The increasing demand for critical raw materials (CRMs), driven by global energy transition, underscores the need for innovative approaches to identify secondary resources, such as mining residues. Mining residues, often overlooked during initial mining activities, now represent valuable sources of raw materials thanks to technological advancements, including hyperspectral remote sensing. This study investigates the potential of hyperspectral satellite imagery to detect and map CRMs in mining residues of the abandoned Sidi Bou Azzouz mine in Morocco. The proposed approach is based on the integration between satellite data, field spectroscopy, chemical, and mineralogical analyses in a strong multi-scale and interdisciplinary framework. The integration between advanced laboratory techniques, including LIBS, XRF, XRPD, and SEM-EDS, was employed to enhance hyperspectral data interpretation. The integration of remote sensing and laboratory results provided a comprehensive understanding of mineral composition, confirming the effectiveness of hyperspectral methods for characterizing heterogeneous surface deposits. This research demonstrates the potential of hyperspectral observations to identify valuable raw materials and to map them using PRISMA imagery in abandoned mining residues, offering a tool useful for planning cost-effective and sustainable solutions aimed at answering the growing demand for CRMs crucial to industrial competitiveness and sustainable growth.

Hyperspectral Investigation of an Abandoned Waste Mining Site: The Case of Sidi Bou Azzouz (Morocco)

Vaccaro, Carmela
Ultimo
Membro del Collaboration Group
2025

Abstract

The increasing demand for critical raw materials (CRMs), driven by global energy transition, underscores the need for innovative approaches to identify secondary resources, such as mining residues. Mining residues, often overlooked during initial mining activities, now represent valuable sources of raw materials thanks to technological advancements, including hyperspectral remote sensing. This study investigates the potential of hyperspectral satellite imagery to detect and map CRMs in mining residues of the abandoned Sidi Bou Azzouz mine in Morocco. The proposed approach is based on the integration between satellite data, field spectroscopy, chemical, and mineralogical analyses in a strong multi-scale and interdisciplinary framework. The integration between advanced laboratory techniques, including LIBS, XRF, XRPD, and SEM-EDS, was employed to enhance hyperspectral data interpretation. The integration of remote sensing and laboratory results provided a comprehensive understanding of mineral composition, confirming the effectiveness of hyperspectral methods for characterizing heterogeneous surface deposits. This research demonstrates the potential of hyperspectral observations to identify valuable raw materials and to map them using PRISMA imagery in abandoned mining residues, offering a tool useful for planning cost-effective and sustainable solutions aimed at answering the growing demand for CRMs crucial to industrial competitiveness and sustainable growth.
2025
Guglietta, Daniela; Salzano, Roberto; Wafik, Amina; Conte, Aida M.; Paciucci, Matteo; Punturo, Rosalda; Salvatori, Rosamaria; Senesi, Giorgio S.; Vacc...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2617650
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