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An ever‐increasing global population and unabating technological growth have resulted in a relentless appetite for mineral resources, namely rare earth elements, fuel minerals and those utilised in electronics applications, with the price of such species continuing to climb. In contrast to more established large‐scale and high‐cost exploration methodologies, this work details the application of novel multi‐rotor unmanned aerial vehicles equipped with miniaturised radiation detectors for the objective of undertaking resource exploration at lower costs, with greater autonomy and at considerably enhanced higher spatial resolutions; utilizing the ore material’s inherent low levels of characteristic radioactivity. As we demonstrate at the former Wooley Mine site in Arizona, USA, a legacy Cu/Fe prospect where the 600 by 275 m ore body (with a maximum deposit depth of 150 m), it is shown that such a fusion of commercially available low‐altitude multi-rotor aerial technology combined with cutting‐edge micro‐electronics and detector materials is capable of accurately assessing the spatial distribution and associated radiogenic signatures of commercially valuable surface/near‐surface ore bodies. This integrated system, deployed at an autonomously controlled consistent survey altitude and using constant grid transects/separations, is shown to be able to delineate the mineral‐containing ore deposits on the site, the location(s) of former mine workings and other surface manifestations. Owing to its advantageous costs alongside its ease of operation and subsequent data‐processing, through the adoption of this system, it is envisaged that less economically developed countries would now possess the means through which to evaluate and appropriately quantify their mineral wealth without the significant initial expenditure needed to equip themselves with otherwise prohibitively expensive technologies.
Deposit; Drone; Exploration; Minerals; NORM; Radiation; UAV; Uranium
Earth Sciences | Geology | Geomorphology | Physical Sciences and Mathematics
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Martin, P. G.,
Connor, D. T.,
Jones, C. P.,
Kreamer, D. K.,
Scott, T. B.
Radiological Identification of Near‐Surface Mineralogical Deposits Using Low‐Altitude Unmanned Aerial Vehicle.
Remote Sensing, 12(21),