• DocumentCode
    1194010
  • Title

    Empirically Adopted IEM for Retrieval of Soil Moisture From Radar Backscattering Coefficients

  • Author

    Song, Kaijun ; Zhou, Xiaobing ; Fan, Yong

  • Author_Institution
    Dept. of Geophys. Eng., Montana Tech of the Univ. of Montana, Butte, MT
  • Volume
    47
  • Issue
    6
  • fYear
    2009
  • fDate
    6/1/2009 12:00:00 AM
  • Firstpage
    1662
  • Lastpage
    1672
  • Abstract
    The integral equation model (IEM) is considered as a promising algorithm for soil moisture retrieval from active microwave data over bare soil and sparsely vegetated conditions. However, the soil dielectric constant is implicitly embedded in the complicated IEM; inversion of soil moisture is often accomplished through iteration and is thus computationally expensive, particularly when it is applied to retrieve soil moisture from active microwave data on a large scale. To simplify the inversion process of soil moisture directly from the active microwave data, basic math functions were adopted to fit the simulation results of the original IEM so that the radar backscattering coefficient becomes an explicit function of soil dielectric constant or the soil dielectric constant is an explicit function of radar backscattering coefficient. Soil moisture is then calculated directly from radar backscattering coefficient without iteration. We called this model empirically adopted IEM (EA-IEM). The accuracy of the EA-IEM to the original IEM and its applicability are analyzed through three processes: model intercomparison, sensitivity analysis, and model comparison with in situ measurements. The average differences of backscattering coefficients between the EA-IEM and the original IEM are 0.14 dB for HH-polarization and 0.12 dB (Gaussian correlation function) and 0.2 dB (exponential correlation function) for VV-polarization. The sensitivity of soil moisture variation is examined under the consideration of absolute and relative calibration errors. A comparison between the soil moisture estimated and the measurements is performed, and the root-mean-square (rms) error is found to be 3.4%, suggesting that the EA-IEM performs well in these real cases. All these analyses indicate that the EA-IEM is a good representative of the original IEM and can be used to retrieve soil moisture under the tested range of model parameters: incidence angles between 10deg and 60- - deg, soil dielectric constants between 4 and 42, surface rms height from 4 to 31 mm, and correlation length from 50 to 250 mm.
  • Keywords
    backscatter; hydrological techniques; integral equations; moisture; permittivity; remote sensing by radar; soil; Gaussian correlation function; VV-polarization; active microwave data; exponential correlation function; integral equation model; inversion process; radar backscattering coefficients; soil dielectric constant; soil moisture retrieval; Backscattering coefficient; IEM; empirically adopted integral equation model (EA-IEM); soil moisture;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2008.2009061
  • Filename
    4801618