• DocumentCode
    2680171
  • Title

    Characterization of Backscatter by Surface Features in L-Band Active Microwave Remote Sensing of Soil Moisture

  • Author

    Das, Narendra N. ; Mohanty, Binayak P. ; Njoku, Eni G.

  • Author_Institution
    Dept. of Biol. & Agric. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    2
  • fYear
    2008
  • fDate
    7-11 July 2008
  • Abstract
    Satellite-based remote sensing of soil moisture is generally conducted with active (radar) and passive (radiometer) microwave measurements. During active microwave remote sensing the backscattering from the target i.e, the soil surface is adversely affected by the overlaying vegetation, consequently, sending degraded signal back to the radar sensor. This phenomena greatly compromise with the quality of soil moisture measurements. The proposed research presents an algorithm that averts usage of theoretical and empirical backscattering models. The algorithm uses Soil-Vegetation-Atmosphere-Transfer model for soil moisture estimation that is used to quantify the backscattering components of radar signals. The algorithm has simple and valid assumptions that convert the total radar backscattering equations for a particular temporal scale into a set of simple linear systems. The algorithm reasonably estimates the stochastic surface roughness and vegetation backscattering components.
  • Keywords
    moisture; radar cross-sections; remote sensing by radar; soil; vegetation; L-band active microwave remote sensing; Soil-Vegetation-Atmosphere-Transfer model; empirical backscattering model; passive microwave measurements; radar backscattering equations; radar signals; soil moisture; stochastic surface roughness; theoretical backscattering model; vegetation backscattering components; Backscatter; L-band; Moisture measurement; Passive radar; Radar measurements; Radar remote sensing; Remote sensing; Soil measurements; Soil moisture; Vegetation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
  • Conference_Location
    Boston, MA
  • Print_ISBN
    978-1-4244-2807-6
  • Electronic_ISBN
    978-1-4244-2808-3
  • Type

    conf

  • DOI
    10.1109/IGARSS.2008.4779119
  • Filename
    4779119