Overview

The sections below describe the methods used in generating our Mining datasets available on the data page or through an API.

Annual Mining Extents

We produce a dataset, updated annually, of the extent of surface mining operations in Central Appalachia. This dataset identifies the spatial extent of mines based on Normalized Difference Vegetation Index (NDVI) thresholds defined using Landsat annual greenest pixel composites. For more information about the specific approach see our paper published in PLOS, Mapping the yearly extent of surface coal mining in Central Appalachia using Landsat and Google Earth Engine. Data, using the methods described in the PLOS paper, is available from 1985 to the current year (annual updates are published in November). Data for the most recent year is provisional at the time of publication, as the cleaning methodology will be implemented the following year.

We have created a dataset of annual mining extents from 1973 - 1984, derived from Landsat MSS imagery. This data is produced using a methodology similar to the one described in the PLOS publication (linked in the section above), and is released as a provisional data product.

Post-mining Landscapes

We provide datasets describing the status of post-mining landscapes. These datasets explore the ecological performance of mine sites which are no longer identified as active, and compare the spectral characteristics of each site to reference forest sites located in the same EPA Level-4 Ecoregion.

Highwall Features

We have developed a methodology for detecting and characterizing highwall features within larger mining operations. Highwalls are the most expensive features of mines to reclaim, and understanding their location and size is critical to ensure that legally required bonds are adequate to restore landscapes in the event that mine operators fail to do so. Using recent LiDAR-derived digital elevation models of the Central Appalachian region, the methodology delineates areas of steep slope, measures highwall height and length, and calculates estimated costs of backfilling and regrading highwalls into stable slopes. The dataset also incorporates mining permit data to determine accountability and compare estimated reclamation liability to available permit-specific bonds.

Publications

Thomas, C.J., Shriver, R.K., Nippgen, F., Hepler, M., Ross, M.R.V., 2022. Mines to forests? Analyzing long-term recovery trends for surface coal mines in Central Appalachia. Restoration Ecology 31(5), e13827. 
https://doi.org/10.1111/rec.13827
Pericak, A.A., Thomas, C.J., Kroodsma, D.A., Wasson, M.F., Ross, M.R.V., Clinton, N.E., 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

Data Sources

Data
Purpose
Source
Landsat 1–3 satellite imagery
Project: 1973–1984 Annual Mining Extents
Mine detection
Landsat 4–9 satellite imagery
Project: 1985–2025 Annual Mining Extents
Mine detection and ecological performance monitoring
County Boundaries, Roads, 
Urban Areas, Water Features 
(Area and Linear)
Project: Annual Mining Extents
Data masking, threshold determination (county boundaries)
NAIP: National Agriculture Imagery Program
Project: Annual Mining Extents
Accuracy Assessment
Level IV Ecoregion Boundaries
Project: Post-mining ecological assessment
Selection of reference forest sites, ecological baseline establishment
Abandoned Mine Land Inventory System (e-AMLIS)
Project: Mining API
Data visualization and analysis
LiDAR Elevation Data
Project: Highwall Analysis, Topographic Disturbance Analysis
Terrain analysis, Elevation change analysis
High-resolution satellite imagery
Project: Highwall Analysis
Highwall detection confirmation
Mining permit and reclamation bond data
Project: Highwall Analysis
Match highwalls with associated permittees and available reclamation bonds
Refuse impoundments and prep plants
Project: Highwall Analysis
Exclude highwalls intersecting non-surface mining permits
Annual surface mining detections
Project: Highwall Analysis, Topographic Disturbance Analysis
Limit highwall detections to mined areas; estimate highwall age
National elevation dataset
Project: Topographic Disturbance Analysis
Elevation change analysis