Remote Sensing techniques to Detect Areas with Potential for Lithium Prospection in Minas Gerais, Brazil

• Type: Article in International Conference Proceedings Book
• Date: 2019

Authors

Santos, D (Author) Other; Ana Teodoro (Author) FCUP; Alexandre Lima (Author) FCUP; Cardoso Fernandes, J (Author) Other

Conference proceedings International

Title: EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS X

SPIE Conference on Earth Resources and Environmental Remote Sensing/GIS Applications X held at SPIE Remote Sensing Conference

Strasbourg, FRANCE, SEP 10-12, 2019

Indexing

ISI Web of Knowledge - 9 Citations

Scopus - 20 Citations

Other information

Authenticus ID: P-00R-CGV

DOI: 10.1117/12.2532744

Abstract (EN): Lithium (Li) is defined as an alkaline metal which does not exist in nature in its free form. Moreover, it has properties that make it possible to be applied in several manners, such as industrial use, especially in the ceramic and glass industries, as well as the battery industry which has had an increase in this element consumption. It is crucial to use less expensive and faster techniques, compared to classical and intrusive methods, to identify new Li deposits. Remote sensing as proved to be a powerful tool to identify areas with potential for Li exploration. The objective of this work is to apply several images processing techniques, such as RGB band combinations, Band Ratios and Principal Components Analysis (PCA) to identify potential areas for Li prospection in the pegmatite district of Sao Joao Del Rei, located in the south of the state of Minas Gerais, Brazil. In these areas, two study zones were defined: the zone A, with approximately 323 km(2) in the pegmatite district of Sao Joao Del Rei and the zone B with approximately 90 km(2) in the pegmatite district of Aracuai. The results of the techniques applied in this study are very promising since, in addition to ease and low cost, these techniques can be applied to several locations. This approach is highly valuable for the Li mining industry.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17