The Secure and Sustainable Supply of Raw Materials for EU Industry - S34I project is researching and innovating new data-driven methods to analyze Earth Observation (EO) data, supporting systematic mineral exploration and continuous monitoring of extraction, closure, and post-closure activities to increase European autonomy regarding raw materials (RM) resources, and to use EO not only for the management of tec...
To 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)...