• DocumentCode
    815870
  • Title

    Soil Moisture Retrieval During a Corn Growth Cycle Using L-Band (1.6 GHz) Radar Observations

  • Author

    Joseph, Alicia T. ; van der Velde, Rogier ; O´Neill, Peggy E. ; Lang, Roger H. ; Gish, Tim

  • Author_Institution
    Hydrol. Sci. Branch, NASA Goddard Space Flight Center, Greenbelt, MD
  • Volume
    46
  • Issue
    8
  • fYear
    2008
  • Firstpage
    2365
  • Lastpage
    2374
  • Abstract
    This paper reports on the retrieval of soil moisture from dual-polarized L-band (1.6 GHz) radar observations acquired at view angles of 15deg, 35deg, and 55deg, which were collected during a field campaign covering a corn growth cycle in 2002. The applied soil moisture retrieval algorithm includes a surface roughness and vegetation correction and could potentially be implemented as an operational global soil moisture retrieval algorithm. The surface roughness parameterization is obtained through inversion of the Integral Equation Method (IEM) from dual-polarized (HH and VV) radar observations acquired under nearly bare soil conditions. The vegetation correction is based on the relationship found between the ratio of modeled bare soil scattering contribution and observed backscatter coefficient (sigmasoil/sigmaobs) and vegetation water content (W). Validation of the retrieval algorithm against ground measurements shows that the top 5-cm soil moisture can be estimated with an accuracy between 0.033 and 0.064 cm3 ldr cm-3, depending on the view angle and polarization.
  • Keywords
    crops; geophysical signal processing; hydrology; remote sensing by radar; soil; surface roughness; backscatter coefficient; bare soil scattering contribution; corn growth cycle; dual-polarized L-band radar observation; frequency 1.6 GHz; integral equation method; polarization; soil moisture retrieval; surface roughness; vegetation correction; vegetation water content; viewing angle; Backscatter; Integral equations; L-band; Moisture measurement; Radar scattering; Rough surfaces; Soil measurements; Soil moisture; Surface roughness; Vegetation; Field campaign; radar observations; remote sensing; soil moisture retrieval;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2008.917214
  • Filename
    4578823