GREENPEG: New exploration tools for European pegmatite green-tech resources
Published March 3, 2021 | Version v1
Dataset Open

Tools for remote exploration: a Lithium (Li) dedicated spectral library of the Fregeneda-Almendra aplite-pegmatite field

Creators

  • 1. Department of Geosciences, Environment and Spatial Plannings, Faculty of Sciences, University of Porto; ICT (Institute of Earth Sciences) – Porto pole (Portugal), Rua Campo Alegre, 4169-007 Porto, Portugal
  • 2. Department of Geosciences, Environment and Spatial Plannings, Faculty of Sciences, University of Porto, Rua Campo Alegre, 4169-007 Porto, Portugal
  • 3. Université de Lorraine, CNRS, GeoRessources Laboratory, F-54000 Nancy, France
  • 4. Remote Sensing and Mineral Spectroscopy Laboratory, Geological Survey of Brazil (CPRM), Rua Costa, 55, 01304-010, São Paulo, Brazil
  • 5. Departamento de Geología, Universidad del País Vasco (UPV/EHU), Barrio Sarriena, 48940 Leioa, Bilbao, Spain

Description

Currently, there is big market pressure for raw materials like lithium (Li) that has driven new satellite image applications for Li exploration. However, there are no reference spectra for petalite (a Li-mineral) in large, open spectral datasets. In this work, a spectral library was built exclusively dedicated to Li-minerals and Li-pegmatite exploration through satellite remote sensing. The database includes field and laboratory spectra collected in the Fregeneda-Almendra region (Spain-Portugal) from (i) distinct Li-minerals (spodumene, petalite, lepidolite); (ii) several Li-pegmatites and other outcropping lithologies to allow satellite-based lithological mapping; (iii) areas previously misclassified as Li-pegmatites using machine learning algorithms to allow comparisons between these regions and the target areas. The potential future uses of this spectral library are reinforced by its major advantages: (i) data is provided in a universal file format; (ii) it allows to compare field and laboratory spectra; (iii) a large number of complementary data allows the comparison of shape, asymmetry, and depth of the absorptions features of the distinct Li-minerals.

 

The peer-reviewed data descriptor for this dataset has now been published in MDPI Data - an open access journal aiming at enhancing data transparency and reusability, and can be accessed here: https://www.mdpi.com/2306-5729/6/3/33. Please cite this when using the dataset.

Notes

The authors would like to thank the financial support provided by FCT– Fundação para a Ciência e a Tecnologia, I.P., with the ERA-MIN/0001/2017 – LIGHTS project and also with the 869274 — GREENPEG — H2020-SC5-2018-2019-2020 project. The work was also supported by National Funds through the FCT project UIDB/04683/2020 - ICT (Institute of Earth Sciences). Joana Car-doso-Fernandes and Filipa Dias are financially supported within the compass of their respective Ph.D. Thesis, ref. SFRH/BD/136108/2018 and ref. 2020.05534.BD, by national funds from MCTES through FCT, and co-financed by the European Social Fund (ESF) through POCH – Programa Operacional Capital Humano – and NORTE 2020 regional program. The Spanish Ministerio de Ciencia, Innovacion y Universidades (Project RTI2018-094097-B-100, with ERDF funds) and the University of the Basque Country (UPV/EHU) (grant GIU18/084) also contributed economically. The French National Research Agency (ANR – 10 – LABX 21 – LABEX RESSOURCES 21) partly supported Master Student personal grant and the 776804 - NEXT– H2020-SC5-2017 project par-ticipated to equipment purchase.

Files

Guide for the spectral library.pdf

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Additional details

Related works

Is supplemented by
Journal article: 10.3390/data6030033 (DOI)

References

  • Cardoso-Fernandes, Joana et al. (2019). Evaluating the performance of support vector machines (SVMs) and random forest (RF) in Li-pegmatite mapping: preliminary results. In Proceedings of SPIE, SPIE Remote Sensing, Strasbourg, France, 9–12 September 2019; Schulz, K.; Michel, U.; Nikolakopoulos, K. G., Eds. SPIE: Bellingham, WA; 2019. doi: 10.1117/12.2532577.
  • Cardoso-Fernandes, Joana et al. (2020a). Characterization of lithium (Li) minerals from the Fregeneda-Almendra region through laboratory spectral measurements: a comparative study. In SPIE Remote Sensing, SPIE: 2020. doi: https://doi.org/10.1117/12.2573941.
  • Cardoso-Fernandes, Joana et al. (2020b). Reflectance spectroscopy to validate remote sensing data/algorithms for satellite-based lithium (Li) exploration (Central East Portugal). In SPIE Remote Sensing, SPIE: 2020. doi: https://doi.org/10.1117/12.2573929.