Open AccessHydrothermal Minerals Mapping using based on Remotely Sensed Data from Sentinel 2 Sattelite: a Case Study in Vinh Phuc Province, Northern Vietnam
Author(s) -
Trịnh Lê Hùng
Publication year - 2020
Publication title -
gornye nauki i tehnologii
Language(s) - English
Resource type - Journals
ISSN - 2500-0632
DOI - 10.17073/2500-0632-2019-4-309-317
Subject(s) - hydrothermal circulation , principal component analysis , remote sensing , multispectral image , multispectral pattern recognition , mineralogy , geology , mineralization (soil science) , computer science , artificial intelligence , soil science , paleontology , soil water
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.