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Monroe County, in southeastern West Virginia, hosts world-class karst within carbonate units of Mississippian and Ordovician age. There are at least 412 known caves in the county. Location data for these caves were collected from the West Virginia Speleological Survey (WVASS) Bulletin 22 (Dasher, 2019). Point features were created in ArcGIS Pro for each cave location and were used to make a point density raster. This raster displays the number of cave points per square kilometer.
These raster datasets are 3-meter lidar-derived images of Monroe County, West Virginia, and were created using geographic information systems (GIS) software. 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 a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create a 3-meter resolution lidar-derived image. The data is projected in North America Datum (NAD) 1983 UTM Zone 17.
This raster dataset contains 3-meter digital elevation models (DEMs) of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using GlobalMapper v.23 software. These DEMs were derived from 1-meter DEM tiles acquired through the USGS 3D Elevation Program (3DEP). The data are projected in North America Datum (NAD) 1983 (2011) UTM Zone 19N.
The Winchester 30 x 60 minute quadrangle, covering northern Virginia, West Virginia, and Maryland, hosts karsts within carbonate units of Devonian to Cambrian age. Lidar-derived elevation data, acquired between 2011 and 2019, were used to create a mosaic of 1-meter resolution working digital elevation models (DEMs), from which surface depressions were identified using a semi-automated workflow in ArcGIS. Depressions in the automated inventory were systematically checked by a geologist 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...
Categories: Data;
Tags: 30 x 60 minute,
Geomorphology,
Hydrology,
Maryland,
USGS Science Data Catalog (SDC),
This raster dataset contains 1-meter lidar-derived imagery of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using geographic information systems (GIS) software. Lidar-derived elevation data, acquired in 2018, were used to create a 1-meter resolution working digital elevation model (DEM). To create this imagery, a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create these 1-meter resolution lidar-derived images. The data is projected in North America Datum (NAD) 1983 (2011) UTM Zone 19N.
Categories: Data;
Tags: Geomorphology,
Puerto Rico,
USGS Science Data Catalog (SDC),
United States,
data release,
This raster dataset contains 1-meter lidar-derived imagery of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using geographic information systems (GIS) software. Lidar-derived elevation data, acquired between 2015 and 2017, were used to create a 1-meter resolution working digital elevation model (DEM). To create this imagery, a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create these 1-meter resolution lidar-derived images. The data is projected in North America Datum (NAD) 1983 (2011)...
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...
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