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Fundamentals of Satellite Remote Sensing: An Environmental Approach, Second Edition 2nd New edition [Kietas viršelis]

4.44/5 (10 ratings by Goodreads)
(Universidad de Alcala, Alcala de Henares, Spain)
  • Formatas: Hardback, 468 pages, aukštis x plotis: 235x156 mm, weight: 975 g, N/A; 39 Tables, color; 267 Illustrations, color
  • Išleidimo metai: 03-Mar-2016
  • Leidėjas: Productivity Press
  • ISBN-10: 1498728057
  • ISBN-13: 9781498728058
  • Formatas: Hardback, 468 pages, aukštis x plotis: 235x156 mm, weight: 975 g, N/A; 39 Tables, color; 267 Illustrations, color
  • Išleidimo metai: 03-Mar-2016
  • Leidėjas: Productivity Press
  • ISBN-10: 1498728057
  • ISBN-13: 9781498728058
Fundamentals of Satellite Remote Sensing: An Environmental Approach, Second Edition is a definitive guide to remote sensing systems that focuses on satellite-based remote sensing tools and methods for space-based Earth observation (EO). It presents the advantages of using remote sensing data for studying and monitoring the planet, and emphasizes concepts that make the best use of satellite data.



The book begins with an introduction to the basic processes that ensure the acquisition of space-borne imagery and provides an overview of the main satellite observation systems. It then describes visual and digital image analysis, highlights various interpretation techniques, and outlines their applications to science and management. The latter part of the book covers the integration of remote sensing with GIS for environmental analysis.









Based on the first English version published in 2010, this latest edition has been written to reflect a global audience, and factors in international debates and legal issues surrounding EO, as well as future developments and trends.









New in the Second Edition:





















Includes additional illustrations now in full color Uses sample images acquired from different ecosystems at different spatial resolutions to illustrate different interpretation techniques Updates information on recent satellite missions (Landsat-8, Sentinel-2, hyperspectral and hyperspatial programs) Covers near-ground missions (including UAV) and ground sensors (spectro-radiometers, cameras, LIDAR, etc.) to support EO analysis Offers analysis of image spatial properties Presents material on visual analysis, time series analysis, and data fusion Provides examples of EO data that cover different environmental problems, with particular relevance to global observation









Fundamentals of Satellite Remote Sensing: An Environmental Approach, Second Edition details the tools that provide global, recurrent, and comprehensive views of the processes affecting the Earth and is a must-have for researchers, academics, students, and professionals involved in the field of environmental science.

Recenzijos

" this book comprehensively covers the fundamentals of satellite remote sensing, including radiation physics, atmospheric correction, spectral signatures of ground targets, sensors, image processing and analysis, and information retrieval. It also includes enlightening chapters on the validation of satellite-retrieved information and the integration of remote sensing data with geographical information systems. The breadth and depth of this book benefit greatly from the authors wide range of research experience in various fields of remote sensing applications. The text is well written and easy to follow, and the figures are well crafted and informative. It can be an ideal choice as a textbook for an introductory course on satellite remote sensing of the land surface, and it can also be a dependable desktop copy for remote sensing scientists and professionals." Dr. Jing M. Chen, University of Toronto, Canada













" one of the most easy-to-follow, best-organised and accessible overviews of the topic. The inclusion in this second edition of ample schematic examples and conceptual colour illustrations is very helpful in explaining the hard-to-grasp terminology that, more often than not, remote sensing textbooks fail to disentangle. It is an excellent resource for students and practitioners alike." Dr. Elias Symeonakis, School of Science and the Environment, Manchester Metropolitan University, UK











"I value this book highly because it deals with the whole remote sensing chain in a systematic way. a comprehensive introduction into the field of remote sensing. It covers all relevant aspects of the remote observation of the Earths surface " Dr. Jan Clevers, Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, the Netherlands









" It is an absolutely essential read for undergraduate and postgraduate students who want to get on top of the basics in image processing and classification." Kevin Tansey, University of Leicester, UK





" ideal for an introductory course on remote sensing." Viviana Maggioni, George Mason University, Fairfax, Virginia, USA



"a valuable book providing a thorough introduction into the field of earth observation, which will be very valuable as a book of reference for many years. It can be an ideal choice as a textbook for an introductory course on satellite remote sensing of the land surface. The text is well written and easy to follow, and as such highly recommended for students at the undergraduate level." International Journal of Applied Earth Observation and Geoinformation, May 2016



"a good textbook for teaching, a useful source for post-graduate researchers, and a valuable reference source for managers and practitioners."

