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A global-scale data set of mining areas.

Victor MausStefan GiljumJakob GutschlhoferDieison M da SilvaMichael ProbstSidnei L B GassSebastian LuckenederMirko LieberIan McCallum
Published in: Scientific data (2020)
The area used for mineral extraction is a key indicator for understanding and mitigating the environmental impacts caused by the extractive sector. To date, worldwide data products on mineral extraction do not report the area used by mining activities. In this paper, we contribute to filling this gap by presenting a new data set of mining extents derived by visual interpretation of satellite images. We delineated mining areas within a 10 km buffer from the approximate geographical coordinates of more than six thousand active mining sites across the globe. The result is a global-scale data set consisting of 21,060 polygons that add up to 57,277 km2. The polygons cover all mining above-ground features that could be identified from the satellite images, including open cuts, tailings dams, waste rock dumps, water ponds, and processing infrastructure. The data set is available for download from https://doi.org/10.1594/PANGAEA.910894 and visualization at www.fineprint.global/viewer .
Keyphrases
  • electronic health record
  • big data
  • deep learning
  • machine learning
  • convolutional neural network
  • minimally invasive
  • artificial intelligence
  • human health