Lidar-derived closed depression vector data and density raster in karst areas of Monroe County, West Virginia
Monroe County in southeastern West Virginia hosts world-class karst within carbonate units of Mississippian and Ordovician age. Lidar-derived elevation data acquired in late December of 2016 were used to create a 3-meter resolution working digital elevation model (DEM), from which surface depressions were identified using a semi-automated workflow in ArcGIS®. Depressions in the automated inventory were systematically checked by a geologist within a grid of 1.5 square kilometer tiles using aerial imagery, lidar-derived imagery, and 3D viewing of the lidar imagery. Distinguishing features such as modification by human activities or hydrological significance (stream sink, ephemerally ponded, etc.) were noted wherever relevant to a particular depression. Relative confidence in depression identification was provided and determined by whether the depression was visible in the lidar imagery, aerial imagery, or both. Statistics on the geometric morphometry of each depression were calculated including perimeter, area, depth, length of major and minor elliptical axes, and azimuth of the major axis. Center points were created for each surface depression and were used to create a point density raster. The density raster displays the number of closed depression points per square kilometer.
Complete Metadata
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| description | Monroe County in southeastern West Virginia hosts world-class karst within carbonate units of Mississippian and Ordovician age. Lidar-derived elevation data acquired in late December of 2016 were used to create a 3-meter resolution working digital elevation model (DEM), from which surface depressions were identified using a semi-automated workflow in ArcGIS®. Depressions in the automated inventory were systematically checked by a geologist within a grid of 1.5 square kilometer tiles using aerial imagery, lidar-derived imagery, and 3D viewing of the lidar imagery. Distinguishing features such as modification by human activities or hydrological significance (stream sink, ephemerally ponded, etc.) were noted wherever relevant to a particular depression. Relative confidence in depression identification was provided and determined by whether the depression was visible in the lidar imagery, aerial imagery, or both. Statistics on the geometric morphometry of each depression were calculated including perimeter, area, depth, length of major and minor elliptical axes, and azimuth of the major axis. Center points were created for each surface depression and were used to create a point density raster. The density raster displays the number of closed depression points per square kilometer. |
| distribution |
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| identifier | http://datainventory.doi.gov/id/dataset/USGS_609ad73bd34ea221ce36fe61 |
| keyword |
[
"Monroe County",
"USGS:609ad73bd34ea221ce36fe61",
"United States",
"West Virginia",
"geologic maps",
"geology",
"geomorphology",
"geospatial analysis",
"hydrogeology",
"karst",
"maps and atlases",
"sinkhole formation"
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|
| modified | 2021-07-19T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
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| spatial | -80.8585, 37.37, -80.2195, 37.7321 |
| theme |
[
"Geospatial"
]
|
| title | Lidar-derived closed depression vector data and density raster in karst areas of Monroe County, West Virginia |
