School of Geosciences (Journal Articles)

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Browsing School of Geosciences (Journal Articles) by Keyword "Hyperspectral imaging"

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    Accurate hyperspectral imaging of mineralised outcrops: An example from lithium-bearing pegmatites at Uis, Namibia
    (Elsevier Inc, 2021) Booysen, René; Nex, Paul A.M.; Lorenz, Sandra; Thiele, Samuel T.; Fuchsloch, Warrick C.; Marais, Timothy; Gloaguen, Richard
    Efficient, socially acceptable and rapid methods of exploration are required to discover new deposits and enable the green energy transition. Sustainable exploration requires a combination of innovative thinking and new technologies. Hyperspectral imaging (HSI) is a rapidly developing technology and allows for fast and systematic mineral mapping, facilitating exploration of the Earth’s surface at various scales on a variety of platforms. Newly available sensors allow data capture over a wide spectral range, and provide information about the abundance and spatial location of ore and pathfinder minerals in drill-core, hand samples and outcrops with mm to cm precision. Conversely, the complex geometries of the imaged surfaces affect the spectral quality and signal-to-noise ratio (SnR) of HSI data at these very narrow spatial samplings. Additionally, the complex mineral assemblages found in hydrothermally altered ore deposits can make interpretation of spectral results a challenge. In this contribution, we propose an innovative approach that integrates multiple sensors and scales of data acquisition to help disentangle complex mineralogy associated with lithium and tin mineralisation in the Uis pegmatite complex, Namibia. We train this method using hand samples and finally produce a three-dimensional (3D) point cloud for mapping lithium mineralisation in the open pit. We were able to identify and map lithium-bearing cookeite and montebrasite at outcrop scale. The accuracy of the approach was validated by drill-core data, XRD analysis and LIBS measurements. This approach facilitates efficient mapping of complex terrains, as well as important monitoring and optimisation of ore extraction. Our method can easily be adapted to other minerals relevant to the mining industry.