International Journal of Digital Earth, July 2016



"I think that this book is an extremely informative and useful resource for students, instructors, researchers, and professionals in the geospatial field and in ecology. Not only does the book discuss issues in a concise and clear way, but the graphics and imagery used are very informative and help to clarify potentially confusing concepts. The bibliography is particularly helpful as it allows the reader to easily delve into detail on a certain topic. I recommend this book highly as an addition to any library on remote sensing." WAML Information Bulletin, November 2016



"This book is an attempt to help students and professionals become more familiar with remote sensing technology, focusing on satellite remote sensing. All remote sensing aspects are described, from the physical basis to obtain information from a distance, to the operation of platform carrying out the sensor system, to the data acquisition, storage, and interpretation. There are a multitude of airborne sensing systems. Among them, those focused on the thermal emission from the earth, centered on the short wave infrared (SWIR) and long wave infrared (LWIR), have their place in the book."QIRT Journal, December 2016



"a useful addition to more mainstream remote sensing texts." The Photogrammetric Record, March 2017



"has a good general coverage of remote sensing technology and has an excellent coverage of applications related to environmental systems." Geospatial World, March 2017



"Chuvieco provides an complete overview of satellite remote sensing containing a suitable mix of theory and interesting practical examples. The book can be considered a valuable resource for environmental practitioners considering the use of satellite remote sensing as source of information. For these readers the use of consistent example images demonstrates the power of satellite remote sensing to extract a wide range of information. This will enable readers to gain insights as to how these techniques can be applied to their problems and their parts of the world." Journal of Spatial Information Science, No 14 (2017)

