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Computer Processing of Remotely-Sensed Images: An Introduction 4th edition [Minkštas viršelis]

4.20/5 (10 ratings by Goodreads)
(University of Nottingham, England), (Boston University)
  • Formatas: Paperback / softback, 464 pages, aukštis x plotis x storis: 277x211x25 mm, weight: 1134 g
  • Išleidimo metai: 31-Dec-2010
  • Leidėjas: John Wiley & Sons Inc
  • ISBN-10: 0470742380
  • ISBN-13: 9780470742389
Kitos knygos pagal šią temą:
Computer Processing of Remotely-Sensed Images: An Introduction 4th editionDidesnis paveikslėlis
  • Formatas: Paperback / softback, 464 pages, aukštis x plotis x storis: 277x211x25 mm, weight: 1134 g
  • Išleidimo metai: 31-Dec-2010
  • Leidėjas: John Wiley & Sons Inc
  • ISBN-10: 0470742380
  • ISBN-13: 9780470742389
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9780470742389.html
Raktažodžiai:
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 http://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.

Recenzijos

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(28)
1.1 Introduction
1(3)
1.2 Electromagnetic Radiation and Its Properties
4(13)
1.2.1 Terminology
4(2)
1.2.2 Nature of Electromagnetic Radiation
6(1)
1.2.3 The Electromagnetic Spectrum
6(7)
1.2.4 Sources of Electromagnetic Radiation
13(2)
1.2.5 Interactions with the Earth's Atmosphere
15(2)
1.3 Interaction with Earth-Surface Materials
17(9)
1.3.1 Introduction
17(2)
1.3.2 Spectral Reflectance of Earth Surface Materials
19(7)
1.4 Summary
26(3)
2 Remote Sensing Platforms and Sensors
29(38)
2.1 Introduction
29(2)
2.2 Characteristics of Imaging Remote Sensing Instruments
31(8)
2.2.1 Spatial Resolution
32(3)
2.2.2 Spectral Resolution
35(2)
2.2.3 Radiometric Resolution
37(2)
2.3 Optical, Near-infrared and Thermal Imaging Sensors
39(19)
2.3.1 Along-Track Scanning Radiometer (ATSR)
40(1)
2.3.2 Advanced Very High Resolution Radiometer (AVHRR) and NPOESS VIIRS
41(1)
2.3.3 MODIS
42(1)
2.3.4 Ocean Observing Instruments
42(3)
2.3.5 IRS LISS
45(1)
2.3.6 Landsat Instruments
46(2)
2.3.7 SPOT Sensors
48(5)
2.3.8 Advanced Spaceborrie Thermal Emission and Reflection Radiometer (ASTER)
53(1)
2.3.9 High-Resolution Commercial and Small Satellite Systems
53(5)
2.4 Microwave Imaging Sensors
58(8)
2.4.1 European Space Agency Synthetic Aperture Spaceborne Radars
62(1)
2.4.2 Radarsat
63(1)
2.4.3 TerraSAR-X and COSMO/Skymed
64(1)
2.4.4 ALOS PALSAR
65(1)
2.5 Summary
66(1)
3 Hardware and Software Aspects of Digital Image Processing
67(20)
3.1 Introduction
67(1)
3.2 Properties of Digital Remote Sensing Data
67(13)
3.2.1 Digital Data
67(7)
3.2.2 Data Formats
74(4)
3.2.3 System Processing
78(2)
3.3 Numerical Analysis and Software Accuracy
80(3)
3.4 Some Remarks on Statistics
83(1)
3.5 Summary
84(3)
4 Preprocessing of Remotely-Sensed Data
87(38)
4.1 Introduction
87(2)
4.2 Cosmetic Operations
89(5)
4.2.1 Missing Scan Lines
89(1)
4.2.2 Destriping Methods
90(4)
4.3 Geometric Correction and Registration
94(18)
4.3.1 Orbital Geometry Model
96(2)
4.3.2 Transformation Based on Ground Control Points
98(10)
4.3.3 Resampling Procedures
