Abstract
It is very important to extract various kinds of underlying surfaces for soil erosion model because of various contributions of soil,vegetation,desert and rock under the same natural condition.Currently,traditional classification and information extraction methods based on remote sensing data have been widely applied in eco-hydrologic process field.But due to similarity and complexity of spectrums of soil,rock and desert,it was hard to distinguish soil,desert and rock in the same area.Rock land mountain,desert and soil mountain are widely distributed in the middle and upper reaches of Yellow River basin.In this paper,real spectrums of rock,soil and desert measured in lab using ASD(Analysis Spectrum Device) are analyzed,the result indicates that they could be well distinguished.On account of complex topographic changes and underlying surface roughness,spectrums from Landsat TM 5 become more complex and uncertain,but characteristics of surface texture of the rock land mountain are obvious and could be well differentiated from that of soil mountain and desert.For problem-solving of spectral complexity,normalized spectral index(NSI) is presented: NSI=(R4+R3+R2-3×R1)/(R5-R1)(R1,R2,R3,R4 and R5 individually refer to reflectance of the Langsat TM bands from 1 to 5).Then,the rock land mountain index(RMI) is presented according to the characteristics of normalized spectral index and texture: RMI=(R4+R3+R2-3×R1)/(R5-R1)+Rt(Rt refers to homogeneity index of texture),and the result indicates that information extraction precision of rock land mountain is 82.7% through set of threshold.Finally,we analyze spectral normalized spectral information of desert and soil and establish desert-exposed soil difference model(DS-Def): =DS-Def=(R4-R1)/(R5-R1)+R1+R2,and the result indicates that desert information extraction precision is 73.1%,and that of exposed soil is 72.8%.The above results indicate that the information extraction precision is higher than that by methods of traditional classification.
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