Leveraging Earth Observation and Machine Learning to Address Critical Raw Material Challenges in the EU - a Policy Brief by The European Sustainable Mining & Innovation Network

Critical raw materials (CRMs) are central to Europe’s economy and its transition to a sustainable and digital future. They are essential for the development of advanced technologies for clean energy and digital infrastructures. For instance, lithium, cobalt and nickel are used in batteries for electric vehicles, Rare Earth Elements (REE) are critical for permanent magnets in wind turbines and electronics, and copper, silicon and tantalum are required for artificial intelligence (AI) infrastructures. Demand for these materials is predicted to increase manifold over the next decades, while recent crises such as the COVID-19 pandemic and geopolitical tensions have shown how fragile and import-dependent Europe’s supply chains remain. Securing reliable access to CRMs is now a strategic priority, and the European Commission has introduced the European Critical Raw Materials Act (CRMA), as part of its Green Deal Industrial Plan. The CRMA sets ambitious goals: scale up domestic production, diversify sourcing, increase circularity (recycling and substitution), and strengthen permitting, monitoring and innovation. Achieving these objectives requires not only funding and regulatory reform but also robust, operational technologies capable of improving CRM exploration, mining operations, environmental monitoring, traceability and regulatory compliance across the full CRM lifecycle. Earth Observation (EO) and Machine Learning (ML) feature among the most promising fields to address these objectives. EO provides a continuous flow of information on geology, the environment, land use and ground stability while ML helps turning complex datasets into practical insights. Together, they can reduce costs and risks in mineral exploration, increase the sustainability and efficiency of mining operations, improve environmental monitoring, and speed up decision-making. Several Horizon Europe projects, joining forces within the European Sustainable Mining and Innovation Network (ESMIN), are developing and testing such innovative EO and ML solutions. This policy brief presents preliminary results and illustrates how EO and ML can support mining companies, geological surveys, non-governmental organisations and national institutions in delivering on the CRMA objectives.Written by MultiMiner, GoldenRAM, MOSMIN, AGEMERA, M4Mining, and MINEYE as representatives of ESMIN (European Sustainable Mining & Innovation Network). MultiMiner was funded by the European Union’s HORIZON research and innovation actions programme under Grant Agreement No. 101091374. GoldenRAM was funded by the European Union’s HORIZON research and innovation actions programme under Grant Agreement No. 101138153. AGEMERA was funded by the European Union’s HORIZON research and innovation actions programme under Grant Agreement No. 101058178. MOSMIN is funded by the European Union Agency for the Space Programme and the European Union‘s Horizon Europe innovation action programme under grant agreement No 101131740. M4Mining was funded by the European Union’s HORIZON research and innovation actions programme under Grant Agreement No. 101091462 MINEYE was funded by the European Union’s HORIZON research and innovation actions programme under Grant Agreement No. 101138456.