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Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine

Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine

Full Title: Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine
Author(s): Andrew A. Pericak, Christian J. Thomas, David A. Kroodsma, Matthew F. Wasson, Matthew R. V. Ross, Nicholas E. Clinton, David J. Campagna, Yolandita Franklin, Emily S. Bernhardt, John F. Amos
Publisher(s): PLoS ONE
Publication Date: July 1, 2018
Full Text: Download Resource
Description (excerpt):

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, however, 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 mining footprint of 5,900 km2. Over the study period, correlating active mine area with historical 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 environmental, 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.

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