Field geological mapping is the initial step of preliminary research in mining. However, in the last decades, the rapid progress of remote sensing data processing and its use for reconnaissance of geological outcrops for the purpose of locating possible mining sites gained increasing attention due to the significant time and cost savings. In this study, a new methodology, focused on mapping ferronickel (Fe–Ni) laterite deposits by using Sentinel-2 satellite data, is introduced. It describes a novel spectral index (called laterite spectral index (LSI)) that enhances laterite surface outcrops. To the best of our knowledge, LSI is the first spectral index tailored for this task, concerning minerals that are simultaneously rich in Fe and Ni. The LSI was applied on a continuum removed image by taking advantage of the spectral features present in two specific spectral areas of 490–560 nm and 842–945 nm. The entire methodology was tested and validated on four different excavation sites in eastern Central Greece based on known drillholes. In all excavation sites, the proposed LSI compared favorably with other relative spectral indices proposed in the literature for the detection of Fe-bearing minerals or Fe-oxides.

野外地质填图是采矿前期研究的第一步。然而，在过去的几十年中，遥感数据处理的快速发展及其用于地质露头的勘测以定位可能的采矿地点，由于显着节省时间和成本而受到越来越多的关注。在这项研究中，介绍了一种新的方法，该方法专注于利用 Sentinel-2 卫星数据绘制镍铁 (Fe-Ni) 红土矿床。它描述了一种新的光谱指数（称为红土光谱指数 (LSI)），可增强红土地表露头。据我们所知，LSI 是为这项任务量身定制的第一个光谱指数，涉及同时富含铁和镍的矿物。通过利用 490-560 nm 和 842-945 nm 的两个特定光谱区域中存在的光谱特征，将 LSI 应用于连续去除的图像。基于已知钻孔，整个方法在希腊中东部的四个不同挖掘地点进行了测试和验证。在所有挖掘地点，所提出的 LSI 与文献中提出的用于检测含铁矿物或铁氧化物的其他相对光谱指数相比，具有优势。