Abstract: The importance of monitoring soil moisture of the cultivated land in the spring is discussed and the current several major inversion methods of soil moisture content is analyzed comparatively in this paper. In order to improve the soil moisture monitoring accuracy of the cultivated land, a new soil moisture content (SMC) inversion algorithm is proposed based on the analysis of soil emissivity database simulated by AIEM model. This new inversion algorithm and coefficient of the parameterized model developed by us can apply to most of the natural terrain. The soil moisture and roughness can be retrieved by using dual-polarized microwave brightness temperature data of 47 observing angle ancillary the soil temperature products retrieved from thermal infrared remote sensing data. Though initial verification, the new algorithm shows high inversion accuracy and the inversion accuracy of SMC and soil roughness are 0.0148 and 0.0461 respectively.