• DocumentCode
    965268
  • 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
  • Volume
    4
  • Issue
    1
  • fYear
    2007
  • Firstpage
    41
  • Lastpage
    45
  • 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;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2006.883526
  • Filename
    4063291