Karst rocky desertification is a significant environmental and ecological problem in Southwest China. In this paper, the
spectral information, spatial context and topography information were utilized to synthetically discriminate the Karst
rocky desertification degree, which are derived from The SPOT satellite imagery and DEM. By the back-propagation
neural network, we proposed the classification model structure and classified the rocky desertification levels in Du'an
County of Guangxi province, China. The results verified the classification model of Karst rocky desertification degree is
efficient and accurate.
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