Fundamentals of satellite remote sensing /

Fundamentals of satellite remote sensing /

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Bibliographic Details
Author / Creator:Chuvieco, Emilio.
Uniform title:Fundamentos de teledetección espacial. English
Imprint:Boca Raton : CRC Press, c2010.
Description:xii, 436 p. : ill., maps ; 25 cm. + 1 CD-ROM (4 3/4 in.)
Language:English
Subject:
Artificial satellites in remote sensing.
Earth sciences -- Remote sensing.
Environmental monitoring.
Artificial satellites in remote sensing.
Earth sciences -- Remote sensing.
Environmental monitoring.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/7908259
Hidden Bibliographic Details
Other authors / contributors:Huete, Alfredo.
ISBN:9780415310840 (hardcover : alk. paper)
0415310849 (hardcover : alk. paper)
9780415310857 (pbk. : alk. paper)
0415310857 (pbk. : alk. paper)
Notes:Includes bibliographical references and index.
System requirements: viewers for MS PowerPoint, MPEG, and GeoTIFF.
Table of Contents:
  • Foreword
  • Chapter 1. Introduction
  • 1.1. Definition and Objectives
  • 1.2. Historical Background
  • 1.3. International Space Law
  • 1.4. Advantages of Space-Based Observations
  • 1.4.1. Global Coverage
  • 1.4.2. A Synoptic View
  • 1.4.3. Multiscale Observations
  • 1.4.4. Observations over the Nonvisible Regions of the Spectrum
  • 1.4.5. Repeat Observation
  • 1.4.6. Immediate Transmission
  • 1.4.7. Digital Format
  • 1.5. Sources of Information on Remote Sensing
  • 1.6. Review Questions
  • Chapter 2. Physical Principles of Remote Sensing
  • 2.1. Fundamentals of Remote Sensing Signals
  • 2.2. The Electromagnetic Spectrum
  • 2.3. Terms and Units of Measurement
  • 2.4. Electromagnetic Radiation Laws
  • 2.5. Spectral Signatures in the Solar Spectrum
  • 2.5.1. Introduction
  • 2.5.2. Vegetation Reflectance
  • 2.5.3. Soil Reflectance Properties
  • 2.5.4. Water in the Solar Spectrum
  • 2.6. The Thermal Infrared Domain
  • 2.6.1. Characteristics of EM Radiation in Thermal Infrared
  • 2.6.2. Thermal Properties of Vegetation
  • 2.6.3. Soils in Thermal Domain
  • 2.6.4. Thermal Signature of Water and Snow
  • 2.7. The Microwave Region
  • 2.7.1. Characteristics of Electromagnetic Radiation in the Microwave Region
  • 2.7.2. Characteristics of Vegetation in the Microwave Region
  • 2.7.3. Characteristics of Soil and Water in the Microwave Region
  • 2.8. Atmospheric interactions
  • 2.8.1. Atmospheric Absorption
  • 2.8.2. Atmospheric Scattering
  • 2.8.3. Atmospheric Emission
  • 2.9. Review Questions
  • Chapter 3. Sensors and Remote Sensing Satellites
  • 3.1. Types of Sensors
  • 3.2. Resolution of a Sensor System
  • 3.2.1. Spatial Resolution
  • 3.2.2. Spectral Resolution
  • 3.2.3. Radiometric Resolution
  • 3.2.4. Temporal Resolution
  • 3.2.5. Angular Resolution
  • 3.2.6. Relationship among Different Types of Resolution
  • 3.3. Passive Sensors
  • 3.3.1. Photographic Cameras
  • 3.3.2. Cross-Track Scanners
  • 3.3.3. Along-Track (Push-Broom) Scanners
  • 3.3.4. Video Cameras
  • 3.3.5. Microwave Radiometers
  • 3.4. Active Sensors
  • 3.4.1. Radar
  • 3.4.2. LIDAR
  • 3.5. Satellite Remote Sensing Missions
  • 3.5.1. Satellite Orbits
  • 3.5.2. The Landsat Program
  • 3.5.3. SPOT Satellite
  • 3.5.4. The IRS Program
  • 3.5.5. High-Spatial-Resolution Commercial Satellites
  • 3.5.6. TIROS-NOAA
  • 3.5.7. Other Polar Orbiting Meteorological Satellites
  • 3.5.8. Terra-Aqua
  • 3.5.9. Geostationary Meteorological Satellites
  • 3.6. Review Questions
  • Chapter 4. Basis for Interpretation of Remote Sensing Images
  • 4.1. Constraints in Using Remote Sensing Data
  • 4.1.1. What Can Be Estimated from the Images?
