North Carolina Synthetic Elevation Checkpoints, Simple Version
The geospatial datasets describe positions, elevations, and uncertainties for synthetic elevation checkpoints generated across the developed coastline of North Carolina. Two datasets are provided as point shapefiles and American Standard Code for Information Interchange (ASCII) tables, and each contains synthetic checkpoints generated using a time series (1996-2018) of digital elevation models (DEMs), a road vector network, and a classified landcover dataset. The first 'simple' dataset contains ~10,000 checkpoints and the second 'complex' dataset contains ~7,000 checkpoints. The latter dataset was derived using more demanding processing settings and as a result, checkpoints are more accurate, but fewer in number. These datasets can be used to validate remotely sensed topographic surveys such as lidar and photogrammetry-derived DEMs and digital surface models (DSMs). The methods used to generate these data followed the process outlined in "Automated Generation of a Synthetic Elevation Checkpoint Network across the North Carolina Coastline, USA" by Seymour and others (2025).
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Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[ "010:12" ] |
| contactPoint |
{ "fn": "Kara S. Doran", "@type": "vcard:Contact", "hasEmail": "mailto:kdoran@usgs.gov" } |
| description | The geospatial datasets describe positions, elevations, and uncertainties for synthetic elevation checkpoints generated across the developed coastline of North Carolina. Two datasets are provided as point shapefiles and American Standard Code for Information Interchange (ASCII) tables, and each contains synthetic checkpoints generated using a time series (1996-2018) of digital elevation models (DEMs), a road vector network, and a classified landcover dataset. The first 'simple' dataset contains ~10,000 checkpoints and the second 'complex' dataset contains ~7,000 checkpoints. The latter dataset was derived using more demanding processing settings and as a result, checkpoints are more accurate, but fewer in number. These datasets can be used to validate remotely sensed topographic surveys such as lidar and photogrammetry-derived DEMs and digital surface models (DSMs). The methods used to generate these data followed the process outlined in "Automated Generation of a Synthetic Elevation Checkpoint Network across the North Carolina Coastline, USA" by Seymour and others (2025). |
| distribution |
[ { "@type": "dcat:Distribution", "title": "Digital Data", "format": "XML", "accessURL": "https://doi.org/10.5066/P1HZA84J", "mediaType": "application/http", "description": "Landing page for access to the data" }, { "@type": "dcat:Distribution", "title": "Original Metadata", "format": "XML", "mediaType": "text/xml", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.688436dc-b1e4-4a0d-b397-96b2b2abecee.xml" } ] |
| identifier | http://datainventory.doi.gov/id/dataset/USGS_688436dc-b1e4-4a0d-b397-96b2b2abecee |
| keyword |
[ "CMHRP", "Coastal and Marine Hazards and Resources Program", "SPCMSC", "St. Petersburg Coastal and Marine Science Center", "U.S. Geological Survey", "USGS", "USGS:688436dc-b1e4-4a0d-b397-96b2b2abecee", "aerial photography", "coastal processes", "digital elevation models", "earth sciences", "environment", "erosion", "floods", "geoscientificInformation", "geospatial datasets", "hazards", "lidar", "marine geology", "ocean sciences", "oceans", "remote sensing", "structure", "structure from motion", "time series analysis", "time series datasets" ] |
| modified | 2025-05-09T00:00:00Z |
| publisher |
{ "name": "U.S. Geological Survey", "@type": "org:Organization" } |
| spatial | -78.516605, 33.846311, -75.462562, 36.543159 |
| theme |
[ "geospatial" ] |
| title | North Carolina Synthetic Elevation Checkpoints, Simple Version |
