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Remote Sensing Technology and Application
    
Remote Sensing Prospecting in High Vegetation Coverage Area——A Case Study of the in Datuanbao Copper Ore Deposit
Zhao Xiaoxing1,2,Qian Jianping1,Qin Shunqiao1,Huang Kechen1,Han Shuai1
(1.College of Earth Science,Guilin University of Technology,Guilin 541004,China; 2.Fujian Institute of Geological Survey,Fuzhou 350013,China)
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Abstract  This article described the way to extract information of copper and lead anomaly in high vegetation coverage area through a case study from the Datuanbao copper ore deposit and its environs,Jiangcheng,Yunnan Province.Principal component analysis,false color composite,stretch Histogram and supervise classification etc were analyzed in the remote sensing images using ENVI4.6 software.It is suggested that the linear structure,which is delineated by convolution filter and morphological analysis method,is characterized by statistical self-similarity and fractal geometry.It is found that the high value of fractal dimension is roughly coincident with the copper and lead anomaly of vegetation by the comparison between contour maps of plant geochemical anomaly and fractal dimensions,which is calculated by box-counting.As a matter of fact,80 percent of copper and lead deposits or occurrences are located in areas of high value of fractal dimension and vegetation anomaly.By the comprehensive analysis of stratigraphy,igneous rocks,copper and lead mineralizations,fractal dimension of linear structures and vegetation anomaly from remote sensing,nine exploration targets with three levels of probabilities are figured out.
Key words:  ETM+ remote sensing      Linear structure interpretation      Extraction of plant geochemical anomaly      Metallogenic prognosis     
Received:  05 August 2012      Published:  14 March 2014
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Zhao Xiaoxing
Qian Jianping
Qin Shunqiao
Huang Kechen
Han Shuai

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Zhao Xiaoxing,Qian Jianping,Qin Shunqiao,Huang Kechen,Han Shuai. Remote Sensing Prospecting in High Vegetation Coverage Area——A Case Study of the in Datuanbao Copper Ore Deposit. Remote Sensing Technology and Application, 2013, 28(5): 879-889.

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http://www.rsta.ac.cn/EN/     OR     http://www.rsta.ac.cn/EN/Y2013/V28/I5/879

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