Artigo Acesso aberto Revisado por pares

The INOVMineral Project’s Contribution to Mineral Exploration—A WebGIS Integration and Visualization of Spectral and Geophysical Properties of the Aldeia LCT Pegmatite Spodumene Deposit

2023; Multidisciplinary Digital Publishing Institute; Volume: 13; Issue: 7 Linguagem: Inglês

10.3390/min13070961

ISSN

2075-163X

Autores

Joana Cardoso-Fernandes, Douglas Santos, Cátia Rodrigues de Almeida, Julia Tucker Vasques, Ariane Mendes, Ricardo Ribeiro, Antônio Azzalini, Lia Duarte, Rui Moura, Alexandre Lima, Ana Cláudia Teodoro,

Tópico(s)

Soil Geostatistics and Mapping

Resumo

Due to the current energetic transition, new geological exploration technologies are needed to discover mineral deposits containing critical materials such as lithium (Li). The vast majority of European Li deposits are related to Li–Cs–Ta (LCT) pegmatites. A review of the literature indicates that conventional exploration campaigns are dominated by geochemical surveys and related exploration tools. However, other exploration techniques must be evaluated, namely, remote sensing (RS) and geophysics. This work presents the results of the INOVMINERAL4.0 project obtained through alternative approaches to traditional geochemistry that were gathered and integrated into a webGIS application. The specific objectives were to: (i) assess the potential of high-resolution elevation data; (ii) evaluate geophysical methods, particularly radiometry; (iii) establish a methodology for spectral data acquisition and build a spectral library; (iv) compare obtained spectra with Landsat 9 data for pegmatite identification; and (v) implement a user-friendly webGIS platform for data integration and visualization. Radiometric data acquisition using geophysical techniques effectively discriminated pegmatites from host rocks. The developed spectral library provides valuable insights for space-based exploration. Landsat 9 data accurately identified known LCT pegmatite targets compared with Landsat 8. The user-friendly webGIS platform facilitates data integration, visualization, and sharing, supporting potential users in similar exploration approaches.

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