  • 4.1.2. Costs of Data Acquisition
  • 4.1.3. End-User Requirements
  • 4.2. Types of Interpretation
  • 4.2.1. Thematic Classification
  • 4.2.2. Generation of Biophysical Variables
  • 4.2.3. Change Detection
  • 4.2.4. Spatial Patterns
  • 4.3. Organization of Remote Sensing Project
  • 4.3.1. Description of Objectives
  • 4.3.2. Scale and Resolution
  • 4.3.3. Classification Typology
  • 4.3.4. Selection of Imagery
  • 4.3.5. Image Formats and Media
  • 4.3.6. Selection of Interpretation Method: Visual or Digital Processing?
  • 4.4. Interpretation Phase
  • 4.5. Presentation of Study Cases
  • 4.6. Review Questions
  • Chapter 5. Visual Interpretation
  • 5.1. Characteristics of Photographic Images
  • 5.2. Feature Identification
  • 5.3. Criteria for Visual Interpretation
  • 5.3.1. Brightness
  • 5.3.2. Color
  • 5.3.3. Texture
  • 5.3.4. Spatial Context
  • 5.3.5. Shadows
  • 5.3.6. Spatial Pattern
  • 5.3.7. Shape and Size
  • 5.3.8. Stereoscopic View
  • 5.3.9. Period of Acquisition
  • 5.4. Elements of Visual Analysis
  • 5.4.1. Geometric Characteristics of a Satellite Image
  • 5.4.2. Effect of Spatial Resolution in Visual Analysis
  • 5.4.3. Effect of Spectral Resolution in Visual Analysis
  • 5.4.4. Color Composites
  • 5.4.5. Multitemporal Approaches
  • 5.5. Review Questions
  • Chapter 6. Digital Image Processing (I): Enhancements and Corrections
  • 6.1. Structure of a Digital Image
  • 6.2. Media and Data Organization
  • 6.2.1. Data Storage
  • 6.2.2. Recording Formats
  • 6.3. Digital Image Processing Equipment
  • 6.4. General File Operations
  • 6.4.1. File Management
  • 6.4.2. Display Utilities
  • 6.4.3. Image Statistics and Histograms
  • 6.5. Visual Enhancements
  • 6.5.1. Contrast Enhancement
  • 6.5.1.1. Color Look-Up Table
  • 6.5.1.2. Contrast Compression
  • 6.5.1.3. Contrast Stretch
  • 6.5.2. Color Composites
  • 6.5.3. Pseudo-Color
  • 6.5.4. Filters
  • 6.5.4.1. Digital Filters
  • 6.5.4.2. Low-Pass Filter
  • 6.5.4.3. High-Pass Filter
  • 6.6. Image Corrections
  • 6.6.1. Sources of Error in Satellite Imagery
  • 6.6.2. Radiometric Corrections
  • 6.6.2.1. Restoration of Missing Lines and Pixels
  • 6.6.2.2. Correction of Striping Effects
  • 6.6.2.3. Calculating Reflectance
  • 6.6.2.4. Calculating Temperature
  • 6.6.3. Geometric Corrections
  • 6.6.3.1. Introduction
  • 6.6.3.2. Correction from Orbital Models
  • 6.6.3.3. Correction from Control Points
  • 6.6.3.4. Calculating the Transformation Function
  • 6.6.3.5. Transference of the Original DL to Its Corrected Position
  • 6.6.3.6. Correction with Digital Elevation Models
  • 6.7. Review Questions
  • Chapter 7. Digital Image Processing (II): Generation of Thematic Information
  • 7.1. Continuous Variables
  • 7.1.1. Inductive and Deductive Models in Remote Sensing
  • 7.1.2. Principal Component Analysis
  • 7.1.3. Spectral Vegetation Indices (VIs)
  • 7.1.3.1. Ratio-Based VIs
  • 7.1.3.2. Optimized VIs
  • 7.1.3.3. Orthogonal-Based VIs
  • 7.1.4. Extraction of Subpixel Information
  • 7.2. Digital Image Classification
  • 7.2.1. Introduction
