2024 Vol. 51, No. 3
Article Contents

BAI Longyang, DAI Jingjing, WANG Nan, LI Baolong, LIU Zhibo, LI Zhijun, CHEN Wei. 2024. Extraction of mineral alteration information and mineralization prospecting analysis based on GF−5 hyperspectral in Zhule−Mangla, Tibet[J]. Geology in China, 51(3): 995-1007. doi: 10.12029/gc20220701002
Citation: BAI Longyang, DAI Jingjing, WANG Nan, LI Baolong, LIU Zhibo, LI Zhijun, CHEN Wei. 2024. Extraction of mineral alteration information and mineralization prospecting analysis based on GF−5 hyperspectral in Zhule−Mangla, Tibet[J]. Geology in China, 51(3): 995-1007. doi: 10.12029/gc20220701002

Extraction of mineral alteration information and mineralization prospecting analysis based on GF−5 hyperspectral in Zhule−Mangla, Tibet

    Fund Project: Supported by National Key Research and Development Program of China (No.2022YFC2905001), the projects of China Geological Survey (No.DD20230054, No.DD20230033), the Scientific Examinations of Bulk Metal Resources on Qinghai−Tibet Plateau, the National Major Research Program of Science and Technology (No.2021QZKK0304), National Natural Science Foundation of China (No.42172332) and the Basic Research Projects of the Institute of Mineral Resources, Chinese Academy of Geological Sciences (No.KK2102).
More Information
  • Author Bio: BAI Longyang, female, born in 2000, master candidate, majors in earth exploration and information technology; E-mail: bailongyang111@163.com
  • Corresponding author: DAI Jingjing, female, born in 1982, researcher, engaged in the research of remote sensing geology; E-mail: daijingjing863@sina.com
  • This paper is the result of mineral exploration engineering.

    Objective

    Remote sensing has been widely used in geological survey and mineral exploration in recent years. Alteration mineral mapping using multispectral remote sensing data provides important technical support for geological prospecting. However, only a limited number of surveys were carried out based on the Chinese hyperspectral remote sensing data. The smaller spectral interval of the GaoFen−5 (GF−5) hyperspectral remote sensing data provides a richer spectral information of geological targets than multispectral data, which offers an ideal data source for mineral identification. This paper was mainly focusing on the extraction of alteration minerals based on GF−5 data in the south of Geji, Tibet. Moreover, the alteration minerals extracted from GF−5 were overlaid and compared with the results extracted from Landsat−8 and ASTER data. The results were verified by field survey, which could deepen the application of remote sensing in mineral resources investigation.

    Methods

    A spectral index model for different alteration minerals was proposed based on the multispectral data. During the extraction of alteration information from GF−5 data, traditional methods such as spectral angle mapper were abandoned, while the decision tree algorithm was adopted to support mixture tuned matched filter for the extraction of mineralized alteration information. Finally, regional structure, alteration information and other factors were integrated to delineate mineralization anomalous targets. The field investigation was carried out to verify the technical reliability.

    Results

    The information of iron−stained, hydroxyl (Mg−OH, Al−OH) and carbonate minerals was enhanced and extracted using Landsat−8 and ASTER. Eight alteration minerals including calcite, paragonite, muscovite, phengite, alunite, kaolinite, dickite and chlorite were identified by GF−5.

    Conclusions

    Combined with the extraction and superimposition results from different data sources, the reliability of the mineralization alteration information extraction method proposed in this paper was confirmed. The field investigation results showed that the area is characterized by high−sulfur epithermal alteration mineral assemblage, which has the potential for porphyry−epithermal hydrothermal deposit. It is suggested that the combination of hyperspectral and multispectral could help the subsequent analysis of alteration zonation and provide accurate mineralization prediction for prospecting, so as to serve the sector of mineral exploration engineering.

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