Basin soil type, moisture content and vegetation cover index are important factors affecting the basin water of Yongding River, using traditional sampling method to investigate soil moisture and the watershed soil type not only consuming a lot of manpower and material resources but also causing experimental error because of the instrument and other objective factors. This article selecting the Yongding River Basin-Beijing section as the study area, using total station instruments to survey field sampling and determination 34 plots, combined with 6 TM image data from 1978 to 2009 to extract soil information and the relationship between region’s soil type, soil moisture and remote sensing factors. Using genetic algorithms normalization to select key factors which influenced NDWI, which is based on the green band and near-infrared bands normalized ratio index, usually used to extract water information in the image. In order to accurate screening and factors related to soil moisture, using genetic algorithms preferred characteristics, accelerate the convergence by controlling the number of iterations to filter key factor. Using multiple regression method to establish NDWI inversion model, which analysis the accuracy of model is 0.987, also use the species outside edges tree to meet accuracy test, which arrived that soil available nitrogen, phosphorus and potassium content and longitude correlation is not obvious, but a positive correlation with latitude and soil, inner precision researched 87.6% when the number of iterations to achieve optimal model calculation Maxgen. Models between NDWI and vegetation cover, topography, climate ect, through remote sensing and field survey methods could calculate the NDWI values compared with the traditional values, arrived the average relative error E is -0.021%, suits accord P reached 87.54%. The establishment of this model will be provide better practical and theoretical basis to the research and analysis of the watershed soil moisture and organic of Yongding River.