CONTENTS -- CHAPTER 1 INTRODUCTION -- 1.1 WHAT IS REMOTE SENSING (AS FAR AS WE'RE CONCERNED)? -- 1.2 WHY REMOTE SENSING? -- 1.3 WHAT KINDS OF REMOTE SENSING? -- 1.4 THE IMAGE CHAIN APPROACH -- 1.5 REFERENCES -- CHAPTER 2 HISTORICAL PERSPECTIVE AND PHOTO MENSURATION -- 2.1 PHOTO INTERPRETATION -- 2.2 QUANTITATIVE ANALYSIS OF AIR PHOTOS -- 2.2.1 Photogrammetry -- 2.2.2 Camera as a Radiometer -- 2.3 EVOLUTION OF EO SYSTEMS -- 2.4 SPACE-BASED EO SYSTEMS -- 2.5 DIGITAL CONCEPTS -- 2.6 REFERENCES -- CHAPTER 3 RADIOMETRY AND RADIATION PROPAGATION -- 3.1 ENERGY PATHS -- 3.1.1 Solar Energy Paths -- 3.1.2 Thermal Energy Paths -- 3.2 RADIOMETRIC TERMS -- 3.2.1 Definition of Terms -- 3.2.2 Blackbody Radiators -- 3.2.3 Polarization Concepts -- 3.3 RADIOMETRIC CONCEPTS -- 3.3.1 Inverse-Square Law for Irradiance from a Point Source -- 3.3.2 Projected Area Effects (cos θ) -- 3.3.3 Lambertian Surfaces -- 3.3.4 Magic π -- 3.3.5 Lens Falloff -- 3.4 ATMOSPHERIC PROPAGATION -- 3.4.1 Atmospheric Absorption -- 3.4.2 Atmospheric Scattering -- 3.5 CHARACTERISTICS OF THE EM SPECTRUM -- 3.6 REFERENCES -- CHAPTER 4 THE GOVERNING EQUATION FOR RADIANCE REACHING THE SENSOR -- 4.1 IRRADIANCE ONTO THE EARTH'S SURFACE -- 4.1.1 Solar Irradiance -- 4.1.2 Downwelled Radiance (Skylight) -- 4.1.3 Reflected Background Radiance -- 4.2 REFLECTED SOLAR IRRADIANCE AND BIDIRECTIONAL REFLECTANCE -- 4.2.1 Ways to Characterize Reflectance -- 4.2.2 Reflected Solar Radiance -- 4.3 SOLAR RADIANCE REACHING THE SENSOR -- 4.3.1 Solar Scattered Upwelled Radiance (Path Radiance) -- 4.3.2 Cumulative Solar Effects -- 4.3.3 Multiple Scattering and Nonlinearity Effects -- 4.4 THERMAL RADIANCE REACHING THE SENSOR -- 4.4.1 Self-Emission -- 4.4.2 Thermal Emission from the Sky and Background Reflected to the Sensor -- 4.4.3 Self-Emitted Component of Upwelled Radiance.

