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Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites

机译:锂(LI)勘探中的遥感数据:一种检测LI-轴承钉脓的新方法

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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 Coa, 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.
机译:已经证明,遥感证明是能够划算几种存款类型的地质学中的强大资源。只有最近,这些方法已被用于检测锂(Li) - Bearing Pegmatites。这发生了,因为LI越来越重要和需求,用于建造电动汽车的锂离子电池。本研究的目的是开发能够通过改变映射和通过直接鉴定Li-Hearing Minerals来识别Li-Pegmatites的创新和有效的遥感方法。为此,使用云的覆盖-5,Landsat-8,Sentinel-2和具有低植被覆盖的Aster图像。图像处理方法包括:RGB(红色,绿色,蓝色)组合,带比和选择性主成分分析(PCA)。这项工作的研究领域是Fregeneda(西班牙萨拉曼卡,西班牙)-Almendra(Vila Nova de Foz CoA,葡萄牙)地区,其中不同已知类型的Li-Pegmatites已被映射。该研究提出了用于选择性PCA的新的RGB组合,带比和子集,能够将Li轴承栓塞的光谱签名与主体岩石的光谱签名区分解。讨论了所提出的方法的潜在和局限性,但总体而言,使用遥感识别Li-Esger Pegmatites的潜力很大。可以使用具有更好的空间和光谱分辨率的传感器来改善所获得的结果。

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