Automatic Extraction of Karst Landscape Elements Based on SPOT 5 Image

doi:10.6046/gtzyyg.2012.02.11

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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.

Keywords Ningxia miner resource potential evaluation structural characteristics alteration information

TP 751.1

Issue Date: 03 June 2012

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	ZHANG Yong-ting
	ZHANG Xiao-dong
	LIU Zi-zeng
	ZHANG Yong-jie
	ZHANG Hui-juan

Cite this article:

ZHANG Yong-ting,ZHANG Xiao-dong,LIU Zi-zeng, et al. Automatic Extraction of Karst Landscape Elements Based on SPOT 5 Image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2012, 24(2): 56-60.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2012.02.11 OR https://www.gtzyyg.com/EN/Y2012/V24/I2/56

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