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This fourth and full colour edition updates and expands a widely-used textbook aimed at advanced undergraduate and postgraduate students taking courses in remote sensing and GIS in Geography, Geology and Earth/Environmental Science departments. Existing material has been brought up to date and new material has been added. In particular, a new chapter, exploring the two-way links between remote sensing and environmental GIS, has been added.
New and updated material includes:
This book provides the material required for a single semester course in Environmental Remote Sensing plus additional, more advanced, reading for students specialising in some aspect of the subject. It is written largely in non-technical language yet it provides insights into more advanced topics that some may consider too difficult for a non-mathematician to understand. The case studies available from the website are fully-documented research projects complete with original data sets. For readers who do not have access to commercial image processing software, MIPS provides a licence-free, intuitive and comprehensive alternative.
“As well as dikes, sills, and laccoliths, there is an exceptionally clear and finely illustrated explanation of ophiolites, a topic routinely ignored in many Earth science texts despite their significance. Add later chapters on kimberlites, volcanic climate modification over time, and a look at how we monitor volcanoes, and you have a very well-done enjoyable “little” book.” (The Leading Edge, 1 August 2012)
Preface to the Second Edition xiii
Preface to the Third Edition xvii
Preface to the Fourth Edition xix
List of Examples xxi
1 Remote Sensing: Basic Principles 1
1.1 Introduction 1
1.2 Electromagnetic Radiation and Its Properties 4
1.2.1 Terminology 4
1.2.2 Nature of Electromagnetic Radiation 6
1.2.3 The Electromagnetic Spectrum 6
1.2.4 Sources of Electromagnetic Radiation 13
1.2.5 Interactions with the Earth's Atmosphere 15
1.3 Interaction with Earth-Surface Materials 17
1.3.1 Introduction 17
1.3.2 Spectral Reflectance of Earth Surface Materials 19
1.4 Summary 26
2 Remote Sensing Platforms and Sensors 29
2.1 Introduction 29
2.2 Characteristics of Imaging Remote Sensing Instruments 31
2.2.1 Spatial Resolution 32
2.2.2 Spectral Resolution 35
2.2.3 Radiometric Resolution 37
2.3 Optical, Near-infrared and Thermal Imaging Sensors 39
2.3.1 Along-Track Scanning Radiometer (ATSR) 40
2.3.2 Advanced Very High Resolution Radiometer (AVHRR) and NPOESS VIIRS 41
2.3.3 MODIS 42
2.3.4 Ocean Observing Instruments 42
2.3.5 IRS LISS 45
2.3.6 Landsat Instruments 46
2.3.7 SPOT Sensors 48
2.3.8 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 53
2.3.9 High-Resolution Commercial and Small Satellite Systems 53
2.4 Microwave Imaging Sensors 58
2.4.1 European Space Agency Synthetic Aperture Spaceborne Radars 62
2.4.2 Radarsat 63
2.4.3 TerraSAR-X and COSMO/Skymed 64
2.4.4 ALOS PALSAR 65
2.5 Summary 66
3 Hardware and Software Aspects of Digital Image Processing 67
3.1 Introduction 67
3.2 Properties of Digital Remote Sensing Data 67
3.2.1 Digital Data 67
3.2.2 Data Formats 74
3.2.3 System Processing 78
3.3 Numerical Analysis and Software Accuracy 80
3.4 Some Remarks on Statistics 83
3.5 Summary 84
4 Preprocessing of Remotely-Sensed Data 87
4.1 Introduction 87
4.2 Cosmetic Operations 89
4.2.1 Missing Scan Lines 89
4.2.2 Destriping Methods 90
4.3 Geometric Correction and Registration 94
4.3.1 Orbital Geometry Model 96
4.3.2 Transformation Based on Ground Control Points 98
4.3.3 Resampling Procedures 108
4.3.4 Image Registration 111
4.3.5 Other Geometric Correction Methods 111
4.4 Atmospheric Correction 112
4.4.1 Background 112
4.4.2 Image-Based Methods 114
4.4.3 Radiative Transfer Models 115
4.4.4 Empirical Line Method 115
4.5 Illumination and View Angle Effects 116
4.6 Sensor Calibration 117
4.7 Terrain Effects 121
4.8 Summary 123
5 Image Enhancement Techniques 125
5.1 Introduction 125
5.2 Human Visual System 126
5.3 Contrast Enhancement 128
5.3.1 Linear Contrast Stretch 128
5.3.2 Histogram Equalization 129
5.3.3 Gaussian Stretch 138
5.4 Pseudocolour Enhancement 140
5.4.1 Density Slicing 140
5.4.2 Pseudocolour Transform 144
5.5 Summary 145
6 Image Transforms 147
6.1 Introduction 147
6.2 Arithmetic Operations 148
6.2.1 Image Addition 148
6.2.2 Image Subtraction 149
6.2.3 Image Multiplication 150
6.2.4 Image Division and Vegetation Indices 152
6.3 Empirically Based Image Transforms 156
6.3.1 Perpendicular Vegetation Index 156
6.3.2 Tasselled Cap (Kauth–Thomas) Transformation 157
6.4 Principal Components Analysis 160
6.4.1 Standard Principal Components Analysis 160
6.4.2 Noise-Adjusted PCA 168
6.4.3 Decorrelation Stretch 169