Preface xv
Author xvii
Chapter 1 Introduction 1(22)
1.1 Definition and Objectives
1(3)
1.2 Historical Background
4(5)
1.3 International Space Law
9(4)
1.4 Benefits of Environmental Monitoring from Satellite Sensors
13(6)
1.4.1 Global Coverage
14(1)
1.4.2 Synoptic View
15(1)
1.4.3 Multiscale Observations
16(1)
1.4.4 Observations over the Nonvisible Regions of the Spectrum
17(1)
1.4.5 Repeat Observation
17(1)
1.4.6 Immediate Transmission
18(1)
1.4.7 Digital Format
18(1)
1.5 Sources of Information on Remote Sensing Data
19(2)
1.6 Review Questions
21(2)
Chapter 2 Physical Principles of Remote Sensing 23(46)
2.1 Fundamentals of Remote Sensing Signals
23(3)
2.2 Electromagnetic Spectrum
26(1)
2.3 Terms and Units of Measurement
27(3)
2.4 Electromagnetic Radiation Laws
30(2)
2.5 Spectral Signatures in the Solar Spectrum
32(17)
2.5.1 Introduction
32(6)
2.5.2 Vegetation Reflectance
38(4)
2.5.3 Soil Reflectance Properties
42(4)
2.5.4 Water in the Solar Spectrum
46(3)
2.6 Thermal Infrared Domain
49(4)
2.6.1 Characteristics of EM Radiation in the Thermal Infrared
49(2)
2.6.2 Thermal Properties of Vegetation
51(1)
2.6.3 Soils in the Thermal Domain
52(1)
2.6.4 Thermal Signature of Water and Snow
52(1)
2.7 Microwave Region
53(8)
2.7.1 Characteristics of Electromagnetic Radiation in the Microwave Region
53(5)
2.7.2 Characteristics of Vegetation in the Microwave Region
58(1)
2.7.3 Characteristics of Soil in the Microwave Region
59(1)
2.7.4 Water and Ice in the Microwave Region
60(1)
2.8 Atmospheric Interactions
61(5)
2.8.1 Atmospheric Absorption
63(2)
2.8.2 Atmospheric Scattering
65(1)
2.8.3 Atmospheric Emission
66(1)
2.9 Review Questions
66(3)
Chapter 3 Sensors and Remote Sensing Satellites 69(58)
3.1 Resolution of a Sensor System
69(8)
3.1.1 Spatial Resolution
70(3)
3.1.2 Spectral Resolution
73(1)
3.1.3 Radiometric Resolution
73(1)
3.1.4 Temporal Resolution
74(1)
3.1.5 Angular Resolution
75(1)
3.1.6 Relationship between Different Resolution Types
76(1)
3.2 Passive Sensors
77(8)
3.2.1 Photographic Cameras
77(4)
3.2.2 Cross-Track Scanners
81(1)
3.2.3 Along-Track (Push-Broom) Scanners
82(1)
3.2.4 Video Cameras
83(1)
3.2.5 Microwave Radiometers
83(2)
3.3 Active Sensors
85(14)
3.3.1 Radar
85(8)
3.3.2 Lidar
93(6)
3.4 Satellite Remote Sensing Missions
99(25)
3.4.1 Satellite Orbits
99(2)
3.4.2 The Landsat Program
101(3)
3.4.3 SPOT Satellites
104(2)
3.4.4 Other Medium-Resolution Optical Sensors
106(2)
3.4.5 High-Spatial-Resolution Satellites
108(3)
3.4.6 Geostationary Meteorological Satellites
111(2)
3.4.7 Polar-Orbiting Meteorological Satellites
113(4)
3.4.8 Terra—Aqua
117(3)
3.4.9 Radar Missions
120(3)
3.4.10 Programs with Hyperspectral Sensors
123(1)
3.5 Review Questions
124(3)
Chapter 4 Basis for Analyzing EO Satellite Images 127(22)
4.1 Constraints in Using Remote Sensing Data
127(4)
4.1.1 What Can Be Estimated from the EO Images
127(2)
4.1.2 Costs of Data Acquisition
129(1)
4.1.3 End-User Requirements
130(1)
4.2 Types of Interpretation
131(2)
4.2.1 Thematic Classification
132(1)
4.2.2 Generation of Biophysical Variables
132(1)
4.2.3 Change Detection
132(1)
4.2.4 Spatial Patterns
133(1)
4.3 Organization of Remote Sensing Project
133(10)
4.3.1 Description of Objectives
133(1)
4.3.2 Scale and Resolution
134(3)
4.3.3 Classification Typology
137(3)
4.3.4 Selection of Imagery
140(1)
4.3.5 Image Formats and Media
141(1)
4.3.6 Selection of Interpretation Method: Visual or Digital Processing?
141(2)
4.4 Interpretation Phase
