Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/142217
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dc.creatorSantos, D
dc.creatorCardoso Fernandes, J
dc.creatorLima, A
dc.creatorMuller, A
dc.creatorBronner, M
dc.creatorTeodoro, AC
dc.date.accessioned2022-09-27T09:27:42Z-
dc.date.available2022-09-27T09:27:42Z-
dc.date.issued2022
dc.identifier.issn2072-4292
dc.identifier.othersigarra:569228
dc.identifier.urihttps://hdl.handle.net/10216/142217-
dc.description.abstractAs an important source of lithium and rare earth elements (REE) and other critical elements, pegmatites are of great strategic economic interest for present and future technological development. Identifying new pegmatite deposits is a strategy adopted by the European Union (EU) to decrease its import dependence on non-European countries for these raw materials. It is in this context that the GREENPEG project was established, an EU project whose main objective is to identify new deposits of pegmatites in Europe in an environmentally friendly way. Remote sensing is a non-contact exploration tool that allows for identifying areas of interest for exploration at the early stage of exploration campaigns. Several RS methods have been developed to identify Li-Cs-Ta (LCT) pegmatites, but in this study, a new methodology was developed to detect Nb-Y-F (NYF) pegmatites in the Tysfjord area in Norway. This methodology is based on spectral analysis to select bands of the Sentinel 2 satellite and adapt RS methods, such as Band Ratios and Principal Component Analysis (PCA), to be used as input in the Random Forest (RF) and other tree-based ensemble algorithms to improve the classification accuracy. The results obtained are encouraging, and the algorithm was able to successfully identify the pegmatite areas already known and new locations of interest for exploration were also defined.
dc.language.isoeng
dc.relationinfo:eu-repo/grantAgreement/FCT - Fundação para a Ciência e Tecnologia/Programa de Financiamento Plurianual de Unidades de I&D/UID/GEO/04683/2019/INSTITUTO DE CIÊNCIAS DA TERRA/INSTITUTO DE CIÊNCIAS DA TERRA
dc.rightsopenAccess
dc.titleSpectral Analysis to Improve Inputs to Random Forest and Other Boosted Ensemble Tree-Based Algorithms for Detecting NYF Pegmatites in Tysfjord, Norway
dc.typeArtigo em Revista Científica Internacional
dc.contributor.uportoFaculdade de Ciências
dc.identifier.doi10.3390/rs14153532
dc.identifier.authenticusP-00W-XYJ
Appears in Collections:FCUP - Artigo em Revista Científica Internacional

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