Soil Moisture Retrievals Using Multi-Temporal Sentinel-1 Data over Nagqu Region of Tibetan Plateau

This paper presents an approach for retrieval of soil moisture in Nagqu region Tibetan Plateau using VV-polarized Sentinel-1 SAR and MODIS optical data, by coupling the semi-empirical Oh-2004 model Water Cloud Model (WCM). The Oh is first used to estimate surface roughness parameter based on hypothesis that invariant among acquisitions. Afterward, vegetation water content (VWC) WCM calculated from daily NDVI data obtained temporal interpolation. To improve performance model, parameters A, B, α are analyzed optimized randomly selected half sampled dataset. Then, retrieved minimizing a cost function between simulated measured backscattering coefficients. comparison with ground measurements shows determination coefficient R2 Root Mean Square Error (RMSE) 0.46 0.08 m3/m3, respectively. These results demonstrate capability reliability estimating over Plateau.