Including vegetation scattering effects in a radar based soil moisture estimation model

R. Bindlish, A. P. Barros

Research output: Contribution to journalArticlepeer-review


Previously, the IEM (Integral Equation Model) was successfully used in conjunction with an inversion model to retrieve soil moisture using multi-frequency and multi-polarization data from Spaceborne Imaging Radar C-band (SIR-C) and X-band Synthetic Aperture Radar (X-SAR), without the need to prescribe time-varying land surface attributes as constraining parameters. The retrieved values were compared against in situ observations from the Washita'94 field experiment. The RMS error in the estimated soil moisture was of the order of 0.05 cm3 cm-3, which is comparable to the effect of noise in the SAR data. The IEM was originally developed for scattering from a bare soil surface, and therefore the vegetation scattering effects are not explicitly incorporated in the model. In this study, we couple a semi-empirical vegetation scattering model, modified after the water-cloud model, to the existing radar based soil moisture inversion model. This approach allows for the explicit representation of vegetation backscattering effects without the need to specify a large number of parameters. Although the use of this parameterization resulted in modest improvements (roughly 4% overall), it does provide a general framework that can be used for other applications.

Original languageEnglish (US)
Pages (from-to)354-361
Number of pages8
JournalIAHS-AISH Publication
Issue number267
StatePublished - 2000
Externally publishedYes


  • Inverse modelling
  • Microwave remote sensing
  • SAR
  • Soil moisture
  • Vegetation

ASJC Scopus subject areas

  • Oceanography
  • Water Science and Technology

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