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Eberly College of Arts and Sciences




Surface mining for coal has taken place in the Central Appalachian region of the United States for well over a century, with a notable increase since the 1970s. Researchers have quantified the ecosystem and health impacts stemming from mining, relying in part on a geospatial dataset defining surface mining’s extent at a decadal interval. This dataset, how- ever, does not deliver the temporal resolution necessary to support research that could establish causal links between mining activity and environmental or public health and safety outcomes, nor has it been updated since 2005. Here we use Google Earth Engine and Landsat imagery to map the yearly extent of surface coal mining in Central Appalachia from 1985 through 2015, making our processing models and output data publicly available. We find that 2,900 km2 of land has been newly mined over this 31-year period. Adding this more-recent mining to surface mines constructed prior to 1985, we calculate a cumulative

2 mining footprint of 5,900 km . Over the study period, correlating active mine area with histor-

ical surface mine coal production shows that each metric ton of coal is associated with 12 m2 of actively mined land. Our automated, open-source model can be regularly updated as new surface mining occurs in the region and can be refined to capture mining reclamation activity into the future. We freely and openly offer the data for use in a range of environmen- tal, health, and economic studies; moreover, we demonstrate the capability of using tools like Earth Engine to analyze years of remotely sensed imagery over spatially large areas to quantify land use change.

Source Citation

Pericak AA, Thomas CJ, Kroodsma DA, Wasson MF, Ross MRV, Clinton NE, et al. (2018) Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine. PLoS ONE 13(7): e0197758. https://doi. org/10.1371/journal.pone.0197758


: © 2018 Pericak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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