A physically-based algorithm for surface soil moisture retrieval in the Tibet Plateau using passive microwave remote sensing

Abstract

A physically-based algorithm for surface soil moisture retrieval in the Tibetan Plateau using passive microwave remote sensing was presented. The algorithm is based on a radiative transfer model and the assumption that the vegetation optical depth is polarization independent. It combines the effects of vegetation and roughness as a single parameter and uses the microwave polarization difference index (MPDI) to eliminate the effects of surface temperature and obtain soil moisture through a nonlinear iterative procedure. The advantage of this algorithm is that it needs only one frequency brightness temperature observations, and requires no field observations of roughness, soil moisture or vegetation data sets during the whole retrieval process. Finally, the algorithm was tested with the 6.9 GHz dual-polarized brightness temperature data from the Advanced Microwave Scanning Radiometer (AMSR-E) and compared with NASA official algorithm using in situ soil moisture from 20 stations in the Tibetan Plateau. The results show that the soil moisture retrieved by the algorithm is more consistent with ground measurements than the NASA soil moisture products.