Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region
Porphyry copper ore is a vital strategic mineral resource. It is often associated with significant hydrothermal alteration, which alters the original mineralogical properties of the rock. Extracting alteration information from remote sensing data is crucial for porphyry copper exploration. However,...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/13/4/501 |
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| author | Chunhui Liu Chunxia Qiu Luoqi Wang Jie Feng Sensen Wu Yuanyuan Wang |
| author_facet | Chunhui Liu Chunxia Qiu Luoqi Wang Jie Feng Sensen Wu Yuanyuan Wang |
| author_sort | Chunhui Liu |
| collection | DOAJ |
| description | Porphyry copper ore is a vital strategic mineral resource. It is often associated with significant hydrothermal alteration, which alters the original mineralogical properties of the rock. Extracting alteration information from remote sensing data is crucial for porphyry copper exploration. However, the current method of extracting hydrothermal alteration information from ASTER remote sensing data does not consider the influence of disturbing factors, such as topography, and ignores the weak report of surface minerals, which has significant limitations. Therefore, this paper selects the Gondwana region of the East Tethys–Himalayan tectonic domain as the study area, combines waveform calculation with principal component analysis methods, proposes a spectral feature-enhanced principal component analysis (EPCA) method, and constructs a model to complete the automatic selection of principal components for each scene image. The results show that the etching information extracted by the EPCA method is significantly better than the traditional Crosta method in terms of etching area and spatial aggregation and discovers several prospective mineralization areas that have not yet been explored and exploited, such as Sakya and Xietongmen counties in Rikaze, providing theoretical support for subsequent mineralization exploration and large-scale mineral extraction. Meanwhile, obtaining the alteration information of the whole area can help to understand the distribution of mineralizing elements from a macroscopic perspective in the future, which is of great scientific significance in order to deeply analyze the formation process of metal deposits in mineralizing areas and improve the theory of porphyry mineralization. |
| first_indexed | 2024-03-11T04:42:11Z |
| format | Article |
| id | doaj.art-0dddb5e019bc4061a70387f0d665a73b |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-11T04:42:11Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-0dddb5e019bc4061a70387f0d665a73b2023-11-17T20:35:34ZengMDPI AGMinerals2075-163X2023-03-0113450110.3390/min13040501Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana RegionChunhui Liu0Chunxia Qiu1Luoqi Wang2Jie Feng3Sensen Wu4Yuanyuan Wang5College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, ChinaSchool of Earth Sciences, ZheJiang University, Hangzhou 310027, ChinaSchool of Earth Sciences, ZheJiang University, Hangzhou 310027, ChinaSchool of Earth Sciences, ZheJiang University, Hangzhou 310027, ChinaZhejiang Provincial Key Laboratory of Geographic Information Science, Hangzhou 310028, ChinaPorphyry copper ore is a vital strategic mineral resource. It is often associated with significant hydrothermal alteration, which alters the original mineralogical properties of the rock. Extracting alteration information from remote sensing data is crucial for porphyry copper exploration. However, the current method of extracting hydrothermal alteration information from ASTER remote sensing data does not consider the influence of disturbing factors, such as topography, and ignores the weak report of surface minerals, which has significant limitations. Therefore, this paper selects the Gondwana region of the East Tethys–Himalayan tectonic domain as the study area, combines waveform calculation with principal component analysis methods, proposes a spectral feature-enhanced principal component analysis (EPCA) method, and constructs a model to complete the automatic selection of principal components for each scene image. The results show that the etching information extracted by the EPCA method is significantly better than the traditional Crosta method in terms of etching area and spatial aggregation and discovers several prospective mineralization areas that have not yet been explored and exploited, such as Sakya and Xietongmen counties in Rikaze, providing theoretical support for subsequent mineralization exploration and large-scale mineral extraction. Meanwhile, obtaining the alteration information of the whole area can help to understand the distribution of mineralizing elements from a macroscopic perspective in the future, which is of great scientific significance in order to deeply analyze the formation process of metal deposits in mineralizing areas and improve the theory of porphyry mineralization.https://www.mdpi.com/2075-163X/13/4/501Gondwana regionhydrothermal alterationporphyry copper orespectral feature enhancementprincipal component analysis |
| spellingShingle | Chunhui Liu Chunxia Qiu Luoqi Wang Jie Feng Sensen Wu Yuanyuan Wang Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region Minerals Gondwana region hydrothermal alteration porphyry copper ore spectral feature enhancement principal component analysis |
| title | Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region |
| title_full | Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region |
| title_fullStr | Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region |
| title_full_unstemmed | Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region |
| title_short | Application of ASTER Remote Sensing Data to Porphyry Copper Exploration in the Gondwana Region |
| title_sort | application of aster remote sensing data to porphyry copper exploration in the gondwana region |
| topic | Gondwana region hydrothermal alteration porphyry copper ore spectral feature enhancement principal component analysis |
| url | https://www.mdpi.com/2075-163X/13/4/501 |
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