Processing and Applications of Remotely Sensed Data

Digital image processing, post-processing, and data integration techniques as applied to airborne and satellite remotely sensed data for the purpose of extracting useful Earth resources information will be discussed in this chapter. Image preprocessing and data reduction tools are described in the previous chapter. The concepts discussed in this chapter include: • Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems • The most widely accepted indices and land use/land cover classification schemes • Post-processing techniques such as filtering and change detection • Accuracy assessment and validation of results • Data integration and spatial modeling including examples of integration of remotely sensed data with other conventional survey and map form data for Earth observation purposes

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