Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/158779
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dc.creatorCardoso Fernandes, J
dc.creatorCarvalho, M
dc.creatorAzzalini, A
dc.creatorRodrigues, G
dc.creatorMonteiro, G
dc.creatorAlexandre Lima
dc.creatorAna Teodoro
dc.date.accessioned2024-05-23T23:13:13Z-
dc.date.available2024-05-23T23:13:13Z-
dc.date.issued2023
dc.identifier.othersigarra:645800
dc.identifier.urihttps://hdl.handle.net/10216/158779-
dc.description.abstractTo achieve sustainable development goals, it is crucial to ensure the best practices through the whole mining cycle of critical raw materials (CRM) used in high-Tech, low-carbon goods (batteries, wind turbines, electronics). This is the aim of the SECURE AND SUSTAINABLE SUPPLY OF RAW MATERIALS FOR EU INDUSTRY (S34I) Horizon Europe (HE) project that began on January 1st, 2023. S34I is investigating new data-driven methods to analyze Earth Observation (EO) data, supporting systematic mineral exploration (and other) activities to increase European autonomy regarding CRM resources. The S34I project is based on satellite data, airborne, unmanned aerial vehicle (UAV), ground-based conventional in-situ techniques/methods, and fieldwork. This study presents the first preliminary results based on Sentinel-1 and Sentinel-2 data using classical image processing techniques (RGB combinations, band ratio, Principal Component Analysis PCA, and unsupervised classification) for mineral exploration in Spain, either: (i) on land (Aramo area), to gain knowledge on cobalt (Co) deposits (and associate CRMs) by hydrothermal alteration mapping; and (ii) offshore/shallow waters (Ria de Vigo area), to update the knowledge on coastal metallic placers including CRMs such as Ti, Sn, Li, rare earth elements (REEs) and Au. Among the techniques, PCA proved most effective, followed by band ratios, and selfproposed algorithms for detecting placer minerals showed promise, warranting further investigation. In the future, S34I will exploit Copernicus Contributing Missions (CCM) and other EU hyperspectral satellite sensors such as PRISMA and EnMAP. Different Artificial Intelligence (AI) techniques will, in the future, promote advances and innovative methods that mining stakeholders can use to address the challenges faced in different phases of the mining life-cycle. (c) 2023 SPIE. All rights reserved.
dc.language.isoeng
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineering
dc.rightsopenAccess
dc.titleSentinel data for critical raw materials (CRM) exploration: First results of the S34I project
dc.typeArtigo em Livro de Atas de Conferência Internacional
dc.contributor.uportoFaculdade de Ciências
dc.identifier.doi10.1117/12.2679373
dc.identifier.authenticusP-00Z-6P0
Appears in Collections:FCUP - Artigo em Livro de Atas de Conferência Internacional

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