Satellite Remote Sensing of Natural Resources offers an introduction to digital remote sensing. This comprehensive text emphasizes the basics, with simple concepts presented in clear, easy-to-understand language. For those who are interested in practical remote sensing but do not have an extensive background in math and statistics, this primer is invaluable. The main topics covered include satellite images, image processing systems, spectral regions, radiometric and geometric corrections, supervised and unsupervised classification, and accuracy assessment. Each chapter concludes with a section of sample problems and list of additional readings.
Author(s): David L. Verbyla
Series: Mapping Sciences Series
Publisher: CRC Press
Year: 1995
Language: English
Pages: 210
City: Boca Raton
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Contents
CHAPTER 1. SATELLITE IMAGES
Raster Image Data
Remote Sensing Detectors
Analog to Digital Conversion
Scanning Systems
Image Scale and Resolution
Scale
Resolution
Spatial Resolution
Spectral Resolution
Radiometric Resolution
Temporal Resolution
Major Satellite Systems Used In Natural Resources Management
Landsat
SPOT
AVHRR
Chapter 1 Problems
Additional Readings
General Readings
Satellite Remote Sensing of Natural Resources
Landsat Readings
SPOT Readings
AVHRR Readings
CHAPTER 2. IMAGE PROCESSING SYSTEMS
Introduction
Computer Fundamentals
Bits and Bytes
Magnetic Tapes
Packaging Multispectral Data
Display of Panchromatic Images
Contrast Enhancements
Min/Max Contrast Stretch
Linear Stretch Based on Standard Deviations
Histogram Equalization
Display of Color Images
Color Video Display
Color Image Printing
Image Magnification and Reduction
Chapter 2 Problems
Additional Readings
CHAPTER 3. SPECTRAL REGIONS
Introduction
Spectral Regions
Electromagnetic Spectrum
Spectral Distribution of Solar Energy
Terminology
Insolation-Earth Surface Interactions
Reflection
Absorption and Transmission
Atmospheric Scattering
Spectral Bands
Vegetation Spectral Relationships
Visible Spectral Region
Near-Infrared Spectral Region
Mid-Infrared Spectral Region
Water Spectral Relationships
Snow and Cloud Spectral Relationships
Soil Spectral Relationships
Thermal Remote Sensing
Potential Problems
Mixed Pixels
Spectral Dominance
Field Versus Laboratory Conditions
Chapter 3 Problems
Literature Cited
Additional Readings
General Readings
Vegetation Spectral Relationships
Water Spectral Relationships
Snow and Cloud Spectral Relationships
Soil Spectral Relationships
Thermal Remote Sensing
Topographic Corrections
CHAPTER 4. RADIOMETRIC CORRECTIONS
Introduction
Detector Errors
Line Dropout
Destriping
Correction for Atmospheric Scattering
Typical Applications
Aquatic Applications
Ratio Adjustments
Multi-Image Applications
Multi-Sensor Applications
Haze Remove Strategies
Histogram Adjustment Technique
Chapter 4 Problems
Literature Cited
Additional Readings
CHAPTER 5. GEOMETRIC CORRECTIONS
Introduction
Map Projections
Mercator Projection
Transverse Mercator Projection
Space Oblique Mercator Projection
Map Coordinate Systems
Geographic Coordinates
Universal Transverse Mercator Coordinates
State Plane Coordinates
Map Coordinates on Usgs 7.5-Minute Maps
U.S. National Map Accuracy Standards
Horizontal Accuracy Standard
Vertical Accuracy Standard
Selection of Ground Control Points
Ground Control Points from Maps
Ground Control Points Using GPS Receivers
Image Rectification Models
Review of Linear Models
Affine Coordinate Transformations
Polynomial Models
How Many Ground Control Points or Pixels?
A Simple No-Error Example
A Simple Example with Errors
Pixel Resampling Methods
Nearest Neighbor Resampling
Bilinear Interpolation Resampling
Cubic Convolution Resampling
Ordering Rectified Data
Chapter 5 Problems
Additional Readings
Map Accuracy
Map Projections and Coordinate Systems
Global Positioning Systems
Rectification of Digital Images
CHAPTER 6. UNSUPERVISED CLASSIFICATION
Introduction
Histogram-Based Unsupervised Classification
Sequential Clustering
Isodata Clustering
Skip Factors in Unsupervised Classification
Grouping of Spectral Classes
Grouping Based on Spatial Similarity
Cursor Inquiry
Color Palette Manipulation
Spectral Class Overlay
Grouping Based on Spectral Similarity
Chapter 6 Problems
Additional Readings
General
Applications
CHAPTER 7. SUPERVISED CLASSIFICATION
Introduction
Training Fields
Map Digitizing
On-Screen Digitizing
Seed-Pixel Approach
Popular Classifiers
Minimum Distance Classifier
Parallelepiped Classifier
Maximum Likelihood Classifier
Chapter 7 Problems
Additional Readings
General
Applications
CHAPTER 8. ACCURACY ASSESSMENT
Introduction
The Error Matrix
User’s and Producer’s Accuracy
Kappa Statistic
Collection of Reference Data
Sources of Conservative Estimates of Classification Accuracy
Errors in Reference Data
Positional Errrors
Minimum Mapping Unit Area
Sources of Optimistic Estimates of Classification Accuracy
Training Fields as Reference Data
Sampling from Blocks of Classified Pixels
Chapter 8 Problems
Additional Readings
APPENDIX SOLUTIONS TO EVEN-NUMBERED PROBLEMS
INDEX
