SATELLITE REMOTE SENSING

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Hubert Jackson
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1 SATELLITE REMOTE SENSING of NATURAL RESOURCES David L. Verbyla LEWIS PUBLISHERS Boca Raton New York London Tokyo

2 Contents CHAPTER 1. SATELLITE IMAGES 1 Raster Image Data 2 Remote Sensing Detectors 2 Analog to Digital Conversion 3 Scanning Systems 4 Image Scale and Resolution 5 Scale 5 Resolution 6 Spatial Resolution 6 Spectral Resolution 6 Radiometric Resolution 6 Temporal Resolution 7 Major Satellite Systems Used In Natural Resources Management 7 Landsat 9 SPOT 9 AVHRR 10 Chapter 1 Problems 10 Additional Readings 11 General Readings 11 Satellite Remote Sensing of Natural Resources 12 Landsat Readings 12 SPOT Readings 13 AVHRR Readings 13 CHAPTER 2. IMAGE PROCESSING SYSTEMS 15 Introduction 16 Computer Fundamentals 16 Bits and Bytes 16 Magnetic Tapes 17 Packaging Multispectral Data 19

3 Display of Panchromatic Images 20 Contrast Enhancements 22 Min/Max Contrast Stretch 22 Linear Stretch Based on Standard Deviations 24 Histogram Equalization 24 Display of Color Images 27 Color Video Display 28 Color Image Printing 30 Image Magnification and Reduction 31 Chapter 2 Problems 32 Additional Readings 40 CHAPTER 3. SPECTRAL REGIONS 41 Introduction 42 Spectral Regions 43 Electromagnetic Spectrum 43 Spectral Distribution of Solar Energy 43 Terminology 43 Insolation-Earth Surface Interactions 45 Reflection 45 Absorption and Transmission 45 Atmospheric Scattering 46 Spectral Bands 46 Vegetation Spectral Relationships 46 Visible Spectral Region 46 Near-Infrared Spectral Region 48 Mid-Infrared Spectral Region 50 Water Spectral Relationships 51 Snow and Cloud Spectral Relationships 53 Soil Spectral Relationships 54 Thermal Remote Sensing 55 Potential Problems 57 Mixed Pixels 57 Spectral Dominance 58 Field Versus Laboratory Conditions 58 Chapter 3 Problems 60 Literature Cited 62 Additional Readings 63 General Readings 63 Vegetation Spectral Relationships 64 Water Spectral Relationships 64 Snow and Cloud Spectral Relationships ; 65 Soil Spectral Relationships 65 Thermal Remote Sensing 65 Topographic Corrections 66

4 CHAPTER 4. RADIOMETRIC CORRECTIONS 69 Introduction 70 Detector Errors 70 Line Dropout 70 Destriping 71 Correction for Atmospheric Scattering 72 Typical Applications 72 Aquatic Applications 72 Ratio Adjustments 72 Multi-Image Applications 73 Multi-Sensor Applications 73 Haze Remove Strategies 73 Histogram Adjustment Technique 73 Chapter 4 Problems 75 Literature Cited 75 Additional Readings 76 CHAPTER 5. GEOMETRIC CORRECTIONS 77 Introduction 78 Map Projections 78 Mercator Projection 78 Transverse Mercator Projection 78 Space Oblique Mercator Projection 79 Map Coordinate Systems 79 Geographic Coordinates 80 Universal Transverse Mercator Coordinates 80 State Plane Coordinates 81 Map Coordinates on Usgs 7.5-Minute Maps 82 U.S. National Map Accuracy Standards 82 Horizontal Accuracy Standard 84 Vertical Accuracy Standard 84 Selection of Ground Control Points 84 Ground Contrci Points from Maps 84 Ground Control Points Using GPS Receivers 85 Image Rectification Models 86 Review of Linear Models 86 Affine Coordinate Transformations 87 Polynomial Models 87 How Many Ground Control Points or Pixels? 89 A Simple No-Error Example 92 A Simple Example with Errors 93 Pixel Resampling Methods 98 Nearest Neighbor Resampling 98 Bilinear Interpolation Resampling 99 Cubic Convolution Resampling 101

5 Ordering Rectified Data 101 Chapter 5 Problems 102 Additional Readings 104 Map Accuracy 104 Map Projections and Coordinate Systems 104 Global Positioning Systems 105 Rectification of Digital Images 105 CHAPTER 6. UNSUPERVISED CLASSIFICATION 107 Introduction 108 Histogram-Based Unsupervised Classification 108 Sequential Clustering Ill Isodata Clustering 117 Skip Factors in Unsupervised Classification 124 Grouping of Spectral Classes 124 Grouping Based on Spatial Similarity 124 Cursor Inquiry 125 Color Palette Manipulation 125 Spectral Class Overlay 125 Grouping Based on Spectral Similarity 126 Chapter 6 Problems 128 Additional Readings 131 General 131 Applications 131 CHAPTER 7. SUPERVISED CLASSIFICATION 133 Introduction 134 Training Fields 134 Map Digitizing 135 On-Screen Digitizing 135 Seed-Pixel Approach 136 Popular Classifiers 137 Minimum Distance Classifier 137 Parallelepiped Classifier 139 Maximum Likelihood Classifier 142 Chapter 7 Problems 150 Additional Readings 155 General 155 Applications 155 CHAPTER 8. ACCURACY ASSESSMENT 157 Introduction 158 The Error Matrix 158 User's and Producer's Accuracy 159 Kappa Statistic 159

6 Collection of Reference Data 160 Sources of Conservative Estimates of Classification Accuracy 160 Errors in Reference Data 161 Positional Errrors 161 Minimum Mapping Unit Area 161 Sources of Optimistic Estimates of Classification Accuracy 161 Training Fields as Reference Data 163 Sampling from Blocks of Classified Pixels 163 Chapter 8 Problems 164 Additional Readings 166 APPENDIX SOLUTIONS TO EVEN-NUMBERED PROBLEMS 169 INDEX 193

SHRI ANGALAMMAN COLLEGE OF ENGINEERING AND TECHNOLOGY (An ISO 9001:2008 Certified Institution) Siruganoor, Tiruchirappalli

SHRI ANGALAMMAN COLLEGE OF ENGINEERING AND TECHNOLOGY (An ISO 9001:2008 Certified Institution) Siruganoor, Tiruchirappalli 621 105. FS 81504 DEPARTMENT OF CIVIL ENGINEERING 1. Define remote sensing. CE-1304