Essential Image Processing and GIS for Remote Sensing is an accessible overview of the subject and successfully draws together these three key areas in a balanced and comprehensive manner. The book provides an overview of essential techniques and a selection of key case studies in a variety of application areas.Key concepts and ideas are introduced in a clear and logical manner and described through the provision of numerous relevant conceptual illustrations. Mathematical detail is kept to a minimum and only referred to where necessary for ease of understanding. Such concepts are explained through common sense terms rather than in rigorous mathematical detail when explaining image processing and GIS techniques, to enable students to grasp the essentials of a notoriously challenging subject area. The book is clearly divided into three parts, with the first part introducing essential image processing techniques for remote sensing. The second part looks at GIS and begins with an overview of the concepts, structures and mechanisms by which GIS operates. Finally the third part introduces Remote Sensing Applications. Throughout the book the relationships between GIS, Image Processing and Remote Sensing are clearly identified to ensure that students are able to apply the various techniques that have been covered appropriately. The latter chapters use numerous relevant case studies to illustrate various remote sensing, image processing and GIS applications in practice.
Author(s): Jian Guo Liu, Philippa Mason
Edition: 1
Year: 2009
Language: English
Pages: 460
Essential Image Processing and GIS for Remote Sensing......Page 2
Contents......Page 8
Overview of the Book......Page 18
Part One: Image Processing......Page 20
1.1 What is a digital image?......Page 22
1.2.1 Monochromatic display......Page 23
1.2.2 Tristimulus colour theory and RGB colour display......Page 24
1.2.3 Pseudo colour display......Page 26
Questions......Page 27
2.1 Histogram modification and lookup table......Page 28
2.2 Linear contrast enhancement......Page 30
2.2.1 Derivation of a linear function from two points......Page 31
2.3.1 Logarithmic contrast enhancement......Page 32
2.4 Histogram equalization......Page 33
2.5 Histogram matching and Gaussian stretch......Page 34
2.6.1 *Derivation of coefficients, a, b and c for a BCET parabolic function......Page 35
2.8 Tips for interactive contrast enhancement......Page 37
Questions......Page 38
3.1 Image addition......Page 40
3.3 Image multiplication......Page 41
3.4 Image division (ratio)......Page 43
3.5 Index derivation and supervised enhancement......Page 45
3.5.1 Vegetation indices......Page 46
3.5.2 Iron oxide ratio index......Page 47
3.7.1 Analysis of solar radiation balance and simulated irradiance......Page 48
3.7.2 Simulated spectral reflectance image......Page 49
3.7.3 Calculation of weights......Page 50
3.7.4 Example: ATM simulated reflectance colour composite......Page 51
3.7.5 Comparison with ratio and logarithmic residual techniques......Page 52
3.8 Summary......Page 53
Questions......Page 54
4.1 Fourier transform: understanding filtering in image frequency......Page 56
4.2 Concepts of convolution for image filtering......Page 58
4.3 Low-pass filters (smoothing)......Page 59
4.3.1 Gaussian filter......Page 60
4.3.4 Adaptive median filter......Page 61
4.3.7 Conditional smoothing filters......Page 62
4.4 High-pass filters (edge enhancement)......Page 63
4.4.1 Gradient filters......Page 64
4.4.2 Laplacian filters......Page 65
4.4.3 Edge-sharpening filters......Page 66
4.6 *FFT selective and adaptive filtering......Page 67
4.6.1 FFT selective filtering......Page 68
4.6.2 FFT adaptive filtering......Page 70
Questions......Page 73
5.1 Colour coordinate transformation......Page 76
5.2 IHS decorrelation stretch......Page 78
5.3 Direct decorrelation stretch technique......Page 80
5.4 Hue RGB colour composites......Page 82
5.5.1 Derivation of RGB–IHS Transformation......Page 84
5.5.2 Derivation of IHS–RGB transformation......Page 85
5.6.1 Mathematical proof of DDS......Page 86
5.6.2 The properties of DDS......Page 87
Questions......Page 89
6.1 RGB–IHS transformation as a tool for data fusion......Page 90
6.3 Smoothing-filter-based intensity modulation......Page 92
6.3.1 The principle of SFIM......Page 93
6.3.2 Merits and limitation of SFIM......Page 94
Questions......Page 95
7.1 Principle of PCA......Page 96
7.2 Principal component images and colour composition......Page 99
7.3.1 Dimensionality and colour confusion reduction......Page 101
7.3.2 Spectral contrast mapping......Page 102
7.3.3 FPCS spectral contrast mapping......Page 103
7.5 Physical-property-orientated coordinate transformation and tasselled cap transformation......Page 104
