Soil moisture estimation at various growth stages of winter wheat based on ASAR data

In this study, the relationship between Advanced Synthetic Aperture Radar (ASAR) data and soil moisture was studied using correlation analysis. The empirical and semi-empirical approaches were used to develop the soil moisture estimation models based on ASAR data. Some conclusions were drawn. Firstly, winter wheat crown scattering influenced the sounding depth of ASAR. The optional depths for monitoring the soil moisture by ASAR were 0-20 cm and 0-5 cm for before the erecting stage and after the jointing stage, respectively. Secondly, since ASAR data at VV polarization and low incidence angle had significant linear correlations with soil moisture, the empirical models were suitable to estimate soil moisture before the jointing stage; however, when winter wheat crown was dense (at the earing stage), the empirical model could not be applied to retrieve soil moisture with a high accuracy. Then, multi-angle ASAR data were used to develop a semi-empirical model to retrieve soil moisture with a higher accuracy. Finally, the soil moisture estimation models developed in this study were employed to estimate soil moisture, the Root Mean Squared Error of estimated soil moisture were 0.0125, 0.0247 and 0.0298 g/g, respectively.