Towards Multiscale and Multisource Remote Sensing Mineral Exploration Using RPAS: A Case Study in the Lofdal Carbonatite-Hosted REE Deposit, Namibia

Abstract

Traditional exploration techniques usually rely on extensive field work supported by geophysical ground surveying. However, this approach can be limited by several factors such as field accessibility, financial cost, area size, climate, and public disapproval. We recommend the use of multiscale hyperspectral remote sensing to mitigate the disadvantages of traditional exploration techniques. The proposed workflow analyzes a possible target at different levels of spatial detail. This method is particularly beneficial in inaccessible and remote areas with little infrastructure, because it allows for a systematic, dense and generally noninvasive surveying. After a satellite regional reconnaissance, a target is characterized in more detail by plane-based hyperspectral mapping. Subsequently, Remotely Piloted Aircraft System (RPAS)-mounted hyperspectral sensors are deployed on selected regions of interest to provide a higher level of spatial detail. All hyperspectral data are corrected for radiometric and geometric distortions. End-member modeling and classification techniques are used for rapid and accurate lithological mapping. Validation is performed via field spectroscopy and portable XRF as well as laboratory geochemical and spectral analyses. The resulting spectral data products quickly provide relevant information on outcropping lithologies for the field teams. We show that the multiscale approach allows defining the promising areas that are further refined using RPAS-based hyperspectral imaging. We further argue that the addition of RPAS-based hyperspectral data can improve the detail of field mapping in mineral exploration, by bridging the resolution gap between airplane-and ground-based data. RPAS-based measurements can supplement and direct geological observation rapidly in the field and therefore allow better integration with in situ ground investigations. We demonstrate the efficiency of the proposed approach at the Lofdal Carbonatite Complex in Namibia, which has been previously subjected to rare earth elements exploration. The deposit is located in a remote environment and characterized by difficult terrain which limits ground surveys. 2 of 28 increased demand for Rare Earth Elements (REEs). As a result, the exploration of new and promising REE deposits is of economic importance in view of the current dependence of the world market on imports from a limited number of countries.Carbonatites, rocks comprising more than 50 modal-% carbonate minerals, are the main source of REEs [1]. The typical ore minerals for light rare earth elements (LREEs) are monazite, bastnaesite, and parisite, and for the heavy rare earth elements (HREEs), is xenotime [1]. Hyperspectral remote sensing has been recently suggested to detect and identify carbonatites as potential REE deposits [2][3][4], due to the distinctive absorption feature of carbonates (CO 3 ) around 2300 to 2350 nm [5]. At a sufficient grade, REEs can be detected directly due to their characteristic narrow absorption features in the VNIR and SWIR [3,6]. Neodymium...

Integrated Geological and Geophysical Mapping of a Carbonatite-Hosting Outcrop in Siilinjärvi, Finland, Using Unmanned Aerial Systems

“…Successful applications of UAS-based surveys in mineral exploration were used to explore rare earths using spectral imaging [10] and target uranium deposits using radiometric gamma survey [11]. UAS geophysical magnetic mapping was employed in exploration for iron, zinc, chromite, or gold deposits [12][13][14][15].…”

A spectral library for laser-induced fluorescence analysis as a tool for rare earth element identification

“…Reflectance spectroscopy has shown an immense potential for fast, non-invasive mineral mapping. Several studies particularily demonstrated advances in reflectance hyperspectral imaging (in the following abbreviated as HSI) of REEs in natural materials from close-range scanning of drill-cores and outcrops or from drone-borne data of larger-scale areas (e.g., Boesche et al, 2015;Turner, 2015;Neave et al, 2016;Zimmermann et al, 2016;Booysen et al, 2019). However, an absorption feature-based identification relies in most application cases on single REEs (e.g.…”

Detection of REEs with lightweight UAV-based hyperspectral imaging

“…Turner et al 11 , Boesche et al 12 and Neave et al 9 successfully identified and mapped REEs using laboratory-or ground-based hyperspectral imaging (HSI). Booysen et al 3 demonstrated how unmanned aerial vehicle (UAV)-based hyperspectral data can be used in a multi-scale remote sensing exploration approach to map REEs indirectly. Minute spectral features, low concentrations, large ground sampling distances (GSDs) and heavy imaging equipment have impeded their direct measurements from lightweight airborne platforms so far.…”

“…Drones have been increasingly used in mineral exploration (e.g., Booysen et al 3 ; Jackisch et al 13 ; Malehmir et al 14 ; Sayab et al 15 ). Difficult terrain or outcrops unreachable on foot or by vehicles can be rapidly surveyed with UAVs from a safe distance with minimal personnel on site, ensuring safety, efficiency and speed 16,17 .…”

“…We have recently proposed an innovative approach for the acquisition and processing of UAV-based HSI data 3,20 . We use two types of unmanned aerial systems (UAS); a fixed-wing system (Fig.…”