Retrieving Surface Soil Moisture over Wheat-Covered Areas Using Data from Sentinel-1 and Sentinel-2

Surface soil moisture (SSM) is a major factor that affects crop growth. Combined microwave and optical data have been widely used to improve the accuracy of SSM retrievals. However, influence vegetation indices derived from red-edge spectral bands multi-spectral on retrieval has not sufficiently analyzed. In this study, we retrieved wheat-covered surfaces using Sentinel-1/2 data. First, modified water cloud model (WCM) was proposed remove backscattering coefficient radar The fraction (FV) then introduced in WCM, content (VWC) calculated multiple linear regression model. Subsequently, support vector technique retrieve SSM. This approach validated situ measurements wheat fields Hebi, located northern Henan Province, China. key findings study are: (1) Based obtained Sentinel-2 data, VWC estimation effectively eliminated vegetation; (2) Compared with vertical transmit horizontal receive (VH) polarization, (VV) polarization better for detecting changes phenological phases wheat; (3) indicates successfully area Sentinel-1