To obtain the spatiotemporal characteristics of soil moisture in Anhui Province, the Kriging method was firstly used to interpolate the in-situ observed and multilayer soil moisture to gridded data. Then, the spatiotemporal variability of soil moisture across this region was analyzed. A Back Propagation(BP)neural network optimized by the genetic algorithm was established to retrieve the soil moisture using the brightness temperature measured by the Fengyun 3B satellite. The results show that soil moisture across Anhui Province shows high temporal fluctuations. And, the soil moisture in the Huaibei plain and the Dabie Mountains is lower than the other regions. As depth becomes deeper, soil moisture has a higher value with lower seasonal and horizontal variability. The correlation between retrieved and observed daily gridded values across the five sub-regions is 0. 605, while the corresponding root mean square error is 0. 056 m³/m³. Clearly, the proposed retrieval algorithm is able to capture the spatiotemporal variability of soil moisture in Anhui Province.