On the feasibility of imaging carbonatite-hosted rare earth element (REE) deposits using remote sensing

Abstract

Rare earth elements (REEs) generate characteristic absorption features in visible to shortwave infra-red (VNIR-SWIR) reflectance spectra. Neodymium (Nd) has amongst the most prominent absorption features of the REEs and thus represents a key pathfinder element for the element group as a whole. Given that the world’s largest REE deposits are associated with carbonatites, we present spectral, petrographic and geochemical data from a predominantly carbonatitic suite of rocks that we use to assess the feasibility of imaging REE deposits using remote sensing. Samples were selected to cover a wide range of extents and styles of REE mineralization, and encompass calcio-, ferro- and magnesiocarbonatites. REE ores from the Bayan Obo (China) and Mountain Pass (USA) mines as well as REErich alkaline rocks from the Motzfeldt and Ilímaussaq intrusions in Greenland were also included in the sample suite. The depth and area of Nd absorption features in spectra collected under laboratory conditions correlate positively with the Nd content of whole-rock samples. The wavelength of Nd absorption features is predominantly independent of sample lithology and mineralogy. Correlations are most reliable for the two absorptions features centered at ~744 nm and ~802 nm and can be observed in samples containing as little as ~1000 ppm Nd. By convolving laboratory spectra to the spectral response functions (SRFs) of a variety of remote sensing instruments we demonstrate that hyperspectral instruments with capabilities equivalent to the operational Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and planned Environmental Mapping and Analysis Program (EnMAP) instruments have the spectral resolution necessary to detect Nd absorption features, especially in high grade samples with economically relevant REE accumulations (Nd > 30000 ppm). Adding synthetic noise to convolved spectra indicates that correlations between Nd absorption area and whole-rock Nd content only remain robust when spectra have signal-to-noise ratios in excess of ~250:1. Although atmospheric interferences are modest across the wavelength intervals relevant for Nd detection, most REE-rich outcrops will be too small to be detectable using satellite-based platforms with >30 m spatial resolutions. However, our results indicate that Nd absorption features should be identifiable in high-quality, airborne, hyperspectral datasets collected at meter-scale spatial resolutions. Future deployment of hyperspectral instruments on Unmanned Aerial Vehicles (UAVs) could enable REE grade to be mapped at the cm-scale across whole deposits