The surface moisture is one of the most important parameters in modeling water-plant coupled land surface processes and land-air coupled climatic systems. The use of remotely sensed data is potentially of great interest in such a context. Several methods have been proposed to estimate soil moisture conditions, but the limitations of these methods are obvious. In this study, we developed a method to detect soil moisture condition using surface temperature (Ts) and vegetation index (NDVI) derived from Landsat ETM+ data. We then applied this method to the semiarid area and mapped out the spatial distribution of soil moisture. We further compared the soil moisture distribution with the spatial distribution of desertification and found that desertification in semiarid area exerts a great effect on soil moisture conditions.