mineBenchDL: A geomorphology deep learning dataset of historic surface coal mine benches in West Virginia, USA

mineBenchDL Dataset
A dataset for geomorphic deep learning. Goal is to detect historic mine benches resulting from surface coal mining from lidar-derived digital terrain models. Mine bench extents were manually digitized via interpretation of lidar-derived terrain data, leaf-off aerial imagery, and ancillary geospatial data. Mine bench extents have been provided as vector data. The elev folder contains the lidar-derived elevation data at a 2 m spatial resolution. The images folder contains a 3 band stack of terrain variables. The masks folder contains a binary feature mask. Data were randomly split into training, test, and validation sets randomly using quarter quad boundaries
*All layers in NAD83 UTM Zone 17N
trainQQs.csv: quarter quads randomly selected as training set (69 quarter quads)
testQQs.csv: quarter quads randomly selected as test set (49 quarter quads)
valQQs.csv: quarter quads randomly selected as validation set (50 quarter quads)
vectors folder:
mineBenches.shp = digitized mine bench features (QKEY field used as unique ID)
quarterQuads.shp = quarter quad boundaries (just those containing mine benches)
images folder:
3 band stack of land surface parameter predictor variables (2 m spatial resolution).
The first layer is a topographic position index (TPI) calculated using a moving window
with a 50 m circular radius and designed to characterize general hillslope position.
The second layer is the square root of slope calculated in degrees, which provides a
measure of steepness. The third layer is another TPI; however, it is calculated using
an annulus moving window with an inner radius of 2 and outer radius of 5 m. This surface
captures more local relief and surface roughness patterns in comparison to the other TPI.
Values for both TPIs and the square root of slope were clamped to a range of -10 to 10 then
linearly rescaled to a range of 0 to 1.
masks folder:
Mine bench raster masks (1 band, 1 = bench, 0 = background)