The Extraction Of Soil Moisture Information Based On Landsat ETM Remote Sensing Data In Coal Mining Zone Of Daliuta

The soil moisture is a major index to monitor the soil quality,in the meantime, the condition of soil moisture is one of indicative factor of Eco-environment statement of health.Traditional monitor method of the soil moisture has certain limitations.With the development of the technology of the RS and GIS, using the technology of RS and combining the analysis function of GIS, we can effectively carry out the real-time soil moisture dynamics of large-scale monitoring.It's very meaningful for Environmental protection and rebuilding.This paper using the RS date from Landsat ETM,combining the date of the field survey and the spectral data, do a research of RS quantitative analysis on the soil moisture in Daliuta mining area in northern Shaanxi province, retrieval the distribution of water content of soil in this area. This not only can provide parameters for the loss of soil water study, but also provide decision parameters for economic development and environment protection in this area.1.The spectral characteristics of soil moisture in Shenmu county;2.The relational model of the soil spectral reflectance and the soil water content;3.The processing method of the soil RS information;4.The RS quantitative analysis model of the soil moisture;5.The distribution characteristics of the soil moisture;By the correlation analysis of soil spectral reflectance and the soil moisture messured from the field, this research show that the soil spectral reflectance is lowering with the raising of the soil water content, and the both is negative correlation. This is follow the general rule; Using the RS reflectance(R2,R3 and R4) of ETM2,ETM3 and ETM4 and the tested soil water content, relationship model were built respectively. It shows that the exponential model of ETM4 is very sensitive to soil moisture; Using the optics vegetation coverage model to remove the vegetation coverage interference, which is resulted from vegetation coverage monitoring the soil moisture with RS method; Using the exponential model of ETM4: S=5.84705e"00144*B4 for retrieval, the average absolute error of result is 0.206667, the average relative error is 15.46144%; According to the retrieval model and ETM image of this area, soil moisture was estimated, and distribution rank chart was made which intuitively displayed the distribution rule of soil moisture; At mean time, taking advantage of the NDVI to classify the vegetation coverage, the result shows that the retrieval result and the vegetation demonstrate a definite positive correlation, and the result match up the practical situation.