Mapping Mining Areas in the Tropics from 2016 to 2024

Mining provides crucial materials for the global economy and the energy transition but can have severe environmental and social impacts. Available analyses of these impacts are limited by a lack of data on mining activity, particularly in the regions most affected. In this paper, we present a detailed panel dataset mapping mining sites along the tropical belt from 2016 to 2024. Our approach uses a machine learning model, trained on over 25,000 mining polygons from the literature, to automatically segment mining areas in high-resolution (<5 m) satellite imagery. The dataset maps over 145,000 mining polygons covering an average area of 65,000 km² annually, with an accuracy of 87.7 % and precision of 84.1 %. Our approach allows for accurate, precise, and consistent delineation, and can be scaled to other locations and periods. The dataset enables detailed analyses of local environmental, social, and economic impacts of mining in regions where conventional data are scarce or incomplete.