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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
��exercises
chapter 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
��exercises
chapter 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 systems
chapter4 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
��exercises
chapter 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
��exercises
chapter 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 classification
1 matrix indexing
2 function imadjust
3 logarithmic and contrast-stretching transformation
4 generating and plotting image histog