Introductory Digital Image Processing: A Remote Sensing PerspectiveFor junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology. This text focuses exclusively on the art and science of digital image processing of satellite and aircraft-derived remotely-sensed data for resource management. Extensively illustrated, it explains how to extract biophysical information from remote sensor data for almost all multidisciplinary land-based environmental projects. Part of the Prentice Hall Series Geographic Information Science. |
Contents
Chapter 1Introduction to Digital Image Processing of Remotely Sensed Data | 1 |
Remote Sensing Data Analysis | 8 |
Chapter 2Remote Sensing Data Acquisition Alternatives | 16 |
Copyright | |
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aerial photography algorithm analysis array atmospheric brightness values cattail change detection Charleston classification map clusters coefficients computed contrast stretch coordinate dataset detector digital elevation model digital image processing display Engineering & Remote enhancement equation error example extract feature space filter forest Fourier transform frequency GCPs Geographic Information Systems geometric green histogram identify IFOV image processing systems imagery infrared input Jensen land-cover Landsat Landsat MSS Landsat Thematic Mapper Landsat TM linear mask matrix mean vectors measure MSS data Multispectral Scanner near-infrared normalization output panchromatic parallelepiped Photogrammetric Engineering pixel polygon radiance radiant flux radiometric raster rectified remote sensing system remotely sensed data sample satellite Savannah River scan scene selected sensor data sensor system shown in Figure slope soil spatial resolution spectral spectral space SPOT Image statistics surface Table terrain texture thermal infrared tion TM band TM data Variable vegetation visual wetland