143(2)
4.5 Presentation of Study Areas
145(2)
4.6 Review Questions
147(2)
Chapter 5 Visual Interpretation 149(24)
5.1 Characteristics of Photographic Images
149(1)
5.2 Feature Identification
149(2)
5.3 Criteria for Visual Interpretation
151(14)
5.3.1 Brightness
152(1)
5.3.2 Color
153(4)
5.3.3 Texture
157(3)
5.3.4 Spatial Context
160(1)
5.3.5 Shape and Size
160(1)
5.3.6 Shadows
161(2)
5.3.7 Spatial Pattern
163(1)
5.3.8 Stereoscopic View
163(1)
5.3.9 Period of Acquisition
164(1)
5.4 Elements of Visual Analysis
165(6)
5.4.1 Geometric Characteristics of a Satellite Image
165(1)
5.4.2 Effect of Spatial Resolution in Visual Analysis
166(1)
5.4.3 Effect of Spectral Resolution in Visual Analysis
167(2)
5.4.4 Color Composites
169(1)
5.4.5 Multitemporal Approaches
170(1)
5.5 Review Questions
171(2)
Chapter 6 Digital Image Processing (I): Enhancements and Corrections 173(86)
6.1 Structure of a Digital Image
173(3)
6.2 Media and Data Organization
176(1)
6.2.1 Data Storage
176(1)
6.2.2 Image File Formats
176(1)
6.3 Digital Image Processing Systems
177(2)
6.4 General File Operations
179(10)
6.4.1 File Management
179(3)
6.4.2 Display Utilities
182(2)
6.4.3 Image Statistics and Histograms
184(5)
6.5 Visual Enhancements
189(19)
6.5.1 Contrast Enhancement
189(9)
6.5.1.1 Color Lookup Table
190(2)
6.5.1.2 Contrast Compression
192(1)
6.5.1.3 Contrast Stretch
193(5)
6.5.2 Color Composites
198(2)
6.5.3 Pseudocolor
200(1)
6.5.4 Filters
201(7)
6.5.4.1 Digital Filters
201(4)
6.5.4.2 Low-Pass Filter
205(1)
6.5.4.3 High-Pass Filter
206(2)
6.6 Geometric Corrections
208(18)
6.6.1 Sources of Errors in Satellite Acquisitions
208(3)
6.6.2 Georeferencing from Orbital Models
211(4)
6.6.2.1 Image Inclination
211(2)
6.6.2.2 Panoramic Distortion
213(1)
6.6.2.3 Effect of Earth's Curvature
214(1)
6.6.3 Georeferencing from Control Points
215(11)
6.6.3.1 Establishing Control Points
216(1)
6.6.3.2 Calculating the Correction Function
217(4)
6.6.3.3 Generation of the Georeferenced Image
221(5)
6.6.4 Georeferencing with Digital Elevation Models
226(1)
6.7 Radiometric Corrections
226(27)
6.7.1 Solving Missed or Deteriorated Data
226(4)
6.7.1.1 Restoration of Missing Lines and Pixels
226(2)
6.7.1.2 Correction of Striping Effects
228(2)
6.7.2 Conversion from DL to Radiance
230(2)
6.7.3 Calculation of Reflectance
232(17)
6.7.3.1 Simplified Reflectance
232(2)
6.7.3.2 Atmospheric Correction
234(7)
6.7.3.3 Topographic Shadow Corrections
241(4)
6.7.3.4 Correction of Bidirectional Effects
245(4)
6.7.4 Calculation of Temperature
249(4)
6.8 Image Fusion Methods
253(4)
6.9 Review Questions
257(2)
Chapter 7 Digital Image Processing (II): Generation of Derived Variables 259(120)
7.1 Generation of Continuous Variables
259(38)
7.1.1 Inductive and Deductive Models in Remote Sensing
260(3)
7.1.2 Principal Component Analysis
263(6)
7.1.3 Spectral Vegetation Indices
269(16)
7.1.3.1 Ratio-Based VIs
271(4)
7.1.3.2 Optimized VIs
275(5)
7.1.3.3 Orthogonal-Based VIs
280(5)
7.1.3.4 Fluorescence Indices
285(1)
7.1.4 Other Spectral Indices
285(1)
7.1.5 Extraction of Subpixel Information
286(7)
7.1.6 Lidar Data Processing
293(4)
7.2 Digital Image Classification
297(44)
7.2.1 Introduction
297(2)
7.2.2 Training Phase
299(15)
7.2.2.1 Basic Concepts
299(2)
7.2.2.2 Supervised Classification
301(3)
7.2.2.3 Unsupervised Classification
304(4)
7.2.2.4 Mixed Methods
308(1)
7.2.2.5 Analysis of the Training Statistics
309(5)
7.2.3 Assignment Phase
314(24)
7.2.3.1 Minimum-Distance Classifier
