For these three statewide datasets of North Carolina, information was extracted and post processed from lidar derived digital elevation models (DEMs) at 10 ft. and 30ft. resolution. Datasets are currently used for the project SPARROW Modeling for North Carolina Watersheds, but have the potential to be used in numerous applications. Slope area index (SAI), the ten most common geomorphons (i.e. geomorphologic feature), and topographic openness are included in this data release and should be utilized based on user needs.

Rasters of the ten most common geomorphic landscape forms (geomorphons) were developed with 1-meter resolution for the Greater Raleigh, NC Area, based on 1-meter high-resolution lidar-derived digital elevation models representing the years 2013, 2015, and 2022. The ten geomorphons include the landscape forms representing peaks, ridges, shoulders, spurs, slopes, hollows, footslopes, valleys, pits, and flat areas. All files are available as Cloud Optimized GeoTIFF image file format, meaning they are formatted to work on the cloud or can be directly downloaded.

Rasters of the ten most common geomorphic landscape forms (geomorphons) were developed with 1-meter resolution for the Greater Raleigh, NC Area, based on 1-meter high-resolution lidar-derived digital elevation models representing the years 2013, 2015, and 2022. The ten geomorphons include the landscape forms representing peaks, ridges, shoulders, spurs, slopes, hollows, footslopes, valleys, pits, and flat areas. All files are available as Cloud Optimized GeoTIFF image file format, meaning they are formatted to work on the cloud or can be directly downloaded.

As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey developed a suite of high-resolution lidar-derived raster datasets for the Greater Raleigh Area, North Carolina, using repeat lidar data from the years 2013, 2015, and 2022. These datasets include raster representations of digital elevation models (DEMs), DEM of difference, the ten most common geomorphons (i.e. geomorphologic feature), lidar point density, and positive topographic openness. Raster footprints vary by year based on extent of lidar data collection. All files are available as Cloud Optimized GeoTIFF, meaning they are formatted to work on the cloud or can be directly downloaded. These metrics have been developed to pair with field geomorphic assessments for use in the development of a model that can remotely predict streambank erosion potential along streams in the Greater Raleigh, NC Area, however, they have the potential to be used in numerous applications.

As part of a collaborative study with the City of Raleigh, North Carolina, the U.S. Geological Survey developed a drainage network for the Greater Raleigh Area, North Carolina using the most recent available lidar data, representing the years 2015 and 2022. This dataset includes the delineated drainage network (drainage_network.zip) and rasters representing the breached and filled digital elevation model (raleigh_dem_fil.tif), the flow accumulation raster (raleigh_d8_fac.tif), and the flow direction raster (raleigh_d8_fdr.tif). Raster files are available as Cloud Optimized GeoTIFFs, meaning they are formatted to work on the cloud or can be directly downloaded. The drainage network was delineated for all locations with an upstream drainage area greater than 0.075 square kilometers (approximately 18.5 acres) and represents perennial streams, ephemeral streams, ditches, stream buried in pipes, and artificial paths through water bodies. This dataset was developed for use in the development of a model that can remotely predict streambank erosion potential along streams in the Greater Raleigh, NC Area. However, the drainage network and supporting raster files have the potential to be used in numerous applications including watershed delineation.

Digital elevation models (DEMs) were developed from lidar surveys from 2013, 2015, and 2022 for the Greater Raleigh, NC Area, with 1-meter resolution. A DEM of difference raster was also developed to represent change in elevation from 2015 to 2022. The 2015 and 2022 DEMs were selected for differencing because of the superior quality level (QL2) of base lidar data used to develop the DEMs compared with the poorer quality level (QL3) of base lidar data used to develop the 2013 DEM. The DEMs were developed to use as inputs to generate a suite of geomorphic metrics for use in a machine learning model to predict streambank erosion hotspots. All files are available as Cloud Optimized GeoTIFF, meaning they are formatted to work on the cloud or can be directly downloaded.

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina (NCnorth), central North Carolina (NCcentral), southern North Carolina (NCsouth), and western North Carolina (NCwest). Previously published historical shorelines for North Carolina (Kratzmann and others, 2017) were combined with the new lidar shoreline to calculate long-term (up to 169 years) and short-term (up to 20 years) rates of change. Files associated with the long-term and short-term rates are appended with "LT" and "ST", respectively. A proxy-datum bias reference line that accounts for the positional difference in a proxy shoreline (e.g. High Water Line (HWL) shoreline) and a datum shoreline (e.g. MHW shoreline) is also included in this release.

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina (NCnorth), central North Carolina (NCcentral), southern North Carolina (NCsouth), and western North Carolina (NCwest). Previously published historical shorelines for North Carolina (Kratzmann and others, 2017) were combined with the new lidar shoreline to calculate long-term (up to 169 years) and short-term (up to 20 years) rates of change. Files associated with the long-term and short-term rates are appended with "LT" and "ST", respectively. A proxy-datum bias reference line that accounts for the positional difference in a proxy shoreline (e.g. High Water Line (HWL) shoreline) and a datum shoreline (e.g. MHW shoreline) is also included in this release.

The 10 most common geomorphic features are identified for the state of North Carolina using Lidar derived DEMs at 30 ft. resolution. This product uses r.geomorphon, a feature in GRASS GIS, to calculate the geomorphic features for the state. The tool requires a user input length scale and slope for calculation. This dataset uses 60 cells, or 1800 ft. as the length scale and two different slope values of 1 degree (Blue Ridge/Piedmont ecoregion) and 0.0001 degree (Coastal Plain ecoregion).

The U.S. Geological Survey (USGS) has compiled national shoreline data for more than 20 years to document coastal change and serve the needs of research, management, and the public. Maintaining a record of historical shoreline positions is an effective method to monitor national shoreline evolution over time, enabling scientists to identify areas most susceptible to erosion or accretion. These data can help coastal managers and planners understand which areas of the coast are vulnerable to change. This data release includes one new mean high water (MHW) shoreline extracted from lidar data collected in 2017 for the entire coastal region of North Carolina which is divided into four subregions: northern North Carolina (NCnorth), central North Carolina (NCcentral), southern North Carolina (NCsouth), and western North Carolina (NCwest). Previously published historical shorelines for North Carolina (Kratzmann and others, 2017) were combined with the new lidar shoreline to calculate long-term (up to 169 years) and short-term (up to 20 years) rates of change. Files associated with the long-term and short-term rates are appended with "LT" and "ST", respectively. A proxy-datum bias reference line that accounts for the positional difference in a proxy shoreline (e.g. High Water Line (HWL) shoreline) and a datum shoreline (e.g. MHW shoreline) is also included in this release.