Evaluation of EnMAP Hyperspectral Data for the Identification of Placers in the Rias Baixas Region (Spain)

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2025

Autores

Araújo, L (Autor) Outra; Cardoso Fernandes, J (Autor) FCUP; Azzalini, A (Autor) Outra; Carvalho, M (Autor) Outra; Lima, A (Autor) Outra; González, J (Autor) Outra; Ana Teodoro (Autor) FCUP

Ata de Conferência Internacional

Título: Proceedings of the 11th International Conference on Geographical Information Systems Theory, Applications and Management

Páginas: 297-304

11th International Conference on Geographical Information Systems Theory, Applications and Management, GISTAM 2025

Porto, 1 April 2025 through 3 April 2025

Indexação

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-018-H9N

DOI: 10.5220/0013496200003935

Abstract (EN): Critical Raw Materials are crucial to achieve the European Union¿s (EU) goals of a climate-neutral economy by 2050. The high supply risk led the EU to prioritise domestic mineral exploration. This study, part of the S34I - SECURE AND SUSTAINABLE SUPPLY OF RAW MATERIALS project, utilised remote-sensing-based methods to identify and map heavy-mineral (HM) placer deposits in the Ria de Vigo, located in Galicia, Spain. Documented since the 70s, the sands of the Vigo beaches contain placers rich in Ti, Sn, Li, Rare Earth Elements (REE), Au, Fe and Cu. Mineral mapping was performed using hyperspectral EnMAP data. Band ratios were applied to identify possible mineralisation areas. Additionally, spectral unmixing was performed through the Mixture Tuned Matched Filtering (MTMF) workflow, included in ENVI 6.0 software, and two classification maps were obtained: one utilising the USGS spectral library and the other employing an HM concentrate spectral library. Band ratios were able to distinguish possible areas of hydrothermal alteration. MTMF classifications mapped most HM known to occur in the Ria, namely sillimanite, garnet, tourmaline, ilmenite, rutile, and monazite, were identified. This first approach will allow the selection of areas of interest for field validation and verification. The results will also be confronted with existing geological data. © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7