Soil Moisture Retrieval Using SAR Backscattering Ratio Method during the Crop Growing Season

Soil moisture content (SMC) is an indispensable basic element for crop growth and development in agricultural production. Obtaining accurate information on SMC real time over large areas has important guiding significance yield estimation production management. In this study, the paper reports retrieval of from RADARSAT-2 polarimetric SAR data. The proposed algorithm includes vegetation correction based a ratio method roughness optimal method. Three description parameters (i.e., RVI, LAI, NDVI) serve as descriptors parameterization algorithm. To testify result algorithm, water cloud model (WCM) was compared with calibrated integrated equation (CIEM) employed to describe backscattering underlying soil. improve accuracy retrieval, CIEM optimized by using parameter normalization reference incidence angle. Validation against ground measurements showed high correlation between measured estimated when NDVI serves descriptor (R2 = 0.68, RMSE 4.15 vol.%, p < 0.01). overall performance better than that WCM. It demonstrates operational potential estimate wheat fields during growing season.