• DocumentCode
    862446
  • Title

    Retrieval of land surface parameters in the Sahel from ERS wind scatterometer data: a "brute force" method

  • Author

    Jarlan, L. ; Mazzega, P. ; Mougin, E.

  • Author_Institution
    Centre d´´Etudes Spatiales de la Biosphere, Toulouse, France
  • Volume
    40
  • Issue
    9
  • fYear
    2002
  • fDate
    9/1/2002 12:00:00 AM
  • Firstpage
    2056
  • Lastpage
    2062
  • Abstract
    The retrieval of surface parameters, namely, the soil moisture content and the herbaceous above-ground biomass, from European Remote Sensing (ERS) wind-scatterometer data is investigated for a Sahelian study site during the period 1993-1994. Thanks to the low dimension of the unknown parameter vector, a systematic exploration of the parameter space could be carried out. This method allows the recovery of the optimal parameter set as well as an exhaustive description of the subdomain of acceptable solutions. The mapping of this subdomain points out the lack of constraints brought by the ERS dataset on the determination of the surface parameters. Particularly, additional constraints should be found on the rapid and short-scale variation of the soil moisture content. Moreover, it is shown that the distributions of the retrieved parameters are not normal nor log normal, as could be expected from random variables. As a consequence, the optimal parameter set is neither the average nor the maximum likelihood, and the computation of an a posteriori standard deviation of the parameters is meaningless.
  • Keywords
    hydrological techniques; moisture; remote sensing by radar; soil; spaceborne radar; vegetation mapping; ERS wind scatterometer data; Sahel; herbaceous above-ground biomass; land surface parameters; nonlinear optimization; optimal parameter set; soil moisture content; subdomain; unknown parameter vector; Cost function; Information retrieval; Inverse problems; Land surface; Least squares methods; Radar measurements; Remote sensing; Soil moisture; Spaceborne radar; Uninterruptible power systems;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2002.802500
  • Filename
    1046854