  • 7.2.2. Training Phase
  • 7.2.2.1. Basic Concepts
  • 7.2.2.2. Supervised Classification
  • 7.2.2.3. Unsupervised Classification
  • 7.2.2.4. Mixed Methods
  • 7.2.2.5. Analysis of the Training Statistics
  • 7.2.3. Assignment Phase
  • 7.2.3.1. Minimum Distance Classifier
  • 7.2.3.2. Parallelepiped Classifier
  • 7.2.3.3. Maximum Likelihood Classifier
  • 7.2.3.4. Decision Tree Classifier
  • 7.2.3.5. Neural Networks
  • 7.2.3.6. Fuzzy Classification
  • 7.2.3.7. Hyperspectral Classification
  • 7.2.3.8. Contextual Classifiers
  • 7.2.4. Classification Outputs
  • 7.2.4.1. Mapping Products
  • 7.2.4.2. Statistical Products
  • 7.3. Techniques of Multitemporal Analysis
  • 7.3.1. Temporal Domain in Remote Sensing Studies
  • 7.3.2. Prerequisites for Multitemporal Analysis
  • 7.3.2.1. Multitemporal Matching
  • 7.3.2.2. Radiometric Calibration
  • 7.3.3. Methods for Seasonal Analysis
  • 7.3.4. Change Detection Techniques
  • 7.3.4.1. Multitemporal Color Composites
  • 7.3.4.2. Image Differencing
  • 7.3.4.3. Multitemporal Ratios
  • 7.3.4.4. principal Components
  • 7.3.4.5. Regression Analysis
  • 7.3.4.6. Change Vector Analysis
  • 7.3.4.7. Defining Change Thresholds
  • 7.3.4.8. Multitemporal Analysis of Classified Images
  • 7.4. Analysis of Landscape Patterns
  • 7.4.1. Remote Sensing and Landscape Ecology
  • 7.4.2. Spatial Metrics for Interval-Scale Images
  • 7.4.2.1. Global Metrics for Continuous Data
  • 7.4.2.2. Local Metrics for Continuous Data
  • 7.4.3. Spatial Metrics for Classified Images
  • 7.4.3.1. Global Metrics for Classified Data
  • 7.4.3.2. Local Metrics for Classified Data
  • 7.4.4. Landscape Structural Dynamics
  • 7.5. Review Questions
  • Chapter 8. Accuracy Assessment
  • 8.1. Relevance of Validating Results
  • 8.2. Methods to Estimate Accuracy
  • 8.3. Sources of Error
  • 8.3.1. Sensor Limitations
  • 8.3.2. Method of Analysis
  • 8.3.3. Landscape Complexity
  • 8.3.4. Verification Process
  • 8.4. Sampling Design
  • 8.4.1. Error Distribution
  • 8.4.2. Sampling Unit
  • 8.4.3. Sampling Strategies
  • 8.4.4. Sample Size
  • 8.5. Gathering Information
  • 8.6. Measuring Error in Interval-Scale Variables
  • 8.7. Measuring Error in Classified Images
  • 8.7.1. The Confusion Matrix
  • 8.7.2. Global Accuracy
  • 8.7.3. User Accuracy and Producer Accuracy
  • 8.7.4. Kappa Statistic
  • 8.7.5. Normalizing the Confusion Matrix
  • 8.7.6. Validation of Binary Classes
  • 8.8. Verification of Multitemporal Analysis
  • 8.9. Review Questions
  • Chapter 9. Remote Sensing and Geographic Information Systems
  • 9.1. The Need for GIS
  • 9.2. Trends in GIS and Remote Sensing Development
  • 9.3. Common Technical Requirements
  • 9.4. GIS as Input for Remote Sensing Interpretation
  • 9.5. Remote Sensing as Input for GIS
  • 9.5.1. Availability of Geographic Information
  • 9.5.2. Generation of Input Variables
  • 9.5.3. Updating the Information
  • 9.6. Integration of Satellite Images and GIS
  • 9.7. Review Questions
  • Appendix
  • References
  • Index
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