Remote sensing for monitoring vegetation disturbance and reclamation for appalachian surface mines: a case study on the fola mining complex in west virginia

Abstract

Surface coal mining has caused a variety of negative environmental impacts, especially in regions like Appalachia. Federal regulations are in place that govern the mining and reclamation of surface coal mines, including placing the responsibility of reclaiming the land on mine operators. Historically, the priority for reclamation was land stability, which was often completed using grasses. However, this led to a loss of native forest resources and a drastic alteration of the landscape. In 2004, the Appalachian Regional Reforestation Initiative was developed to promote reclaiming coal-mined lands to native forest vegetation using the Forestry Reclamation Approach guidelines. Monitoring is a critical component for analyzing mining impacts and reclamation success. This is often completed using field monitoring, which can be time-consuming, expensive, and labor-intensive. Using publicly available remote sensing data offers an alternative, cost-effective method. Therefore, my study used the Fola mining complex in West Virginia to explore applying remote sensing techniques with Landsat satellite data to monitor vegetation and land cover changes. My primary objectives included applying methods of image classification, change detection, and NDVI analysis across the entire complex as well as individual mining permit sites. I also analyzed areas with differing post-mining land uses (hayland versus forest). Results demonstrated that these methods could be successfully applied to assist in assessing reclamation and monitoring through the tracking of vegetation health and land cover changes across times correlating to pre-mining, mining, and reclamation. NDVI results revealed a reduction in vegetation health following mining as well as an increase post-reclamation. When I compared samples from individual mines, the mine using forest vegetation in the reclamation process had significantly higher mean NDVI values. Land classification offered complementary information through tracking patterns of land cover. During active mining, there was an increase in barren land and a reduction in forest. When comparing the specific mines with different post-mining land uses, the mine using forest vegetation had significantly more forest land cover following reclamation. These types of remote sensing tools may provide additional information to managers that contribute to the success of achieving environmental goals, while potentially reducing costs and labor.