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Innovative Hyperspectral Data Fusion for Enhanced Mineral Prospectivity Mapping
La Rosa, R; Steffen, M; Storch, I; Knobloch, A; Cardoso Fernandes, J; Carvalho, M; Barrios, MS; Sánchez Migallón, JM; Nygren, P; Williams, VTo meet the European Unions growing demand for critical raw materials in the transition to green energy, this study presents a novel, cost-effective, and non-invasive methodology for mineral prospectivity mapping. By integrating hyperspectral data from satellite, airborne, and ground-based sources with deep learning techniques, we enhance mineral exploration efficiency. We employ Bayesian Neural Networks (BNNs)...
Date: 2025
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Origin: Repositório Aberto da Universidade do Porto