SOURCE-LINKED INTELLIGENCE
Artisanal Mines, Economic Development and Social Impact
ountries over the period 2000-2020 with exact information on location (GPS coordinates). Two other crucial information are also collected: the size and the mineral extracted from each ASM. I will use machine learning techniques and satellite image time series to identify sediment and open pit-mining activities. Second, equipped with this ground-breaking dataset, I aim to provide systematic and large-scale evidence of the impact of ASM on violence and conflict; environmental degradation and health; and internal migration. The proposals objectives, grounded in quantitative economics, are spanning several literatures from a wide variety of disciplines, by combining state-of-the-art machine learning techniques and remote sensing data. I expect the methodologies and the results to push the research frontier in several dimensions. Moreover, the conclusions drawn from the project would be highly relevant for policy-makers and NGOs aiming to improve the monitoring of those mining activities and their impacts on conflict, health and environmental degradation. Development economics, natur
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 1522748
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.