Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites |
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| Institution: | 1. Dep. of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto, Rua do Campo Alegre, Porto, Portugal;2. ICT (Institute of Earth Sciences) – Porto pole, Portugal;1. IANIGLA, CCT-CONICET, Mendoza. Av. Ruiz Leal s/n, 5500, Mendoza, Argentina;2. Mineralogía y Petrología, FAD, Universidad Nacional de Cuyo, Centro Universitario, 5502, Mendoza, Argentina;3. Departamento de Geología, Universidad Nacional de San Luis, Ejército de los Andes 950, San Luis, 5700, Argentina;4. CeReDeTeC, Facultad Regional Mendoza, Universidad Tecnológica Nacional, Coronel Rodríguez 273, 5502, Mendoza, Argentina;1. Department of Geology, Federal University of Pernambuco, Av. da Arquitetura, s/n, 50740-550, Recife-Pernambuco, Brazil;2. Institute of Geosciences, University of Campinas, PO Box 6152, 13083-870, Campinas, São Paulo, Brazil;3. Institute of Geosciences, University of Brasília, Campus Universitário Darcy Ribeiro s/n, Asa Norte, 70910-900, Brasília, Distrito Federal, Brazil;1. Department of Earth Sciences, Stellenbosch University, Private Bag X1, Matieland, 7602, South Africa;2. Council for Geoscience, P.O. Box, 572, Bellville, 7535, South Africa |
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| Abstract: | Remote sensing has proved to be a powerful resource in geology capable of delineating target exploration areas for several deposit types. Only recently, these methodologies have been used for the detection of lithium (Li)-bearing pegmatites. This happened because of the growing importance and demand of Li for the construction of Li-ion batteries for electric cars. The objective of this study was to develop innovative and effective remote sensing methodologies capable of identifying Li-pegmatites through alteration mapping and through the direct identification of Li-bearing minerals. For that, cloud free Landsat-5, Landsat-8, Sentinel-2 and ASTER images with low vegetation coverage were used. The image processing methods included: RGB (red, green, blue) combinations, band ratios and selective principal component analysis (PCA). The study area of this work is the Fregeneda (Salamanca, Spain)-Almendra (Vila Nova de Foz Côa, Portugal) region, where different known types of Li-pegmatites have been mapped. This study proposes new RGB combinations, band ratios and subsets for selective PCA capable of differentiating the spectral signatures of the Li-bearing pegmatites from the spectral signatures of the host rocks. The potential and limitations of the methodologies proposed are discussed, but overall there is a great potential for the identification of Li-bearing pegmatites using remote sensing. The results obtained could be improved using sensors with a better spatial and spectral resolution. |
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| Keywords: | Lithium RGB combinations Band ratio PCA Alteration halos ASTER Landsat-5 Landsat-8 Sentinel-2 |
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