4.5 INCORPORATION OF SENSOR SPECTRAL RESPONSE -- 4.6 SIMPLIFICATION OF THE BIG EQUATION AND RELATIVE MAGNITUDE ASSESSMENT -- 4.6.1 Simplification -- 4.6.2 Sensitivity Analysis-Error Propagation -- 4.7 REFERENCES -- CHAPTER 5 SENSING SYSTEMS -- 5.1 CAMERAS AND FILM SYSTEMS -- 5.1.1 Irradiance onto the Focal Plane -- 5.1.2 Sensitometric Analysis -- 5.2 SIMILARITIES BETWEEN SIMPLE CAMERAS AND MORE EXOTIC ELECTRO-OPTICAL IMAGING SYSTEMS -- 5.2.1 Optics and Irradiance at the Focal Plane -- 5.2.2 System Characterization -- 5.3 DETECTORS AND SENSOR PERFORMANCE SPECIFICATIONS -- 5.3.1 Detector Types -- 5.3.2 Detector Figures of Merit -- 5.3.3 Sensor Performance Parameters -- 5.4 DETECTOR-SENSOR PERFORMANCE CALCULATIONS -- 5.5 REFERENCES -- CHAPTER 6 IMAGING SENSORS AND INSTRUMENTICALIBRATION -- 6.1 SINGLE-CHANNEL AND MULTISPECTRAL SENSORS -- 6.1.1 Line Scanners -- 6.1.2 Whisk-Broom and Bow-Tie Imagers -- 6.1.3 Push-Broom Sensors -- 6.1.4 Framing (2-D) Arrays -- 6.2 IMAGING SPECTROMETERS -- 6.2.1 Imaging Spectrometer Issues -- 6.2.2 Agile Spectrometers -- 6.3 LUMINESCENCE SENSORS -- 6.4 CALIBRATION ISSUES -- 6.5 SENSOR CASE STUDY -- 6.6 REFERENCES -- CHAPTER 7 ATMOSPHERIC COMPENSATION: SOLUTIONS TO THE GOVERNING EQUATION -- 7.1 TRADITIONAL APPROACH: CORRELATION WITH GROUND-BASED MEASUREMENTS -- 7.2 APPROACHES TO ATMOSPHERIC COMPENSATION -- 7.3 APPROACHES TO MEASUREMENT OF TEMPERATURE -- 7.3.1 Ground Truth Methods (Temperature) -- 7.3.2 In-Scene Compensation Techniques (Temperature) -- 7.3.3 Atmospheric Propagation Models (Temperature) -- 7.3.4 Emissivity -- 7.3.5 Summary of Thermal Atmospheric Compensation -- 7.4. APPROACHES TO MEASUREMENT OF REFLECTIVITY -- 7.4.1 Ground Truth Methods (Reflectance), a.k.a. Empirical Line Method (ELM) -- 7.4.2 In-Scene Methods (Reflectance) -- 7.4.3 Atmospheric Propagation Models (Reflectance).

7.5 RELATIVE CALIBRATION (REFLECTANCE) -- 7.5.1 Spectral Ratio Techniques -- 7.5.2 Scene-to-Scene Normalization -- 7.6 COMPENSATION OF IMAGING SPECTROMETER DATA FOR ATMOSPHERIC EFFECTS -- 7.6.1 Inversion to Reflectance -- 7.6.2 Spectral Polishing -- 7.7 SUMMARY OF ATMOSPHERIC COMPENSATION ISSUES -- 7.8 REFERENCES -- CHAPTER 8 DIGITAL IMAGE PROCESSING PRINCIPLES -- 8.1 POINT PROCESSING -- 8.2 NEIGHBORHOOD OPERATIONS-KERNEL ALGEBRA -- 8.3 STRUCTURE OR TEXTURE MEASURES -- 8.4 GLOBAL OPERATIONS -- 8.5 IMAGE RESTORATION -- 8.6 REFERENCES -- CHAPTER 9 MULTISPECTRAL REMOTE SENSING ALGORITHMS: LAND COVER CLASSIFICATION -- 9.1 REVIEW OF MATRIX METHODS -- 9.1.1 Vector Algebra -- 9.1.2 Matrix Algebra -- 9.1.3 Eigenvectors and Singular Value Decomposition (SVD) -- 9.2 IMAGE CLASSIFICATION -- 9.2.1 Supervised Classification of a Single-Band Image -- 9.2.2 Supervised Multispectral Image Classification -- 9.2.3 Unsupervised Multivariate Classifier -- 9.2.4 Multivariate Classification Using Texture Metrics -- 9.2.5 Evaluation of Class Maps -- 9.2.6 Limitations of Conventional Multispectral Classification -- 9.3 IMAGE TRANSFORMS -- 9.4 HIERARCHICAL IMAGE PROCESSING -- 9.5 REFERENCES -- CHAPTER 10 SPECTROSCOPIC IMAGE ANALYSIS -- 10.1 PERSPECTIVES ON SPECTRAL DATA -- 10.1.1 The Geometric or Deterministic Perspective -- 10.1.2 The Statistical Perspective -- 10.1.3 Spectral Feature Representation -- 10.2 ISSUES OF DIMENSIONALITY AND NOISE -- 10.2.1 Dimensionality Reduction -- 10.2.2 Noise Characterization: Noise versus Clutter -- 10.2.3 Noise-Sensitive Dimensionality Reduction -- 10.2.4 Estimation of the Dimensionality of a Data Set -- 10.3 GEOMETRIC OR DETERMINISTIC APPROACHES TO SPECTRAL IMAGE ANALYSIS -- 10.3.1 End Member Selection -- 10.3.2 Detection and Mapping Algorithms Using the Geometric or Structured Perspective -- 10.3.3 Linear Mixture Models and Fraction Maps.

