Retrieving the Soil Moisture in Bare Farmland Areas Using a Modified Dubois Model

Abstract

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Soil moisture is an important parameter for global soil moisture transport, environmental evaluation, and precision agricultural research. The accurate retrieval of soil moisture in farmland areas using Synthetic Aperture Radar (SAR) depends on the accurate description of surface and SAR parameters. In these parameters, surface roughness and incidence angle are the key factors that affect the accuracy of the soil moisture retrieval model. This article proposes a modified Dubois model to retrieve soil moisture suitable for the bare surface of farmland area. The model eliminates the incidence angle parameters and uses polarization parameters to depict the surface roughness parameters in the Dubois model. To eliminate the incidence angle, the backscattering coefficients gamma0, which eliminates the effect of the incidence angles, are used to replace the sigma0. Under rain and no rain condition, the trend of backscattering coefficients (VH and VV) and cross-polarization ratio (VH-VV) of different soil texture with the soil moisture are compared. Then, the polarization parameter based on VH backscattering coefficients is used to describe surface roughness. The model is evaluated with time-series soil moisture observation data in situ of the study area. The results indicate that the modified model can retrieve soil moisture with high accuracy, and the total RMSE can reach 0.064 cm3cm−3 while the Dubois model is 0.124 cm3cm−3. Under rain and no rain condition, the retrieval accuracy of the modified model is 0.066 cm3cm−3 and 0.063 cm3cm−3. The retrieval accuracy is 0.060 cm3cm−3 and 0.067 cm3cm−3 under high and low incidence angles conditions, respectively. These results indicate that the modified Dubois model can retrieve soil moisture with high accuracy under different conditions.

Keywords

• sentinel-1
• backscattering coefficients
• retrieval model
• bare surface
• rain