108(3)
4.3.4 Image Registration
111(1)
4.3.5 Other Geometric Correction Methods
111(1)
4.4 Atmospheric Correction
112(4)
4.4.1 Background
112(2)
4.4.2 Image-Based Methods
114(1)
4.4.3 Radiative Transfer Models
115(1)
4.4.4 Empirical Line Method
115(1)
4.5 Illumination and View Angle Effects
116(1)
4.6 Sensor Calibration
117(4)
4.7 Terrain Effects
121(2)
4.8 Summary
123(2)
5 Image Enhancement Techniques
125(22)
5.1 Introduction
125(1)
5.2 Human Visual System
126(2)
5.3 Contrast Enhancement
128(12)
5.3.1 Linear Contrast Stretch
128(1)
5.3.2 Histogram Equalization
129(9)
5.3.3 Gaussian Stretch
138(2)
5.4 Pseudocolour Enhancement
140(5)
5.4.1 Density Slicing
140(4)
5.4.2 Pseudocolour Transform
144(1)
5.5 Summary
145(2)
6 Image Transforms
147(56)
6.1 Introduction
147(1)
6.2 Arithmetic Operations
148(8)
6.2.1 Image Addition
148(1)
6.2.2 Image Subtraction
149(1)
6.2.3 Image Multiplication
150(2)
6.2.4 Image Division and Vegetation Indices
152(4)
6.3 Empirically Based Image Transforms
156(4)
6.3.1 Perpendicular Vegetation Index
156(1)
6.3.2 Tasselled Cap (Kauth-Thomas) Transformation
157(3)
6.4 Principal Components Analysis
160(11)
6.4.1 Standard Principal Components Analysis
160(8)
6.4.2 Noise-Adjusted PCA
168(1)
6.4.3 Decorrelation Stretch
169(2)
6.5 Hue-Saturation-Intensity (HSI) Transform
171(1)
6.6 The Discrete Fourier Transform
172(6)
6.6.1 Introduction
172(1)
6.6.2 Two-Dimensional Fourier Transform
173(5)
6.6.3 Applications of the Fourier Transform
178(1)
6.7 The Discrete Wavelet Transform
178(9)
6.7.1 Introduction
178(1)
6.7.2 The One-Dimensional Discrete Wavelet Transform
179(7)
6.7.3 The Two-Dimensional Discrete Wavelet Transform
186(1)
6.8 Change Detection
187(9)
6.8.1 Introduction
187(1)
6.8.2 NDVI Difference Image
188(1)
6.8.3 PCA
188(4)
6.8.4 Canonical Correlation Change Analysis
192(3)
6.8.5 Summary
195(1)
6.9 Image Fusion
196(6)
6.9.1 Introduction
196(2)
6.9.2 HSI Algorithm
198(1)
6.9.3 PCA
198(1)
6.9.4 Gram-Schmidt Orthogonalization
198(1)
6.9.5 Wavelet-Based Methods
198(1)
6.9.6 Evaluation - Subjective Methods
199(1)
6.9.7 Evaluation - Objective Methods
200(2)
6.10 Summary
202(1)
7 Filtering Techniques
203(26)
7.1 Introduction
203(1)
7.2 Spatial Domain Low-Pass (Smoothing) Filters
204(10)
7.2.1 Moving Average Filter
204(4)
7.2.2 Median Filter
208(1)
7.2.3 Adaptive Filters
209(5)
7.3 Spatial Domain High-Pass (Sharpening) Filters
214(5)
7.3.1 Image Subtraction Method
214(1)
7.3.2 Derivative-Based Methods
215(4)
7.4 Spatial Domain Edge Detectors
219(2)
7.5 Frequency Domain Filters
221(6)
7.6 Summary
227(2)
8 Classification
229(56)
8.1 Introduction
229(2)
8.2 Geometrical Basis of Classification
231(2)
8.3 Unsupervised Classification
233(7)
8.3.1 The k-Means Algorithm
233(1)
8.3.2 ISODATA
234(5)
8.3.3 A Modified k-Means Algorithm
239(1)
8.4 Supervised Classification
240(14)
8.4.1 Training Samples
240(5)
8.4.2 Statistical Classifiers
245(5)
8.4.3 Neural Classifiers
250(4)
8.5 Subpixel Classification Techniques
254(13)
8.5.1 The Linear Mixture Model
258(5)
8.5.2 Spectral Angle Mapping
263(2)
8.5.3 ICA
265(1)
8.5.4 Fuzzy Classifiers
