Soil Moisture Simulation Based On Remote Sensing And Ground Data In Watershed

Water is the key natural factor to restricting the construction of the natural vegetation. The natural vegetation in the Loess Plateau mainly depends on soil moisture, because water is buried deep underground, which is difficult to use by the vegetation. As the important factor in water balance and cycle and soil resource, soil moisture has received extensive research. Meanwhile, soil moisture is the main factor affecting the plant growth, vegetation restoration and soil erosion. Therefore, monitoring soil moisture has an important significance to the agricultural production and the rational use of land for the Loess Plateau.In this paper, based on Sangta village soil moisture sampling experimental area in Ansai County of Shaanxi Province, using Remote sensing digital image processing and GIS methods. At first, extracts Surface temperature (Ts) and Normalized difference vegetation index (NDVI) based on remote sensing. We can calculate the Temperature Vegetation Dryness Index (TVDI) by equation formed by Ts and NDVI. Second, establishes soil moisture retrieval model according to the relevance of TVDI and soil moisture. Using the terrain analysis capabilities of GIS, analyses the slope and land influence on soil moisture and extracts the Topographic Wetness Index based on the Xiannangou DEM. Checks the TVDI model utilizing other data not involved model inference. Taking into account the topographic fators influence on soil moisture, establishes an integrated model to inverse the soil moisture. At last, products soil moisture distribution according to the TVDI model and integrated model. Provide a feasible method collecting soil moisture content quickly. Furthermore, supplies the basic data for the soil erosion model.