Chapter 1 Introuduction to Fundamentals　1.1 Definition of Remote sensing　1.2 Electromagnetic Radiation　1.3 The Electromagnetic Spectrum　1.4 Interactions with the Atmosphere　1.5 Radiation-Target Interactions　1.6 Passive vs. Active Sensing　1.7 Characteristics of Images　ExercisesChapter 2 Satellites and Sensors　2.1 On the Ground, In the Air, In Space　2.2 Satellite Characteristics: Orbits and Swaths　2.3 Spatial Resolution, Pixel Size, and Scale　2.4 Spectral Resolution　2.5 Radiometric Resolution　2.6 Temporal Resolution　2.7 Cameras and Aerial Photography　2.8 Muhispeetral Scanning　2.9 Thermal Imaging　2.10 Geometric Distortion in Imagery　2.11 Weather Satellites/Sensors　2.12 Land Observation Satellites/Sensors　2.13 Marine Observation Satellites/Sensors　2.14 Other Sensors　2.15 Data Reception, Transmission, and Processing　ExercisesChapter 3 Microwave Remote Sensing　3.1 Introduction　3.2 Radar Basics　3.3 Viewing Geometry and Spatial Resolution　3.4 Radar Image Distortions　3.5 Target Interaction and Image Appearance　3.6 Radar Image Properties　3.7 Advanced Radar Applications　3.8 Radar Polarimetry　3.9 Airborne versus Spaceborne Radars　3.10 Airborne and Spaceborne Radar Systems　　3.10.1 Airborne Radar Systems　　3.10.2 Spaceborne Radar SystemsChapter4 Image Interpretaion&Analysis　4.1 Introduction　4.2 Elements of Visual Interpretation　4.3 Pre-processing　　4.3.1 Radiometric Corrections　　4.3.2 Correction of Geometric Distortion　4.4 Image Subsetting and Mosaicking　　4.4.1 Image Subsetting　　4.4.2 Image Mosaicking　4.5 Image Enhancement　　4.5.1 Image Histogram　　4.5.2 Density Slicing　　4.5.3 Linear Enhancement　　4.5.4 Piecewise Linear Enhancement　　4.5.5 Look-up Table　　4.5.6 Nonlinear Stretching　4.6 Spatial Filtering　　4.6.1 Neighborhood and Connectivity　　4.6.2 Kernels and Convolution　　4.6.3 Image Smoothing　　4.6.4 Median Filtering　　4.6.5 Edge-Detection Templates　4.7 Multiple-Image Manipulation　　4.7.1 Band Ratioing　　4.7.2 Vegetation Index　4.8 Image Transformation　　4.8.1 PCA　　4.8.2 Tasseled Cap Transformation　　4.8.3 HIS Transformation　4.9 Image Filtering in Frequency Domain　4.10 Fundamentals of Classification　　4.10.1 Spectral Class versus Information Class　　4.10.2 Distance in the Spectral Domain　4.11Unsupervised Classification　　4.11.1 Moving Cluster Analysis　　4.11.2 Iterative Self-Organizing Data Analysis　　4.11.3 Agglomerative Hierarchical Clustering　　4.11.4 Histogram-Based Clustering　4.12Supervised Classification　　4.12.1 Procedure　　4.12.2 Per-Pixel Image Classifiers　4.13 Unsupervised and Supervised Classification　4.14 Other methods for classification　　4.14.1 Mean Shift Clustering　　4.14.2 Fuzzy Image Classification　　4.14.3 Neural Network　　4.14.4 Decision Tree　4.15 Data Integration and Analysis　ExercisesChapter 5 Applications　5.1 Introduction　5.2 Land Use & Land Cover ( Rural / Urban)　　5.2.1 Basic Concepts　　5.2.2 Change Detection Steps　　5.2.3 Common Satellite and Sensor in LULC Research　　5.2.4 Case Study　5.3 Urban Thermal Environment　　5.3.1 Introduction　　5.3.2 Case study-Yangtze River Delta　ExercisesChapter 6 ERDAS User' s Guide　6.1 Introduction to ERDAS　6.2 Getting Started　6.3 Viewer　6.4 Image Enhance　6.5 Image Rectification　6.6 Unsupervised Classification　6.7 Supervised Classification1 Matrix Indexing2 Function Imadjust3 Logarithmic and Contrast-Stretching Transformation4 Generating and Plotting Image Histograms5 Linear Spatial Filtering6 Basic Steps in DFT Filtering7 Lowpass Frequency Domain Filters8 Dilation and Erosion9 Edge Detection Using Function edgeReferences