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Multi-Scale Approach using Remote Sensing Techniques for Lithium Pegmatite Exploration: First Results

Authors

Cardoso-Fernandes,  Joana
External Organizations;

Teodoro,  Ana Cláudia
External Organizations;

Lima,  Alexandre
External Organizations;

/persons/resource/chmielke

Mielke,  Christian
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/koerting

Koerting,  Friederike
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Roda-Robles,  Encarnación
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Citation

Cardoso-Fernandes, J., Teodoro, A. C., Lima, A., Mielke, C., Koerting, F., Roda-Robles, E. (2020): Multi-Scale Approach using Remote Sensing Techniques for Lithium Pegmatite Exploration: First Results - Proceedings, IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium (Online 2020).
https://doi.org/10.1109/IGARSS39084.2020.9323705


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5008279
Abstract
Raw-materials like lithium (Li) are crucial to the current global decarbonization, but Li-exploration presents some technical challenges. Therefore, new solutions for Li-exploration are needed. Consequently, the aim of this study is to present a unique multi-scale remote sensing approach for Li-pegmatite exploration integrated within the LIGHTS project, considering as study area the Bajoca mine (Portugal). Satellite data allowed the identification of the spectral signatures of Li-pegmatites at a district scale, while drone-borne hyperspectral measurements provided data at the target scale. Handheld spectroscopy and in situ hyperspectral scans of the mine walls were carried out to validate the satellite and drone data. Hyperspectral field and laboratory scans also aim to collect information at the mineral scale, to distinguish different lithological materials, and to identify the Li-rich areas. In the future, machine learning algorithms will deliver an automated integration of all acquired data.