Image Processing and GIS for Remote Sensing
Wiley-Blackwell (Verlag)
978-1-118-72420-0 (ISBN)
The book conveys in-depth knowledge of image processing and GIS techniques in an accessible and comprehensive manner, with clear explanations and conceptual illustrations used throughout to enhance student learning. The understanding of key concepts is always emphasised with minimal assumption of prior mathematical experience.
The book is heavily based on the authors’ own research. Many of the author-designed image processing techniques are popular around the world. For instance, the SFIM technique has long been adopted by ASTRIUM for mass-production of their standard “Pan-sharpen” imagery data. The new edition also includes a completely new chapter on subpixel technology and new case studies, based on their recent research.
Jian Guo Liu received a Ph.D. in 1991 in remote sensing and image processing from Imperial College London, UK and an M.Sc. in 1982 in remote sensing and geology from China University of Geosciences, Beijing, China. He is a Reader in remote sensing in the Department of Earth Science and Engineering, Imperial College London. His current research activities include: sub-pixel technology for image registration, DEM generation and change detection; image processing techniques for data fusion, filtering and InSAR; and GIS multi-data modelling for geohazard studies. Philippa J Mason completed a BSc in Geology at Southampton University in 1987, an MSc in Remote Sensing at University College London in 1993 and a PhD in 1998 at Imperial College London. She is a lecturer in remote sensing & GIS at Imperial College London and a consultant in geological remote sensing and image interpretation. Her research interests include the application of geospatial sciences to geohazards, tectonic geomorphology, spectral geology and mineral exploration.
Overview of the Book xi
Part I Image processing
1 Digital image and display 3
1.1 What is a digital image? 3
1.2 Digital image display 4
1.3 Some key points 8
1.4 Questions 8
2 Point operations (contrast enhancement) 9
2.1 Histogram modification and lookup table 9
2.2 Linear contrast enhancement (LCE) 11
2.3 Logarithmic and exponential contrast enhancement 13
2.4 Histogram equalisation (HE) 14
2.5 Histogram matching (HM) and Gaussian stretch 15
2.6 Balance contrast enhancement technique (BCET) 16
2.7 Clipping in contrast enhancement 18
2.8 Tips for interactive contrast enhancement 18
2.9 Questions 19
3 Algebraic operations (multi‐image point operations) 21
3.1 Image addition 21
3.2 Image subtraction (differencing) 22
3.3 Image multiplication 22
3.4 Image division (ratio) 22
3.5 Index derivation and supervised enhancement 26
3.6 Standardization and logarithmic residual 29
3.7 Simulated reflectance 29
3.8 Summary 33
3.9 Questions 34
4 Filtering and neighbourhood processing 35
4.1 FT: Understanding filtering in image frequency 35
4.2 Concepts of convolution for image filtering 37
4.3 Low pass filters (smoothing) 38
4.4 High pass filters (edge enhancement) 42
4.5 Local contrast enhancement 45
4.6 FFT selective and adaptive filtering 46
4.7 Summary 52
4.8 Questions 52
5 RGB‐IHS transformation 55
5.1 Colour co‐ordinate transformation 55
5.2 IHS de‐correlation stretch 57
5.3 Direct de‐correlation stretch technique 58
5.4 Hue RGB colour composites 60
5.5 Derivation of RGB‐IHS and IHS‐RGB transformation based on 3D geometry of the RGB colour cube 63
5.6 Mathematical proof of DDS and its properties 65
5.7 Summary 67
5.8 Questions 67
6 Image fusion techniques 69
6.1 RGB‐IHS transformation as a tool for data fusion 69
6.2 Brovey transform (intensity modulation) 71
6.3 Smoothing filter‐based intensity modulation 71
6.4 Summary 75
6.5 Questions 75
7 Principal component analysis 77
7.1 Principle of the PCA 77
7.2 PC images and PC colour composition 79
7.3 Selective PCA for PC colour composition 82
7.4 De‐correlation stretch 84
7.5 Physical property orientated coordinate transformation and tasselled cap transformation 85
7.6 Statistical methods for band selection 87
7.7 Remarks 88
7.8 Questions 89
8 Image classification 91
8.1 Approaches of statistical classification 91
8.2 Unsupervised classification (iterative clustering) 92
8.3 Supervised classification 96
8.4 Decision rules: Dissimilarity functions 97
8.5 Post‐classification processing: Smoothing and accuracy assessment 98
8.6 Summary 101
8.7 Questions 101
9 Image geometric operations 103
9.1 Image geometric deformation 103
9.2 Polynomial deformation model and image warping co‐registration 106
9.3 GCP selection and automation of image co‐registration 109
9.4 Summary 110
9.5 Questions 110
10 Introduction to interferometric synthetic aperture radar technique 113
10.1 The principle of a radar interferometer 113
10.2 Radar interferogram and DEM 115
10.3 Differential InSAR and deformation measurement 117
10.4 Multi‐temporal coherence image and random change detection 119
10.5 Spatial de‐correlation and ratio coherence technique 121
10.6 Fringe smoothing filter 123
10.7 Summary 124
10.8 Questions 125
11 Sub‐pixel technology and its applications 127
