Title :
Terrain Moisture Classification Using GPS Surface-Reflected Signals
Author :
Grant, Michael S. ; Acton, Scott T. ; Katzberg, Stephen J.
Author_Institution :
Software Syst. Branch, NASA Langley Res. Center, Hampton, VA
Abstract :
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
Keywords :
Global Positioning System; geophysical signal processing; image classification; moisture; soil; terrain mapping; GPS surface reflected signals; digital imagery; global positioning system signals; hydrology; land surface classification; landcover classes; precision agriculture; soil moisture component; surface imagery; surface moisture component; terrain moisture classification; visible image data; visible wavelengths; visibly identifiable terrain; wetlands mapping; Delay effects; Fresnel reflection; Global Positioning System; Instruments; Moisture; Rough surfaces; Satellites; Sea surface; Surface roughness; Surface topography; Global positioning system (GPS); pattern classification; pattern recognition; radar scattering; soil measurements;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2006.883526