Publikationsrepositorium - Helmholtz-Zentrum Dresden-Rossendorf
1 PublikationUnderground hyperspectral outcrop scanning for automated mine-face mapping — the Lithium deposit of Zinnwald/Cínovec
Kirsch, M.; Mavroudi, M.; Thiele, S. T.; Lorenz, S.; Tusa, L.; Booysen, R.; Herrmann, E.; Fatihi, A.; Möckel, R.; Dittrich, T.; Gloaguen, R.
Abstract
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.
Keywords: hyperspectral; underground mining; point cloud; lithium; mineral mapping
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Data publication: Underground hyperspectral outcrop scanning for automated …
ROBIS: 36215 HZDR-primary research data are used by this (Id 37299) publication -
Data publication: Underground hyperspectral outcrop scanning for automated …
RODARE: 2078 HZDR-primary research data are used by this (Id 37299) publication
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The Photogrammetric Record 38(2023)183, 408-429
DOI: 10.1111/phor.12457
Cited 1 times in Scopus
Permalink: https://www.hzdr.de/publications/Publ-37299