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Mapping alteration zones in the Southern section of Yulong copper belt, Tibet using multi-source remote sensing data
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Methods for extracting mineralized alteration information using remote sensing images have recently become both efficient and cost-effective. Technology involving the extraction of alteration information based on multi-spectral data has been widely practiced and effectively verified. In recent years, research on fine mineral extraction methods based on hyperspectral data has also been rapidly developing. The Yulong copper belt is a porphyry copper belt located in China with high prospects for mineralization. However, most previous studies focused on the northern section of the Yulong copper belt, with limited exploration of the southern section. In this study, alteration information of the southern section of the Yulong copper belt was extracted from remote sensing data from Landsat-8 OLI, ASTER, and ZY1-02D, and the prospecting potential of this area was evaluated. Principal component analysis was used to extract iron oxide and hydroxyl alteration from Landsat-8 data, in addition to Al hydroxyl and propylitic alterations from ASTER data. Considering the challenge of the extraction of too many pseudo-anomalies using traditional methods, the mixture-tuned matched filtering (MTMF) method was used to more accurately extract iron oxide alterations. Regarding hyperspectral data, the minimum noise fraction and pure pixel index algorithms were used to extract white mica and carbonatite endmembers. The MTMF method was also used for alteration mapping, which took advantage of sub-pixel abundance mapping to finely divide the white mica and carbonatite alterations into five classes. The extraction results of multi-source remote sensing data were then compared and analyzed to avoid occasional single-image extraction results, which confirmed the superiority of the hyperspectral remote sensing and MTMF methods. Combined with field verification, the mineralization alteration information coincided with the spatial location of the Secuo, Mamupu, and Jicuo deposits, which confirmed the accuracy of alteration information extraction. The results of this study confirmed the application potential of remote sensing alteration information extraction in the field of mineral resource exploration. The results have important reference significance for further geological prospecting and exploration in the southern section of the Yulong copper belt.
Title: Mapping alteration zones in the Southern section of Yulong copper belt, Tibet using multi-source remote sensing data
Description:
Methods for extracting mineralized alteration information using remote sensing images have recently become both efficient and cost-effective.
Technology involving the extraction of alteration information based on multi-spectral data has been widely practiced and effectively verified.
In recent years, research on fine mineral extraction methods based on hyperspectral data has also been rapidly developing.
The Yulong copper belt is a porphyry copper belt located in China with high prospects for mineralization.
However, most previous studies focused on the northern section of the Yulong copper belt, with limited exploration of the southern section.
In this study, alteration information of the southern section of the Yulong copper belt was extracted from remote sensing data from Landsat-8 OLI, ASTER, and ZY1-02D, and the prospecting potential of this area was evaluated.
Principal component analysis was used to extract iron oxide and hydroxyl alteration from Landsat-8 data, in addition to Al hydroxyl and propylitic alterations from ASTER data.
Considering the challenge of the extraction of too many pseudo-anomalies using traditional methods, the mixture-tuned matched filtering (MTMF) method was used to more accurately extract iron oxide alterations.
Regarding hyperspectral data, the minimum noise fraction and pure pixel index algorithms were used to extract white mica and carbonatite endmembers.
The MTMF method was also used for alteration mapping, which took advantage of sub-pixel abundance mapping to finely divide the white mica and carbonatite alterations into five classes.
The extraction results of multi-source remote sensing data were then compared and analyzed to avoid occasional single-image extraction results, which confirmed the superiority of the hyperspectral remote sensing and MTMF methods.
Combined with field verification, the mineralization alteration information coincided with the spatial location of the Secuo, Mamupu, and Jicuo deposits, which confirmed the accuracy of alteration information extraction.
The results of this study confirmed the application potential of remote sensing alteration information extraction in the field of mineral resource exploration.
The results have important reference significance for further geological prospecting and exploration in the southern section of the Yulong copper belt.
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