7.6.1 Review of Chavez et al.’s and Sheffield’s methods......Page 107
7.7 Remarks......Page 108
Questions......Page 109
8.1.2 Supervised classification......Page 110
8.2.1 Iterative clustering algorithms......Page 111
8.2.2 Feature space iterative clustering......Page 112
8.2.3 Seed selection......Page 113
8.2.4 Cluster splitting along PC1......Page 114
8.3.2 Spectral angle mapping classification......Page 115
8.4.1 Box classifier......Page 116
8.4.4 *Optimal multiple point reassignment......Page 117
8.5.1 Class smoothing process......Page 118
8.5.2 Classification accuracy assessment......Page 119
Questions......Page 121
9.1.1 Platform flight coordinates, sensor status and imaging geometry......Page 124
9.1.2 Earth rotation and curvature......Page 126
9.2 Polynomial deformation model and image warping co-registration......Page 127
9.2.1 Derivation of deformation model......Page 128
9.2.2 Pixel DN resampling......Page 129
9.3.2 *Towards automatic GCP selection......Page 130
9.4.1 Basics of phase correlation......Page 132
9.4.2 Basic scheme of pixel-to-pixel image co-registration......Page 133
9.4.3 The median shift propagation technique......Page 134
9.4.4 Summary of the refined pixel-to-pixel image co-registration and assessment......Page 136
9.5 Summary......Page 137
Questions......Page 138
10.1 The principle of a radar interferometer......Page 140
10.2 Radar interferogram and DEM......Page 142
10.3 Differential InSAR and deformation measurement......Page 144
10.4 Multi-temporal coherence image and random change detection......Page 146
10.5 Spatial decorrelation and ratio coherence technique......Page 148
10.7 Summary......Page 151
Questions......Page 153
Part Two: Geographical Information Systems......Page 154
11.1 Introduction......Page 156
11.3 GIS, cartography and thematic mapping......Page 157
11.4 Standards, interoperability and metadata......Page 158
11.5 GIS and the Internet......Page 159
12.2 How are spatial data different from other digital data?......Page 160
12.3 Attributes and measurement scales......Page 161
12.5.1 Data quantization and storage......Page 162
12.5.3 Representing spatial relationships......Page 164
12.5.4 The effect of resolution......Page 165
12.6 Vector data......Page 166
12.6.1 Representing logical relationships......Page 167
12.6.2 Extending the vector data model......Page 172
12.6.3 Representing surfaces......Page 174
12.7 Conversion between data models and structures......Page 176
12.7.1 Vector to raster conversion (rasterization)......Page 177
12.7.2 Raster to vector conversion (vectorization)......Page 179
12.8 Summary......Page 180
Questions......Page 181
13.2 Datums and projections......Page 182
13.2.1 Describing and measuring the Earth......Page 183
13.2.2 Measuring height: the geoid......Page 184
13.2.4 Datums......Page 185
13.2.5 Geometric distortions and projection models......Page 186
13.2.6 Major map projections......Page 188
13.2.7 Projection specification......Page 191
13.3 How coordinate information is stored and accessed......Page 192
13.4 Selecting appropriate coordinate systems......Page 193
Questions......Page 194
14.1 Introducing operations on spatial data......Page 196
14.2.1 Working with null data......Page 197
14.2.3 Other types of operator......Page 198
14.3.1 Primary operations......Page 200
14.3.2 Unary operations......Page 201
14.3.3 Binary operations......Page 203
14.4.1 Local neighbourhood......Page 204
14.4.2 Extended neighbourhood......Page 210
14.5 Vector equivalents to raster map algebra......Page 211
14.6 Summary......Page 213
Questions......Page 214
15.1 Introduction......Page 216
15.2.2 Spatial autocorrelation......Page 217
15.2.3 Variograms......Page 218
15.2.4 Underlying trends and natural barriers......Page 219
15.3.1 Selecting sample size......Page 220
15.3.3 Deterministic interpolators......Page 221
15.3.4 Stochastic Interpolators......Page 226
Questions......Page 228
16.2.1 Digital Elevation Models......Page 230
16.2.2 Vector surfaces and objects......Page 233
16.3 Visualizing surfaces......Page 234
16.3.1 Visualizing in two dimensions......Page 235
16.3.2 Visualizing in three dimensions......Page 237
16.4.1 Slope: gradient and aspect......Page 239
16.4.2 Curvature......Page 241
16.4.3 Surface topology: drainage networks and watersheds......Page 244
16.4.4 Viewshed......Page 245
16.4.5 Calculating volume......Page 247
Questions......Page 248
17.2 Decision support......Page 250
17.3 Uncertainty......Page 251
17.3.2 Threshold uncertainty......Page 252
17.4 Risk and hazard......Page 253
17.5.1 Error assessment (criterion uncertainty)......Page 254
17.5.3 Multi-criteria decision making (decision rule uncertainty)......Page 255
17.5.4 Error propagation and sensitivity analysis (decision rule uncertainty)......Page 256
