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Global Geology 2022, 25(1) 16-25 DOI:
ISSN: 1673-9736 CN: 22-1371/P |
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Extraction of altered minerals from Aster remote sensing data in Gongchangling iron deposit of Liaoning, China |
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LUAN Yiming, HE Jinxin, DONG Yongsheng, JIANG Tian and XIAO Zhiqiang |
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College of Earth Sciences, Jilin University, Changchun 130061, China |
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Abstract:
The precision of Aster data is higher than that of Landsat series of multispectral remote
sensing data, which can more accurately reveal the distribution of altered minerals. It plays an important role in prospecting, but it is rarely used in areas with complex terrain and high vegetation coverage. Based on this purpose, this study used Aster remote sensing data, and took Gongchangling iron deposit as a case study. It combined the mineral spectrum theory and the basic geologic data of the study area, using the model of principal component analysis (PCA) and color synthesis to extract abnormal altered minerals. The results show that the distribution of identified anomalies is basically consistent with the existing geological data in this study area, which provides a reliable reference for the mineral resources ex-ploration and delineation of mining areas. |
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Keywords:
multispectral remote sensing
Aster data
principal component analysis
color synthesis
Gongchangling iron deposit
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