Soil salination often occurs in these area,where the climate is drought,the soil's evaporation is very intensity,and the water table is high and contain high dissolubility salt.It was occurred by certain climate, terrain, and hydrogeology, and they together influenced the water and salt movement. At the present time, soil salinization and secondary salinization have been an basilic issue of entironment, that influence the production of industrial and agricultural seriously. Then comprehending these factors by the way of general-purpose has a great sense of making reasonable measures to develop the governance.Oasis of Ugan-Kuqa River Delta was selected for this study,located in the North of Tarim Basin. Imformation of soil salinization, Vegetation and soil moisture were extracted by the model of LSMM and MPDI based on TM and ETM+. Through experiment and theoretical reasoning, the research proposed conception of swc-sf 2-D feature space, swc-vf 2-D feature space and vf-sf 2-D feature space and discussed those biophysical characteristics. Analysis revealed that location could be used to improve the current strategies for salinization in the 2-D feature space.Therefore , the research presented models of SSSI,SVSI and VSSI to monitor severity of salinization. The models of SVWSI and SDI, based on 3-D feature space, demonstrate a much better performance in surface soil salinity, compared to the 2-D model of soil salinization. Correlation coefficients between models of SSSI, SVSI, VSSI and soil salinity were obtained and were adjusted to predict soil salinity. It is evident from the results that SVWSI and SDI are highly accordant with in-situ soil SAL values with the highly correlation of 0.8325, 0.8646.Therefore, developing of simple, effective and operational methods for the satellite estimation of surface salnity, especially vegetation cover is of great interest for both researchers in remote sensing community and policy makers for the sustainable development of eco-environments.
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