Sentinel data for critical raw materials (CRM) exploration: First results of the S34I project

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Cardoso Fernandes, J (Author) FCUP; Carvalho, M (Author) Other; Azzalini, A (Author) Other; Rodrigues, G (Author) Other; Monteiro, G (Author) Other; Alexandre Lima (Author) FCUP; Ana Teodoro (Author) FCUP

Conference proceedings International

Title: Proceedings of SPIE - The International Society for Optical Engineering

Earth Resources and Environmental Remote Sensing/GIS Applications XIV 2023

Amsterdam, 2023

Indexing

Scopus - 3 Citations

Other information

Authenticus ID: P-00Z-6P0

DOI: 10.1117/12.2679373

Abstract (EN): To 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. © 2023 SPIE. All rights reserved.

Language: English

Type (Professor's evaluation): Scientific