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REMOTE SENSING FOR LAND & RESOURCES    2014, Vol. 26 Issue (4) : 187-194     DOI: 10.6046/gtzyyg.2014.04.29
Technology Application |
Remote sensing geological features and ore prediction in Lengshuigou, Zhashui County, Shaanxi Province
ZHANG Yunfeng1, JIAO Chaowei1, LI Jianbin2, REN Tao2, ZHANG Xishe2
1. Northwest Nonferrous Geological Research Institute, Xi'an 710054, China;
2. No. 713 Geological Party, Northwest Bureau of Mining and Geology for Nonferrous Metals, Shangluo 726000, China
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Abstract  Located in Zhashui County of Shaanxi Province, the Lengshuigou polymetallic concentration area is rich in mineral resources related to intermediate-acid small intrusive bodies. In order to get a breakthrough of mineral exploration, the authors carried out large-scale geological survey of remote sensing based on high resolution and hyperspectral data, such as WorldView-I and ASTER. According to the survey results, four kinds of intrusive bodies with different lithologies and three types of linear structures as well as circular structures were interpreted from remote sensing images. Based on the classification of the altered minerals and analysis of the features of spectra, the authors extracted two kinds of remote sensing anomalies related to skarnization by using principal component analysis. The remote sensing geological features show that there exists a relatively large magmatic dome at the depth of the Lengshuigou body, that hidden rock bodies are distributed around the dome, and that ore-forming information of remote sensing anomalies is very obvious. Through a comprehensive analysis, two prospecting targets of remote sensing were delineated in the study area.
Keywords ZY-3      Landsat8      spectral information      spatial information      image fusion      quality evaluation     
:  TP79  
Issue Date: 17 September 2014
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LIU Huifen
YANG Yingbao
YU Shuang
KONG Lingting
ZHANG Yong
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LIU Huifen,YANG Yingbao,YU Shuang, et al. Remote sensing geological features and ore prediction in Lengshuigou, Zhashui County, Shaanxi Province[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(4): 187-194.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2014.04.29     OR     https://www.gtzyyg.com/EN/Y2014/V26/I4/187
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