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Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Mapping global resource driven nature loss in the mining sector from 2001 to 2022
Yu-Tong Cheng1, Nguyen Tien Hoang1,2, Yushin Shinoda3
1Graduate School of Environmental Studies, Tohoku University, Sendai, Japan.
Nature Communications
|May 28, 2026
Summary
Global mining is increasing, causing significant deforestation. This study maps nature loss by commodity, revealing gold, coal, and metals drive most forest destruction, especially in tropical rainforests.
Area of Science:
- Environmental Science
- Remote Sensing
- Machine Learning
Background:
- Global mineral extraction is rising due to clean energy demands.
- Environmental impacts of mining are understudied, especially by commodity.
- Data gaps exist for mining's ecological footprint in many regions.
Purpose of the Study:
- To classify ~70,000 mining sites by commodity using novel methods.
- To quantify nature loss, specifically deforestation and habitat destruction, linked to 20 extracted commodities.
- To provide commodity-specific data for supply chain risk assessment and mitigation.
Main Methods:
- Integration of remote sensing, machine learning, and cloud computing for mining site classification.
- Development of a dataset detailing ~70,000 mining sites by commodity.
- Quantification of forest cover loss (2001-2022) attributed to specific mining activities.
Main Results:
- Mining caused 16,268 km² of global forest loss from 2001-2022, with 65.64% in tropical/subtropical areas.
- Gold, coal, bauxite, nickel-cobalt, and copper extraction accounted for roughly half of the deforestation.
- Deforestation-to-mining area ratios and biodiversity risks vary significantly by commodity and location.
Conclusions:
- Commodity-specific mapping of mining-induced nature loss is crucial for targeted conservation.
- Actionable insights are provided for companies to identify and mitigate supply chain risks.
- Understanding localized impacts is key, as conservation threats do not always correlate with deforestation rates.
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