TY - JOUR
T1 - Extending geometallurgy to the mine scale with hyperspectral imaging
T2 - a pilot study using drone- and ground-based scanning
AU - Barton, Isabel F.
AU - Gabriel, Matthew J.
AU - Lyons-Baral, John
AU - Barton, Mark D.
AU - Duplessis, Leon
AU - Roberts, Carson
N1 - Funding Information:
We thank Lantz Indergard for mine access and leach pad ground-truth sampling, and Headwall Photonics and Freeport-McMoRan Inc. for underwriting the cost of the hyperspectral scans. Particular thanks are due to Basil DeSousa, Charlie Kepler, and Will Rock (Headwall) for arranging and conducting the scans and for technical assistance with data reduction. Jingping He carried out additional spectral library refinement and classification. Ground-truth data were provided by Alex Whitehead, with help from Peter D’Amico, from a project supported by NSF grant #17-25338 and by the 2017 W.M. Keck Foundation grant “Evolution of Crustal Paleofluid Flow.” Comments from three anonymous reviewers greatly contributed to the improvement of the work.
Publisher Copyright:
© 2021, Society for Mining, Metallurgy & Exploration Inc.
PY - 2021/4
Y1 - 2021/4
N2 - Geometallurgical assessment of orebodies in the mining industry typically relies on bench-scale or lab-based characterization techniques. In this study, we investigate drone- and tripod-based field hyperspectral imaging as a potential addition to the geometallurgy toolkit in multiple applications. This pilot study tests hyperspectral imaging for large-scale mineral mapping in and around the active Lisbon Valley copper mine, including natural exposures, previously producing U-V mines, highwalls, dumps, and leaching sites. Tests include different (supervised and unsupervised) mineral data classification methods, varying mineral spectral reference libraries, comparison with ground-truth geological and spectroscopic mapping and sampling, and integration with LiDAR data. The results show that hyperspectral scans can produce spatially registered maps of the distribution of different spectrally active mineral types over dumps, highwalls, leach pads, and natural outcrops. Clays, other phyllosilicates, carbonates, and sulfates showed up particularly well. The sensor was also able to distinguish dry from lixiviant-saturated areas and map different clay types on the leach pads, and shows promise for differentiating types and health of vegetation. These results suggest that hyperspectral imaging, if coupled with robust ground-truthing, can be a useful complement to existing geometallurgical techniques in the mining industry, such as geological mapping, blast hole sampling and automated mineralogy identifications, and handheld spectrometry. In particular, hyperspectral imaging has promise for mapping the distribution of acid-consuming minerals; mapping the distribution of swelling, sliming, and heap-blinding clays; and pinpointing problem areas on heap leach pad surfaces.
AB - Geometallurgical assessment of orebodies in the mining industry typically relies on bench-scale or lab-based characterization techniques. In this study, we investigate drone- and tripod-based field hyperspectral imaging as a potential addition to the geometallurgy toolkit in multiple applications. This pilot study tests hyperspectral imaging for large-scale mineral mapping in and around the active Lisbon Valley copper mine, including natural exposures, previously producing U-V mines, highwalls, dumps, and leaching sites. Tests include different (supervised and unsupervised) mineral data classification methods, varying mineral spectral reference libraries, comparison with ground-truth geological and spectroscopic mapping and sampling, and integration with LiDAR data. The results show that hyperspectral scans can produce spatially registered maps of the distribution of different spectrally active mineral types over dumps, highwalls, leach pads, and natural outcrops. Clays, other phyllosilicates, carbonates, and sulfates showed up particularly well. The sensor was also able to distinguish dry from lixiviant-saturated areas and map different clay types on the leach pads, and shows promise for differentiating types and health of vegetation. These results suggest that hyperspectral imaging, if coupled with robust ground-truthing, can be a useful complement to existing geometallurgical techniques in the mining industry, such as geological mapping, blast hole sampling and automated mineralogy identifications, and handheld spectrometry. In particular, hyperspectral imaging has promise for mapping the distribution of acid-consuming minerals; mapping the distribution of swelling, sliming, and heap-blinding clays; and pinpointing problem areas on heap leach pad surfaces.
KW - Big data
KW - Characterization
KW - Geometallurgy
KW - Geotechnics
KW - Hyperspectral imaging
KW - Hyperspectral remote sensing
KW - Imaging spectroscopy
KW - Metallurgy
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UR - http://www.scopus.com/inward/citedby.url?scp=85100704406&partnerID=8YFLogxK
U2 - 10.1007/s42461-021-00404-z
DO - 10.1007/s42461-021-00404-z
M3 - Article
AN - SCOPUS:85100704406
SN - 2524-3462
VL - 38
SP - 799
EP - 818
JO - Mining, Metallurgy and Exploration
JF - Mining, Metallurgy and Exploration
IS - 2
ER -