Estimating soil moisture in the agricultural areas using RADARSAT-2 Quad-olarization SAR data

The aim of this study was to estimate soil moisture from RADARSAT-2 Quad-polarization Synthetic Aperture Radar (SAR) data acquired in the agricultural areas. The adopted approach is based on the combination of semi-empirical Water-Cloud model and Dubois model. Firstly, VH backscattering coefficient was used to develop empirical relationship for crop water content estimation. Secondly, crop water content was then used to correct the semi-empirical Water-Cloud model for vegetation effects in order to get the VV and HH backscattering coefficient of soil surface in the absence of vegetation cover. Thirdly, the soil moisture was retrieved based on Dubois model using VV and HH backscattering coefficient of soil surface in the absence of vegetation cover. Finally, the soil moisture retrieved is evaluated over wheat crop fields using ground measurements. This paper proposes an effective method for acquiring soil moisture in the agricultural areas under any weather conditions.