6.5 Hue-Saturation-Intensity (HSI) Transform 171
6.6 The Discrete Fourier Transform 172
6.6.1 Introduction 172
6.6.2 Two-Dimensional Fourier Transform 173
6.6.3 Applications of the Fourier Transform 178
6.7 The Discrete Wavelet Transform 178
6.7.1 Introduction 178
6.7.2 The One-Dimensional Discrete Wavelet Transform 179
6.7.3 The Two-Dimensional Discrete Wavelet Transform 186
6.8 Change Detection 187
6.8.1 Introduction 187
6.8.2 NDVI Difference Image 188
6.8.3 PCA 188
6.8.4 Canonical Correlation Change Analysis 192
6.8.5 Summary 195
6.9 Image Fusion 196
6.9.1 Introduction 196
6.9.2 HSI Algorithm 198
6.9.3 PCA 198
6.9.4 Gram-Schmidt Orthogonalization 198
6.9.5 Wavelet-Based Methods 198
6.9.6 Evaluation – Subjective Methods 199
6.9.7 Evaluation – Objective Methods 200
6.10 Summary 202
7 Filtering Techniques 203
7.1 Introduction 203
7.2 Spatial Domain Low-Pass (Smoothing) Filters 204
7.2.1 Moving Average Filter 204
7.2.2 Median Filter 208
7.2.3 Adaptive Filters 209
7.3 Spatial Domain High-Pass (Sharpening) Filters 214
7.3.1 Image Subtraction Method 214
7.3.2 Derivative-Based Methods 215
7.4 Spatial Domain Edge Detectors 219
7.5 Frequency Domain Filters 221
7.6 Summary 227
8 Classification 229
8.1 Introduction 229
8.2 Geometrical Basis of Classification 231
8.3 Unsupervised Classification 233
8.3.1 The k-Means Algorithm 233
8.3.2 ISODATA 234
8.3.3 A Modified k-Means Algorithm 239
8.4 Supervised Classification 240
8.4.1 Training Samples 240
8.4.2 Statistical Classifiers 245
8.4.3 Neural Classifiers 250
8.5 Subpixel Classification Techniques 254
8.5.1 The Linear Mixture Model 258
8.5.2 Spectral Angle Mapping 263
8.5.3 ICA 265
8.5.4 Fuzzy Classifiers 265
8.6 More Advanced Approaches to Image Classification 267
8.6.1 Support Vector Machines 267
8.6.2 Decision Trees 269
8.6.3 Other Methods of Classification 270
8.7 Incorporation of Non-spectral Features 272
8.7.1 Texture 272
8.7.2 Use of External Data 275
8.8 Contextual Information 276
8.9 Feature Selection 277
8.10 Classification Accuracy 280
8.11 Summary 283
9 Advanced Topics 285
9.1 Introduction 285
9.2 SAR Interferometry 285
9.2.1 Basic Principles 285
9.2.2 Interferometric Processing 290
9.2.3 Problems in SAR Interferometry 292
9.2.4 Applications of SAR Interferometry 293
9.3 Imaging Spectroscopy 294
9.3.1 Introduction 294
9.3.2 Processing Imaging Spectroscopy Data 300
9.4 Lidar 315
9.4.1 Introduction 315
9.4.2 Lidar Details 318
9.4.3 Lidar Applications 321
9.5 Summary 323
10 Environmental Geographical Information Systems: A Remote Sensing Perspective 325
10.1 Introduction 325
10.1.1 Definitions 326
10.1.2 The Synergy between Remote Sensing and GIS 327
10.2 Data Models, Data Structures and File Formats 328
10.2.1 Spatial Data Models 328
10.2.2 Data Structures 329
10.2.3 File Formats 331
10.2.4 Raster to Vector and Vector to Raster Conversion 331
10.3 Geodata Processing 332
10.3.1 Buffering 332
10.3.2 Overlay 332
10.4 Locational Analysis 333
10.4.1 Slope and Aspect 333
10.4.2 Proximity Analysis 334
10.4.3 Contiguity and Connectivity 334
10.5 Spatial Analysis 335
10.5.1 Point Patterns and Interpolation 335
10.5.2 Relating Field and Remotely-Sensed Measurements: Statistical Analysis 337
10.5.3 Exploratory Data Analysis and Data Mining 338
10.6 Environmental Modelling 338
10.7 Visualization 340
10.8 Multicriteria Decision Analysis of Groundwater Recharge Zones 345
10.8.1 Introduction 345
10.8.2 Data Characteristics 346
10.8.3 Multicriteria Decision Analysis 351
10.8.4 Evaluation 352
10.8.5 Conclusions 352
10.9 Assessing Flash Flood Hazards by Classifying Wadi Deposits in Arid Environments 355
10.9.1 Introduction 355
10.9.2 Water Resources in Arid Lands 355
10.9.3 Case Study from the Sinai Peninsula, Egypt 356
10.9.4 Optical and Microwave Data Fusion 357
10.9.5 Classification of Wadi Deposits 360
10.9.6 Correlation of Classification Results with Geology and Terrain Data 360
10.9.7 Conclusions 365
10.10 Remote Sensing and GIS in Archaeological Studies 365
10.10.1 Introduction 365
10.10.2 Homul (Guatemala) Case Study 365
10.10.3 Aksum (Ethiopia) Case Study 371
10.10.4 Conclusions 374
Appendix A Accessing MIPS 377
Appendix B Getting Started with MIPS 379
Appendix C Description of Sample Image Datasets 381
Appendix D Acronyms and Abbreviations 385
References 389
Index 429
Overview
This fourth and full colour edition updates and expands a widely-used textbook aimed at advanced undergraduate and postgraduate students taking courses in remote sensing and GIS in Geography, Geology and Earth/Environmental Science departments. Existing material has been brought up to date and new material has been added. In particular, a new chapter, exploring the two-way links between remote sensing and environmental GIS, has been added.
New ...