Essential Image Processing and GIS for Remote Sensing

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.В 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.В В 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 "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. This book pinpoints the overlap between the individual subjects, providing a summary of essential techniques and a selection of key case studies in a variety of application areas." "The book conveys in-depth knowledge of image processing and GIS in an accessible manner, with clear explanations and conceptual illustrations used throughout to enhance student understanding. The understanding of key concepts is emphasised throughout with minimal assumption of prior mathematical experience."--Page 4 de la couverture "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. This book pinpoints the overlap between the individual subjects, providing a summary of essential techniques and a selection of key case studies in a variety of application areas." "The book conveys in-depth knowledge of image processing and GIS in an accessible manner, with clear explanations and conceptual illustrations used throughout to enhance student understanding. The understanding of key concepts is emphasised throughout with minimal assumption of prior mathematical experience."--Jacket