<p>Global mineral extraction is expected to surge due to the growing demand for clean energy. While mining is critical to modern society, its environmental impacts, though increasingly studied, remain undocumented for half of the world’s mining areas and are rarely analysed at the commodity level. Here, we introduce a novel approach integrating remote sensing, machine learning, and cloud computing to classify approximately 70,000 mining sites by commodity. Using this newly detailed dataset, we quantify the nature loss associated with 20 extracted commodities, focusing on deforestation and habitat destruction. From 2001 to 2022, mining activities worldwide resulted in the removal of 16,268 km² of forest cover, with 65.64% occurring in tropical and subtropical regions. Notably, approximately half of this deforestation was attributed to the extraction of gold, coal, aluminium (bauxite), nickel-cobalt and copper, primarily in countries intersecting the Amazon, Southeast Asian, and Congo Basin rainforests. Our analysis also reveals that deforestation-to-mining area ratios and biodiversity risks vary by mining location, and conservation threats do not always scale with deforestation rates. By providing commodity-specific maps of mining-induced nature loss, our work equips companies and organisations with actionable insights to identify risks within their supply chains and implement targeted mitigation strategies.</p>