Abstract
Remote sensing science may be used to provide spatially distributed information for a significant number of models and applications. Information is extracted from remotely sensed data using the remote sensing process, which includes stating the problem, data collection (in situ and remote sensing), data-to-information conversion, and information presentation. The process requires a thorough understanding of the spatial, spectral, temporal, radiometric, and angular characteristics of the remotely sensed data. Advances in remote sensing of national spatial data infrastructure (NSDI) framework foundation variables (e.g., geodetic control, orthoimagery, digital elevation models) and selected framework thematic variables (e.g., land use/cover data, vegetation type and condition) are examined. The chapter concludes with a summary of advances in information extraction techniques and the integration of GIS and remote sensing.
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