Vienna University of Economics and Business (WU), Institute for Ecological Economics, Vienna, 1020, Austria.
International Institute for Applied Systems Analysis (IIASA), Advancing Systems Analysis Program, Laxenburg, A-2361, Austria.
Sci Data. 2022 Jul 22;9(1):433. doi: 10.1038/s41597-022-01547-4.
The growing demand for minerals has pushed mining activities into new areas increasingly affecting biodiversity-rich natural biomes. Mapping the land use of the global mining sector is, therefore, a prerequisite for quantifying, understanding and mitigating adverse impacts caused by mineral extraction. This paper updates our previous work mapping mining sites worldwide. Using visual interpretation of Sentinel-2 images for 2019, we inspected more than 34,000 mining locations across the globe. The result is a global-scale dataset containing 44,929 polygon features covering 101,583 km of large-scale as well as artisanal and small-scale mining. The increase in coverage is substantial compared to the first version of the dataset, which included 21,060 polygons extending over 57,277 km. The polygons cover open cuts, tailings dams, waste rock dumps, water ponds, processing plants, and other ground features related to the mining activities. The dataset is available for download from https://doi.org/10.1594/PANGAEA.942325 and visualisation at www.fineprint.global/viewer .
对矿产的需求不断增长，促使采矿活动进入新的地区，这些地区越来越多地影响到生物多样性丰富的自然生物群落。因此，对全球矿业土地利用进行测绘是量化、了解和减轻矿产开采造成的不利影响的前提。本文更新了我们之前对全球采矿地点进行测绘的工作。我们使用 2019 年 Sentinel-2 图像的目视解释，检查了全球 34000 多个采矿地点。其结果是一个包含 44929 个多边形特征的全球范围数据集，涵盖了大规模采矿、手工和小规模采矿，面积达 101583 公里。与数据集的第一个版本相比，覆盖范围有了实质性的增加，第一个版本包括 21060 个多边形，覆盖了 57277 公里。这些多边形覆盖了露天开采、尾矿坝、废石堆、水池、加工厂和其他与采矿活动有关的地面特征。该数据集可从 https://doi.org/10.1594/PANGAEA.942325 下载，并可在 www.fineprint.global/viewer 上进行可视化。
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