Crop drought is a terrible agricultural disaster across the globe, which has been widely studied with remote sensing optical data. However, soil moisture, a key parameter in crop drought monitoring which was hard for optical remote sensing data to estimate. SAR (Synthetic Aperture Radar) observation system is very sensitive to moisture in the soil, more importantly, the microwave which SAR systems used could penetrate the crop canopy into the soil. Water Cloud Model (WCM) is a common method of estimating soil moisture, which needs descriptor of the canopy. In order to reduce descriptor of the canopy error in the WCM, crop parameters are instead by Radar Vegetation Index (RVI). A new method was proposed to soil moisture estimation and application based on WCM and bare soil model. In the new model, crop parameter input ware replaced by RVI, which was calculated by Radarsat-2 SAR data. The result shows a good performance with no crop parameter was used.
['Jibo Yue', 'Guijun Yang', 'Xiudong Qi', 'Yanjie Wang']
Soil moisture retrieval in well covered farmland by Radarsat-2 SAR data