Abstract
This paper presents the experiences obtained in the application of Principal Component Analysis (PCA) method to map hydrothermal minerals based on remotely sensed data. In this study, Sentinel-2B MultiSpectral Instrument (MSI) image is used to detect distribution of hydroxyl-bearing minerals in Vinh Phuc province, northern Vietnam. Four bands of Sentinel-2B image including blue band (band 2), Vegetation Red Edge band (band 8A) and SWIR bands (band 11 and 12) are used to calculate the Principal Components, then and then select the Principal Component, which containing provides information on the hydrothermal minerals information. The obtained results findings show that the methodology and data are effective in detecting and mapping hydrothermal mineralization.
Highlights
Vinh Phuc province comprises many types of minerals resources, including those with significant reserves such as building stone, granite, kaolin, sand, gravel, and clay
This study focuses on the application of Sentinel 2 MultiSpectral Instrument (MSI) data to detect and map hydroxylbearing minerals in Vinh Phuc province, northern Vietnam
Tab. 4 shows that the mines bearing hydroxylcontaining minerals such as Nhan Ly pegmatite mine, Dong Dao and Xuan Hoa sedimentary rock mines have been correctly mapped based on the Sentinel-2B MSI data using Principal Component Analysis (PCA) method
Summary
Vinh Phuc province comprises many types of minerals resources, including those with significant reserves such as building stone, granite, kaolin, sand, gravel, and clay. Hydrothermal Minerals mapping using based on remotely sensed data from Sentinel 2 sattelite: a case study in Vinh Phuc Province, Northern Vietnam. There are many technique based on band ratio and Principal Component Analysis (PCA) applicable to detecting and mapping distribution of minerals [2, 17].
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