Characterisation of coal using hyperspectral core scanning systems

Rodrigues, Sandra; Fonteneau, Lionel; Esterle, Joan

doi:10.1016/j.coal.2023.104220

Cited by 4 publications

(1 citation statement)

References 59 publications

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“…Operational, industrial scanning systems are often a combination of high-resolution digital (RGB) cameras, a spectrometer capturing VNIR and SWIR spectral ranges, and a laser profilometer. The systems include either discontinuous step-and-measure data acquisition (e.g., GeoLogr by Hyperspectral imaging or the HyLogger by CSIRO), allowing for variable integration times, or a continuous, imaging data acquisition per interval (e.g., Corescan, Terraocore, GeologicAi, Plotlogic, DMT ANCORELOG) (examples here include [108][109][110][111][112][113][114].Examples of where hyperspectral core scanning has been deployed and results are published include, but not limited to, analyses of samples and downhole intervals from Cu porphyry deposits to facilitate ore sorting [115,116], porphyry deposits alteration mineral characterization [114,117,118], coal quality studies [111], Au-Cu-Zn VMS mineralization associated with volcanogenic massive sulfide (VMS) deposits [116,[119][120][121], unconformity related Uranium deposits [122], analysis of basement rocks [123], characterization of REE-bearing minerals [124], and lithology discrimination in iron ore deposits [125]. Areas of weathered bedrock [126,128] are highlighted by yellow-coloured hashed lines and highlight which drill cores were sunk into barren ground (D, E, F, G).…”

Section: Exploration Sectormentioning

confidence: 99%

Imaging Spectroscopy for the Mining Life Cycle: A Guide for Drone Applications

Koerting,

Asadzadeh,

Hildebrand

et al. 2024

Preprint

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Hyperspectral imaging data holds great potential for the different stages of the mining life cycle in active and post-mining environments. However, the technology has yet to reach the stage of large-scale industrial implementation and acceptance. While hyperspectral satellite imagery can achieve high spectral resolution, signal-to-noise ratio (SNR) and global availability with break-through satellite systems like EnMAP, EMIT and PRISMA, limited spatial resolution poses chal-lenges for sectors like mining, which require decimetre to centimetre scale resolution for applica-tions such as reconciliation, ore/waste estimates, geotechnical assessments and environmental monitoring. Hyperspectral imaging from drones (referred to herein as Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the camp/ mine scale, with the capability for frequent, user-defined re-visit times. This has been made possible by the miniaturization of hy-perspectral imaging systems. Collection of data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions enables the detection of different minerals and surface altera-tion patterns potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we provide a review of relevant studies de-ploying hyperspectral imaging in or applicable to the mining sector, especially for the use of hy-perspectral VNIR-SWIR Uncrewed Aerial Systems. Where required, we draw on previous in-sights derived from satellite or ground-based systems. We also discuss UAS survey planning, and sampling considerations for validation and interpretation.

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