Hydrothermal Alteration Zones Mapping Using Sentinel 2 MSI and Terra Aster Data in The Uruguay Mine, Minas do Camaquã District

Abstract

Objective: This work has as main objective to evaluate the usage of data from the Terra ASTER multispectral sensor, as well as data from Sentinel 2 MSI for the identification of hydrothermal alteration zones in the Uruguay Mine. Another objective of this work was to map a not-so-great scale deposit that present a hydrothermal pattern associated in a tropical country.   Method: Were applied principal component analysis and entropy analysis technique to the ASTER surface reflectance data and principal components only to the surface reflectance MSI data. The field spectra provided were obtained with the ASD FieldSpec-3 High-Resolution spectroradiometer. The samples collected contained spectral features characteristic of minerals such as ferric chlorite, hematite, goethite and illite (Phengite).   Result and Conclusion: The ASTER data resulted in a good radial highlighted pattern at the mine location indicating that the processing was able to map the target spectral patterns. The MSI data were processed to map the ferric minerals and presented a pattern highlighting the mine contours and slopes, demonstrating the possible occurrence of minerals containing the aimed spectral features. The entropy usage as an intensity factor applied to intensity-hue-saturation (IHS) fusion on ASTER data improved the reliability of the results, by highlighting the pixels with deepest absorbance features, reducing the uncertainty associated with the process. The results were considered good since both processes showed correspondence in the location of the mine.   Implication of the research: This work contributes for the understanding of spectroscopy analysis of alteration minerals related to copper mineralization, and techniques of remote sensing to map them.   Originality/value: Good results of the application of principal component analysis in the studied area and application of entropy concept in spectral analysis.