17.5.5 Result validation (decision rule uncertainty)......Page 257
Questions......Page 258
18.1 Introduction......Page 260
18.2.2 Data-driven approach (empirical)......Page 261
18.3 Evaluation criteria......Page 262
18.4.1 Rating......Page 263
18.4.3 Pairwise comparison......Page 264
18.5.2 Index-overlay and algebraic combination......Page 267
18.5.3 Weights of evidence modelling based on bayesian probability theory......Page 268
18.5.4 Belief and Dempster–Shafer theory......Page 270
18.5.5 Weighted factors in linear combination......Page 271
18.5.6 Fuzzy logic......Page 273
18.5.7 Vectorial fuzzy modelling......Page 275
Questions......Page 277
Part Three: Remote Sensing Applications......Page 278
19 Image Processing and GIS Operation Strategy......Page 280
19.1 General image processing strategy......Page 281
19.1.1 Preparation of basic working dataset......Page 282
19.1.2 Image processing......Page 285
19.1.3 Image interpretation and map composition......Page 289
19.2 Remote-sensing-based GIS projects: from images to thematic mapping......Page 290
19.3.1 Background information......Page 291
19.3.3 Data capture and image interpretation......Page 293
19.3.4 Map composition......Page 297
19.4 Summary......Page 298
Questions......Page 299
20.1.1 Data Preparation and general visualization......Page 300
20.1.2 Gypsum enhancement and extraction based on spectral analysis......Page 302
20.1.3 Gypsum quarry changes during 1984–2000......Page 303
20.2.1 Image datasets and data preparation......Page 306
20.2.2 ASTER image processing and analysis for regional prospectivity......Page 307
20.2.3 ATM image processing and analysis for target extraction......Page 311
20.3.1 Introduction......Page 315
20.3.2 Data preparation......Page 316
20.3.3 Highlighting vegetation......Page 317
20.3.4 Highlighting plastic greenhouses......Page 319
20.3.5 Identifying change between different dates of observation......Page 321
20.4.1 Introduction......Page 323
20.4.2 Geological and hydrological setting......Page 324
20.4.3 Case study objectives......Page 325
20.4.4 Land use and vegetation......Page 326
20.4.5 Lithological enhancement and discrimination......Page 329
20.4.6 Structural enhancement and interpretation......Page 332
20.4.7 Summary......Page 337
Questions......Page 339
References......Page 340
21.1.1 Introduction......Page 342
21.1.3 Methodology......Page 343
21.1.4 Data processing......Page 345
21.1.5 Interpretation of regional vegetation changes......Page 347
21.1.6 Summary......Page 351
21.2.2 The study area......Page 353
21.2.3 Methodology: multi-variable elimination and characterization......Page 355
21.2.4 Terrestrial information extraction......Page 358
21.2.5 DEM and topographic information extraction......Page 363
21.2.6 Landslide hazard mapping......Page 366
21.2.7 Summary......Page 368
21.3.1 Introduction......Page 369
21.3.2 The study area......Page 371
21.3.3 A holistic GIS-based approach to landslide hazard assessment......Page 373
21.3.4 Summary......Page 376
21.4.1 The study area......Page 378
21.4.2 Coherence image processing and evaluation......Page 379
21.4.3 Image visualization and interpretation for change detection......Page 380
References......Page 385
22.1.1 Introduction and objectives......Page 390
22.1.2 Area description......Page 391
22.1.3 Litho-tectonic context – why the project’s concept works......Page 392
22.1.5 Data preparation......Page 393
22.1.6 Multi-criteria spatial modelling......Page 400
22.1.7 Summary......Page 403
22.2.1 Introduction......Page 405
22.2.2 Data preparation......Page 406
22.2.3 Preliminary geological enhancements and target area identification......Page 407
22.2.4 Discrimination potential aquifer lithologies using ASTER spectral indices......Page 409
References......Page 416
Part Four: Summary......Page 418
23.1 Image processing......Page 420
23.2 Geographical information systems......Page 423
23.3 Final remarks......Page 426
A.1 Multi-spectral sensing......Page 428
A.2.1 Digital camera......Page 432
A.2.2 Across-track mechanical scanner......Page 433
A.2.3 Along-track push-broom scanner......Page 434
A.3 Thermal sensing and thermal infrared sensors......Page 435
A.4 Hyperspectral sensors (imaging spectrometers)......Page 436
A.5 Passive microwave sensors......Page 437
A.6 Active sensing: SAR imaging systems......Page 438
B.1 Software – proprietary, low cost and free (shareware)......Page 444
B.3 Data sources including online satellite imagery from major suppliers, DEM data plus GIS maps and data of all kinds......Page 445
Image processing......Page 448
Part One References and further reading......Page 449
Part Two References and further reading......Page 452
Index......Page 456