Update on Our Efforts to Map Surface Mining in Appalachia

Some time has passed since we’ve written about our work mapping surface mining in central Appalachia, but rest assured, we’re still actively monitoring this devastating practice. Our mining work to date has focused on mapping the locations of these operations.

Researchers, some of whom are using our data, are beginning to draw troubling connections between coal mining and the health of people living in communities near those operations. We are working to refine our mapping processes and enable new types of analysis to help understand the environmental and public health consequences of mountaintop removal mining.

The process we used to create our annual maps of surface mining from 1985-2015, relies on the use of a Normalized Difference Vegetation Index (NDVI). NDVI essentially measures a ratio of reflected red and near-infrared light and is particularly useful for detecting changes in vegetation. When areas within the scope of our study experience a change from forest to bare earth, this registers as mineland. The analysis is available here: skytruthmtr.appspot.com

This NDVI image shows the Hobet 21 Coal Mine in West Virginia. Vegetated areas are visualized in white, while bare earth is seen as dark grey or black.

We are working with Dr. Matt Ross, an ecosystem scientist from the University of North Carolina at Chapel Hill, to improve our mining identification algorithm, and add the capacity to evaluate how landscapes affected by surface mining recover over time. This algorithm is an integral step in assessing the efficacy of the reclamation efforts undertaken by mine operators. We expect our mapping will allow researchers to conduct more robust studies on the long-term environmental and health impacts of surface mining, which in turn will help mining-impacted communities hold industry and government accountable for repairing the damage done to Appalachian landscapes, ecosystems and public health. We also hope the work will stimulate government investment as coal mining declines throughout the region, enabling a just transition to a new economy.

The following slider compares one of the new indexes we are incorporating into our work, a Normalized Difference Moisture Index (NDWI), with NDVI at the Hobet 21 Coal Mine. NDWI measures the relative amounts of moisture present in landscapes, densely vegetated areas have high NDMI values, while sparsely vegetated areas or bare earth have lower values. By incorporating new indices we are gaining a better understanding of how the land is affected by these operations. It is worth noting, therefore, the low amount of moisture present across the mine, even in those areas which appear to be recovering in the NDVI.

Global Flaring Volume Map

Interactive Map Detects Gas Flaring Volume Worldwide

SkyTruth has built on NOAA’s work in estimating natural gas flaring volume by creating an interactive map showing individual flaring locations as identified by NOAA’s Earth Observation Group (EOG).

Flaring – the method of burning off the unwanted natural gas in massive, open flames – is a chronic practice in oil fields around the world. While flaring can be a safety measure used to avoid buildup of explosive gases, it often indicates the operator has concluded the cost of building a pipeline for the gas exceeds the value of the lost revenue. If this gas was captured or used to produce electricity on-site, this wasted energy could supplement the electrical grid without burning coal and ease the market demand that drives the drilling and fracking of shale-gas wells elsewhere.

Why are site-specific estimates important? Besides providing knowledge of the locations and magnitudes of greenhouse gas emissions, gas flaring has been shown to affect wildlife, public health, and even agriculture negatively.

SkyTruth’s map makes site data available over virtually any Area of Interest (AOI). As of November 2017, the dataset includes annual estimates for years 2012 through 2016.

Global Flaring Volume Map

With a few clicks, the SkyTruth map lets you:

  • Visually see the location of each flaring site
  • Click for details from the EOG dataset
  • Identify custom Area of Interests (AOI) by either drawing on the map, selecting a range of preloaded AOIs (Country, State, County, Province, Federal Lands), or uploading your own GeoJSON file
  • Download flaring data that falls within any AOI

You can view this map yourself at https://viirs.skytruth.org/apps/heatmap/flarevolume.html.

A description of how EOG estimates flaring volume is detailed in this paper. Details of the nightfire algorithm that detects hot sources from the VIIRS instrument can be found in this paper.