Detecting rare earth elements using EnMAP hyperspectral satellite data: a case study from Mountain Pass, California
Rare earth elements (REEs) exhibit diagnostic absorption features in the visible-near infrared region, enabling their detection and identification via spectroscopic methods. Satellite-based remote sensing mapping of REEs, however, has not been attainable so far due to the necessity for high-quality hyperspectral data to resolve their narrow absorption features. This research leverages EnMAP hyperspectral satellite data to map REEs in Mountain Pass, California-a mining area known to host bastnaesite-Ce ore in sövite and beforsite carbonatites. By employing a polynomial fitting technique to characterize the diagnostic absorption features of Neodymium (Nd) at ∼740 and ∼800 nm, the surface occurrence of Nd was successfully mapped at a 30m pixel resolution. The relative abundance of Nd was represented using the continuum-removed area of the 800 nm feature. The resulting map, highlighting hundreds of anomalous pixels, was validated through laboratory spectroscopy, surface geology, and high-resolution satellite imagery. This study marks a major advancement in REE exploration, demonstrating for the first time, the possibility of directly detecting Nd in geologic environments using the EnMAP hyperspectral satellite data. This capability can offer a fast and cost-effective method for screening Earth's surfaces for REE signature, complementing the existing exploration portfolio and facilitating the discovery of new resources.
Authors
- Saeid Asadzadeh (ORCID: https://orcid.org/0000-0001-9043-0757)
- Sabine Chabrillat (ORCID: https://orcid.org/0000-0001-8600-5168)
- Nicole Koellner
Institutions
- Leibniz University Hannover (DE)
- GFZ Helmholtz Centre for Geosciences (DE)
Publication Details
- Journal
- Scientific Reports
- Published
- 2024-09-05
- DOI
- https://doi.org/10.1038/s41598-024-71395-2
- Citations
- 21
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 7.29