11.1 Phase correlation algorithm 127
11.2 PC scanning for pixel‐wise disparity estimation 132
11.3 Pixel‐wise image co‐registration 134
11.4 Very narrow‐baseline stereo matching and 3D data generation 139
11.5 Ground motion/deformation detection and estimation 143
11.6 Summary 146
Part II Geographical information systems
12 Geographical information systems 151
12.1 Introduction 151
12.2 Software tools 152
12.3 GIS cartography and thematic mapping 152
12.4 Standards, inter‐operability and metadata 153
12.5 GIS and the internet 154
13 Data models and structures 155
13.1 Introducing spatial data in representing geographic features 155
13.2 How are spatial data different from other digital data? 155
13.3 Attributes and measurement scales 156
13.4 Fundamental data structures 156
13.5 Raster data 157
13.6 Vector data 161
13.7 Data conversion between models and structures 171
13.8 Summary 174
13.9 Questions 175
14 Defining a coordinate space 177
14.1 Introduction 177
14.2 Datums and projections 177
14.3 How coordinate information is stored and accessed 188
14.4 Selecting appropriate coordinate systems 189
14.5 Questions 189
15 Operations 191
15.1 Introducing operations on spatial data 191
15.2 Map algebra concepts 192
15.3 Local operations 194
15.4 Neighbourhood operations 199
15.5 Vector equivalents to raster map algebra 206
15.6 Automating GIS functions 209
15.7 Summary 209
15.8 Questions 210
16 Extracting information from point data: Geostatistics 211
16.1 Introduction 211
16.2 Understanding the data 211
16.3 Interpolation 214
16.4 Summary 224
16.5 Questions 225
17 Representing and exploiting surfaces 227
17.1 Introduction 227
17.2 Sources and uses of surface data 227
17.3 Visualising surfaces 230
17.4 Extracting surface parameters 236
17.5 Summary 245
17.6 Questions 246
18 Decision support and uncertainty 247
18.1 Introduction 247
18.2 Decision support 247
18.3 Uncertainty 248
18.4 Risk and hazard 250
18.5 Dealing with uncertainty in GIS‐based spatial analysis 250
18.6 Summary 254
18.7 Questions 255
19 Complex problems and multi‐criterion evaluation 257
19.1 Introduction 257
19.2 Different approaches and models 258
19.3 Evaluation criteria 259
19.4 Deriving weighting coefficients 260
19.5 Multi‐criterion combination methods 263
19.6 Summary 272
19.7 Questions 272
Part III Remote sensing applications
20 Image processing and GIS operation strategy 275
20.1 General image processing strategy 276
20.2 Remote sensing‐based GIS projects: From images to thematic mapping 284
20.3 An example of thematic mapping based on optimal visualisation and interpretation of multi‐spectral satellite imagery 284
20.4 Summary 292
21 Thematic teaching case studies in SE Spain 293
21.1 Thematic information extraction (1): Gypsum natural outcrop mapping and quarry change assessment 293
21.2 Thematic information extraction (2): Spectral enhancement and mineral mapping of epithermal gold alteration and iron‐ore deposits in ferroan dolomite 299
21.3 Remote sensing and GIS: Evaluating vegetation and landuse change in the Nijar Basin, SE Spain 308
21.4 Applied remote sensing and GIS: A combined interpretive tool for regional tectonics, drainage and water resources in the Andarax basin 318
22 Research case studies 335
22.1 Vegetation change in the Three Parallel Rivers region, Yunnan Province, China 335
22.2 GIS modelling of earthquake damage zones using satellite imagery and digital elevation model (DEM) data 345
22.3 Predicting landslides using fuzzy geohazard mapping: An example from Piemonte, north‐west Italy 369
22.4 Land surface change detection in a desert area in Algeria using multi‐temporal ERS SAR coherence images 380
23 Industrial case studies 389
23.1 Multi‐criteria assessment of mineral prospectivity in SE Greenland 389
23.2 Water resource exploration in Somalia 405
Part IV Summary
24 Concluding remarks 419
24.1 Image processing 419
24.2 Geographic Information Systems 422
24.3 Final remarks 425
Appendix A Imaging sensor systems and remote sensing satellites 427
A.1 Multi‐spectral sensing 427
A.2 Broadband multi‐spectral sensors 431
A.3 Thermal sensing and TIR sensors 434
A.4 Hyperspectral sensors (imaging spectrometers) 434
A.5 Passive microwave sensors 436
A.6 Active sensing: SAR imaging systems 437
Appendix B Online resources for information software and data 441
B.1 Software – proprietary, low cost and free (shareware) 441
B.2 Information and technical information on standards, best practice, formats, techniques and various publications 441
B.3 Data sources including online satellite imagery from major suppliers, DEM data plus GIS maps and data of all kinds 442
References 443
Index 451
| Erscheinungsdatum | 22.03.2016 |
|---|---|
| Verlagsort | Hoboken |
| Sprache | englisch |
| Maße | 193 x 249 mm |
| Gewicht | 1179 g |
| Themenwelt | Naturwissenschaften ► Geowissenschaften ► Geografie / Kartografie |
| Naturwissenschaften ► Geowissenschaften ► Geologie | |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-118-72420-8 / 1118724208 |
| ISBN-13 | 978-1-118-72420-0 / 9781118724200 |
| Zustand | Neuware |
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