Muutke küpsiste eelistusi

Computer Processing of RemotelySensed Images An Introduction 4e [Other digital carrier]

(University of Nottingham, England), (Boston University)
  • Formaat: Other digital carrier, 464 pages, kõrgus x laius x paksus: 281x218x23 mm, kaal: 1288 g
  • Ilmumisaeg: 29-Dec-2010
  • Kirjastus: Wiley-Blackwell
  • ISBN-10: 047066651X
  • ISBN-13: 9780470666517
Teised raamatud teemal:
Computer Processing of RemotelySensed Images An Introduction 4e
  • Formaat: Other digital carrier, 464 pages, kõrgus x laius x paksus: 281x218x23 mm, kaal: 1288 g
  • Ilmumisaeg: 29-Dec-2010
  • Kirjastus: Wiley-Blackwell
  • ISBN-10: 047066651X
  • ISBN-13: 9780470666517
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780470666517.html
Märksõnad:
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:

  • A website at www.wiley.com/go/mather4 that provides access to an updated and expanded version of the MIPS image processing software for Microsoft Windows, PowerPoint slideshows of the figures from each chapter, and case studies, including full data sets,
  • Includes new chapter on Remote Sensing and Environmental GIS that provides insights into the ways in which remotely-sensed data can be used synergistically with other spatial data sets, including hydrogeological and archaeological applications,
  • New section on image processing from a computer science perspective presented in a non-technical way, including some remarks on statistics,
  • New material on image transforms, including the analysis of temporal change and data fusion techniques,
  • New material on image classification including decision trees, support vector machines and independent components analysis, and
  • Now in full colour throughout.

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.

Arvustused

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 First Edition xi 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