Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf

The inherent complexity of underground mining requires highly selective ore extraction and adaptive mine planning. Repeated geological face mapping and re-interpretation throughout mine life is therefore routine in underground mines. Hyperspectral imaging has successfully been applied to enhance geological mapping in surface mining environments but remains a largely unexplored opportunity in underground operations due to challenges associated with illumination, wet surfaces, and data corrections. In this study, we propose a workflow that paves the way for the operational use of hyperspectral imaging in active underground mines. In a laboratory setup, we evaluated different hyperspectral sensors and lighting setups as well as the effect of surface moisture. We then acquired hyperspectral data in an underground mine of the Zinnwald/Cínovec Sn-W-Li greisen-type deposit in Germany. These data were corrected for illumination effects, back-projected into 3-D and then used to map mineral abundance and estimate lithium content across the mine face. We validated the results with handheld laser-induced breakdown spectroscopy. Despite remaining challenges, we hope this study will help establish hyperspectral sensors in the extractive industry as a means to increase the volume and efficiency of raw material supply, advance digitalisation, and reduce the environmental footprint and other risks associated with underground mining.