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Global mining footprint mapped from high-resolution satellite imagery

Authors: Liang Tang; Tim T. Werner;

Global mining footprint mapped from high-resolution satellite imagery

Abstract

AbstractMining is of major economic, environmental and societal consequence, yet knowledge and understanding of its global footprint is still limited. Here, we produce a global mining land use dataset via remote sensing analysis of high-resolution, publicly available satellite imagery. The dataset comprises 74,548 polygons, covering ~66,000 km2 of features like waste rock dumps, pits, water ponds, tailings dams, heap leach pads and processing/milling infrastructure. Our polygons finely contour the edges of mine features and do not include the space between them. This distinguishes our dataset from others that employ broader definitions of mining lands. Hence, despite our database being the largest to date by number of polygons, comparisons show relatively lower global land use. Our database is made freely available to support future studies of global mining impacts. A series of spatial analyses are also presented that highlight global mine distribution patterns and broader environmental risks.

Countries
United States, Australia
Related Organizations
Keywords

economic impact, QE1-996.5, 550, Illegal Mining, Spatial analysis, Satellite imagery, Geology, mining, Remote sensing, Mining, Environmental, 004, Environmental sciences, Extractive industries, Spatial patterns, Land use, Global footprint, GE1-350, Satellite data analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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97
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906
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