Potential of Sentinel-2 data in the detection of lithium (Li)-bearing pegmatites: a study case

Abstract

Only recently remotely sensed data and image processing techniques have been used in the detection of lithium (Li)-bearing pegmatites because of the current growing importance and demand of Li for the construction of Li-ion batteries for electric cars. The study area of this work was the Fregeneda (Spain)-Almendra (Portugal) region, where different known types of Li-pegmatites have been mapped. The objective of this study is to develop a methodology considering remotely sensed data, capable of identifying Li-pegmatites based on the recognition of the associated alteration halos. For that, Level 1-C cloud free Sentinel-2 images with low vegetation coverage were used. The normalized difference vegetation index (NDVI) was computed and a threshold was considered (NDVI<0.2). This study also aims exploiting the potential of Sentinel-2 data for this purpose. Minerals have important absorption features in the visible and infrared regions. Based on these features and with the aim of determining the most accurate methodology, Sentinel-2 reflectance data was used to compute RGB combinations, band ratios, principal component analysis (PCA) and image classification (supervised). These methodologies allow to predict the occurrence of iron oxides and clay minerals, and to discriminate between non-altered and hydrothermally altered zones. Band ratio 3/8 also predicts the occurrence of Li-bearing minerals. The results of the application of remote sensing data, in particular, Sentinel-2 images and image processing techniques to Li-mineralizations is of great interest to mining companies since they could lead to an increased efficiency and sustainability of mineral exploration.