期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B6b
页码：297-300
出版社：Copernicus Publications
摘要：Soil Desertification has severely threatened inner stability and sustainable development in arid areas, so extracting soil desertification information based on remote sensing and mastering its spatial distribution are of important practical significance. In this article, taking the Mu Us sand land as a case study, utilizing CBERS-02B including CCD data and HR data, the approach of effective remote-sensing information extraction for soil desertification in arid areas based on principal component fusion and SVM is discussed. Firstly, two dimensional discrete stationary wavelet transform combined average filter processing is presented to improve the image quality. Then principal component fusion and SVM classification were used to extract soil desertification information. Finally, the kernel type of radial basis function was selected and comparing the classification results in SVM classification with maximum likelihood classification and minimum distance classification qualitatively and quantitatively in terms of classification accuracy. The results suggest that the method is effective and the precision of this approach is very high, so it is an effective method for monitoring soil desertification changes utilizing CBERS-02B data in arid area