265(2)
8.6 More Advanced Approaches to Image Classification
267(5)
8.6.1 Support Vector Machines
267(2)
8.6.2 Decision Trees
269(1)
8.6.3 Other Methods of Classification
270(2)
8.7 Incorporation of Non-spectral Features
272(4)
8.7.1 Texture
272(3)
8.7.2 Use of External Data
275(1)
8.8 Contextual Information
276(1)
8.9 Feature Selection
277(3)
8.10 Classification Accuracy
280(3)
8.11 Summary
283(2)
9 Advanced Topics
285(40)
9.1 Introduction
285(1)
9.2 SAR Interferometry
285(9)
9.2.1 Basic Principles
285(5)
9.2.2 Interferometric Processing
290(2)
9.2.3 Problems in SAR Interferometry
292(1)
9.2.4 Applications of SAR Interferometry
293(1)
9.3 Imaging Spectroscopy
294(21)
9.3.1 Introduction
294(6)
9.3.2 Processing Imaging Spectroscopy Data
300(15)
9.4 Lidar
315(8)
9.4.1 Introduction
315(3)
9.4.2 Lidar Details
318(3)
9.4.3 Lidar Applications
321(2)
9.5 Summary
323(2)
10 Environmental Geographical Information Systems: A Remote Sensing Perspective
325(52)
10.1 Introduction
325(3)
10.1.1 Definitions
326(1)
10.1.2 The Synergy between Remote Sensing and GIS
327(1)
10.2 Data Models, Data Structures and File Formats
328(4)
10.2.1 Spatial Data Models
328(1)
10.2.2 Data Structures
329(2)
10.2.3 File Formats
331(1)
10.2.4 Raster to Vector and Vector to Raster Conversion
331(1)
10.3 Geodata Processing
332(1)
10.3.1 Buffering
332(1)
10.3.2 Overlay
332(1)
10.4 Locational Analysis
333(2)
10.4.1 Slope and Aspect
333(1)
10.4.2 Proximity Analysis
334(1)
10.4.3 Contiguity and Connectivity
334(1)
10.5 Spatial Analysis
335(3)
10.5.1 Point Patterns and Interpolation
335(2)
10.5.2 Relating Field and Remotely-Sensed Measurements: Statistical Analysis
337(1)
10.5.3 Exploratory Data Analysis and Data Mining
338(1)
10.6 Environmental Modelling
338(2)
10.7 Visualization
340(5)
10.8 Multicriteria Decision Analysis of Groundwater Recharge Zones
345(10)
10.8.1 Introduction
345(1)
10.8.2 Data Characteristics
346(5)
10.8.3 Multicriteria Decision Analysis
351(1)
10.8.4 Evaluation
352(1)
10.8.5 Conclusions
352(3)
10.9 Assessing Flash Flood Hazards by Classifying Wadi Deposits in Arid Environments
355(10)
10.9.1 Introduction
355(1)
10.9.2 Water Resources in Arid Lands
355(1)
10.9.3 Case Study from the Sinai Peninsula, Egypt
356(1)
10.9.4 Optical and Microwave Data Fusion
357(3)
10.9.5 Classification of Wadi Deposits
360(1)
10.9.6 Correlation of Classification Results with Geology and Terrain Data
360(5)
10.9.7 Conclusions
365(1)
10.10 Remote Sensing and GIS in Archaeological Studies
365(12)
10.10.1 Introduction
365(1)
10.10.2 Homul (Guatemala) Case Study
365(6)
10.10.3 Aksum (Ethiopia) Case Study
371(3)
10.10.4 Conclusions
374(3)
Appendix A Accessing MIPS 377(2)
Appendix B Getting Started with MIPS 379(2)
Appendix C Description of Sample Image Datasets 381(4)
Appendix D Acronyms and Abbreviations 385(4)
References 389(40)
Index 429
Paul M. Mather is the author of Computer Processing of Remotely-Sensed Images: An Introduction, 4th Edition, published by Wiley. Magaly Koch is the author of Computer Processing of Remotely-Sensed Images: An Introduction, 4th Edition, published by Wiley.