10.4 STATISTICAL APPROACHES TO SPECTRAL IMAGE ANALYSIS -- 10.4.1 Estimation of Relevant Statistical Parameters -- 10.4.2 Target Detection Using Statistical Characterization of the Image -- 10.5 SPECTRAL FEATURE APPROACHES TO SPECTRAL IMAGE ANALYSIS -- 10.6 HYBRID APPROACHES TO SPECTRAL IMAGE ANALYSIS -- 10.7 REFERENCES -- CHAPTER 11 USE OF PHYSISCS-BASED MODELS TO SUPPORT SPECTRAL IMAGE ANALYSIS ALGORITHMS -- 11.1 SPECTRAL THERMAL INFRARED ANALYSIS METHODS -- 11.2 MODEL MATCHING USING RADIATIVE TRANSFER MODELS -- 11.2.1 Model Matching Applied to Atmospheric Compensation -- 11.2.2 Model Matching Applied to Water-Quality Parameter Retrieval -- 11.3 STATISTICAL INVERSION OF PHYSICAL MODELS -- 11.4 INCORPORATION OF PHYSICS-BASED MODELS INTO SPECTRAL ALGORITHM TRAINING -- 11.5 INCORPORATION OF PHYSICS-BASED SPATIAL SPECTRAL MODELS INTO ALGORITHM TRAINING -- 11.6 REFERENCES -- CHAPTER 12 IMAGE/DATA COMBINATION ANDINFORMATION DISSEMINATION -- 12.1 IMAGE DISPLAY -- 12.2 THEMATIC AND DERIVED INFORMATION -- 12.3 OTHER SOURCES OF INFORMATION -- 12.3.1 GIS Concepts -- 12.3.2 Databases and Models -- 12.4 IMAGE FUSION -- 12.5 KNOW YOUR CUSTOMER -- 12.6 REFERENCES -- CHAPTER 13 WEAK LINKS IN THE CHAIN -- 13.1 RESOLUTION EFFECTS (SPATIAL FIDELITY) -- 13.1.1 Spatial Image Fidelity Metrics -- 13.1.2 System MTF -- 13.1.3 Measurement of, and Correction for, MTF Effects -- 13.2 RADIOMETRIC EFFECTS -- 13.2.1 Noise -- 13.2.2 Noise Artifacts -- 13.2.3 Approaches for Correction of Noise and Periodic Structure in Images -- 13.3 SPECTRAL AND POLARIZATION EFFECTS -- 13.3.1 Feature/Spectral Band Selection -- 13.3.2 Polarization Issues -- 13.4 SPATIAL, SPECTRAL, AND RADIOMETRIC TRADEOFFS -- 13.5 IMAGE-QUALITY METRICS -- 13.6 SUMMARY OF IMAGE CHAIN CONCEPTS -- 13.7 REFERENCES -- CHAPTER 14 IMAGE MODELING -- 14.1 SIMULATION ISSUES -- 14.2 APPROACHES TO SIMULATION.

14.2.1 Physical Models -- 14.2.2 Fully Computerized Models -- 14.3 A MODELING EXAMPLE -- 14.4 APPLICATION OF SIG MODELS -- 14.5 SIG MODELING AND THE IMAGE CHAIN APPROACH -- 14.6 REFERENCES -- APPENDIX A: BLACKBODY CALCULATIONS -- INDEX -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- X -- Y -- Z.