Automatic Extraction of Karst Landscape Elements Based on SPOT 5 Image
YANG Shu-wen1, XIE Fei1, FENG Guang-sheng2, LIU Tao1
1. School of Mathematics, Physics & Software Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. Fourth Survey and Design Institute of China Railway, Wuhan 430063, China
Abstract：To study the geographical features and image features of peak-cluster, peak-forest and karst depression, this paper puts forward some remote sensing indices based on background values of remote sensing images, such as vegetation index, soil brightness index,and PC1 of principal component transformation of the image and terrain data. Meanwhile,the integrated calculation method of remote sensing indices is proposed, and the automatic extraction model of remote sensing is created. The integrated calculation method of the indices could effectively increase spectral differences between peak-cluster, peak-forest and other surface features. The gray values of peak-cluster and peak-forest are the highest in the image so as to obtain segmenting value for accurate extraction of them based on automatic selection algorithm of threshold. Based on automatic extraction model of remote sensing,this paper puts forward some information of peak-cluster and peak-forest. On such a basis,karst depression information is extracted. Experimental studies show that the method has high accuracy and efficiency of extraction.
杨树文, 谢飞, 冯光胜, 刘涛. 基于SPOT 5图像的岩溶地貌单元自动提取方法[J]. 国土资源遥感, 2012, 24(2): 56-60.
YANG Shu-wen, XIE Fei, FENG Guang-sheng, LIU Tao. Automatic Extraction of Karst Landscape Elements Based on SPOT 5 Image. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(2): 56-60.
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2012, Vol. 24 
