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Terrain Moisture Classification Using GPS Surface-Reflected Signals

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3 Author(s)
Michael S. Grant ; Software Syst. Branch, NASA Langley Res. Center, Hampton, VA ; Scott T. Acton ; Stephen J. Katzberg

In this letter, a novel method of land-surface classification using surface-reflected global positioning system (GPS) signals in combination with digital imagery is presented. Two GPS-derived classification features are merged with visible image data to create terrain moisture classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, the use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping

Published in:

IEEE Geoscience and Remote Sensing Letters  (Volume:4 ,  Issue: 1 )