, 1985),which have been modified somewhat over the years. Table 1.3-2 shows the numberof object pixels required for a decision probability of 50% for the object’s one- andtwo-dimensional expansion (Holst, 1996).

18 1 Introduction

Fig. 1.3-7 Component images for reconition and identification from Fig. 1.3-5 as an illustration(Leica, 2004)

Fig. 1.3-8 Images fromQuickBird, GSD GSD = 0.8m, a digital airborne camera,GSD = 0.2 m, and ananalogue airborne camera,simulated GSD = 0.1 m(Leica, 2004)

1.3 Aircraft Camera or Satellite Camera 19

Table 1.3-2 Decision thresholds derived from the Johnson criterion

Decision DescriptionOne-dimensionalN50 2D N50

Detection The pixel represents an object beingsought with good probability

1 0.75

Recognition Allocation to a specific class withhierarchical certainty

4 3

Identification Specification within a class withhierarchical certainty

8 6

Table 1.3-3 Factors forchanging the outcomeprobabilities in Table1.3-2

Outcome probability Factor

1.00 3.00.95 2.00.80 1.50.50 1.00.30 0.750.10 0.500.02 0.250 0

Table 1.3-3 shows the requisite factors by which the values in Table 1.3-2 needto be multiplied to obtain an outcome probability other than 50% (Ratches, 1975).

It is contended, therefore, that aircraft and satellite systems are complementary.Some essential characteristics of satellite systems are:

• Fixed orbit: area coverage being predictable but dependent on cloud cover• Applicable without having to invest a great deal of effort into preparation• Fixed GSD, current minimum 0.5 m panchromatic and 2 m multispectral• Known costs per scene.

Essential characteristics of aircraft systems:

• Flexible application on demand• Usable even in unfavourable weather (flying below the clouds)• GSD adaptable to the task at hand by varying flight altitude• Stereo data easily acquired.

Data from airborne and satellite sensors is complementary in many applications.Different sensors and platforms have to be used owing to the great variety of objectsto be observed and/or surveyed with respect to size, shape, texture and colour or toproperties that can be differentiated only with multispectral or hyperspectral sensors.Given the increasingly expanding fields of application and the use of GIS stations,it is necessary to fuse all types of sensor date in order to meet the demand forinformation quickly and reliably. Data fusion and GIS have a high potential forcreating new lines of business.