314(1)
7.2.3.2 Parallelepiped Classifier
315(1)
7.2.3.3 Maximum Likelihood Classifier
316(6)
7.2.3.4 Decision Tree Classifier
322(2)
7.2.3.5 Neural Networks
324(4)
7.2.3.6 Fuzzy Classification
328(2)
7.2.3.7 Hyperspectral Classification
330(4)
7.2.3.8 Object-Oriented Classifiers
334(2)
7.2.3.9 Contextual Classifiers
336(1)
7.2.3.10 Postclassification Generalization
336(2)
7.2.4 Classification Outputs
338(3)
7.3 Techniques of Multitemporal Analysis
341(22)
7.3.1 Temporal Domain in Remote Sensing Studies
341(2)
7.3.2 Prerequisites for Multitemporal Analysis
343(3)
7.3.2.1 Multitemporal Matching
343(2)
7.3.2.2 Radiometric Calibration
345(1)
7.3.3 Methods for Seasonal Analysis
346(4)
7.3.4 Change Detection Techniques
350(13)
7.3.4.1 Multitemporal Color Composites
351(2)
7.3.4.2 Image Differencing
353(1)
7.3.4.3 Multitemporal Ratios
354(1)
7.3.4.4 Principal Components
354(1)
7.3.4.5 Regression Analysis
355(1)
7.3.4.6 Change Vector Analysis
355(4)
7.3.4.7 Defining Change Thresholds
359(1)
7.3.4.8 Multitemporal Analysis of Classified Images
360(3)
7.4 Analysis of Spatial Properties
363(11)
7.4.1 Remote Sensing and Landscape Ecology
363(2)
7.4.2 Spatial Metrics for Interval-Scale Images
365(4)
7.4.2.1 Global Metrics for Continuous Data
365(3)
7.4.2.2 Local Metrics for Continuous Data
368(1)
7.4.3 Spatial Metrics for Classified Images
369(5)
7.4.3.1 Global Metrics for Classified Data
371(1)
7.4.3.2 Local Metrics for Classified Data
372(2)
7.4.4 Landscape Structural Dynamics
374(1)
7.5 Review Questions
374(5)
Chapter 8 Validation 379(30)
8.1 Relevance of Validating Results
379(2)
8.2 Sources of Error
381(5)
8.2.1 Sensor Limitations
381(1)
8.2.2 Method of Analysis
381(1)
8.2.3 Landscape Complexity
382(1)
8.2.4 Verification Process
383(3)
8.3 Methods to Estimate Accuracy
386(1)
8.4 Sampling Design
387(5)
8.4.1 Error Distribution
388(1)
8.4.2 Sampling Unit
388(1)
8.4.3 Sampling Strategies
388(2)
8.4.4 Sample Size
390(2)
8.5 Gathering Information
392(1)
8.6 Validating Interval-Scale Variables
393(1)
8.7 Validating Classified Images
394(12)
8.7.1 Confusion Matrix
394(1)
8.7.2 Global Accuracy
395(3)
8.7.3 User and Producer Accuracy
398(1)
8.7.4 Kappa Statistic
399(2)
8.7.5 Normalizing the Confusion Matrix
401(2)
8.7.6 Validation of Binary Classes
403(2)
8.7.7 Verification in Multitemporal Analysis
405(1)
8.8 Review Questions
406(3)
Chapter 9 Remote Sensing and Geographic Information Systems 409(10)
9.1 Trends in GIS and Remote Sensing Development
409(2)
9.2 GIS as Input for RS Interpretation
411(1)
9.3 RS as Input for GIS
412(3)
9.3.1 Availability of Geographic Information
412(1)
9.3.2 Generation of Input Variables
413(1)
9.3.3 Updating the Information
414(1)
9.4 Integration of Satellite Images and GIS
415(2)
9.5 Review Questions
417(2)
Appendix 419(4)
References 423(36)
Index 459
Emilio Chuvieco is a professor of geography and director of the Environmental Ethics chair at the University of Alcalį, Spain. He was a visiting professor at the University of California at Berkeley and Santa Barbara, the Canadian Remote Sensing Center, Cambridge University, and the University of Maryland. In addition, he is science leader of the Fire Disturbance project within the European Space Agencys Climate Change Initiative program. He has coauthored 330 papers and book chapters, and 23 books. He has advised 35 Ph.D. dissertations. He is currently co-editor-in-chief of the journal Remote Sensing of Environment