2025 NC GIA Lidar DEM: Post-Helene, North Carolina

Product: These data were acquired by the NC Collaboratory at UNC Chapel Hill utilizing funds appropriated by the NC General Assembly. These are Digital Elevation Model (DEM) data for North Carolina as part of the required deliverables for the NC_Lidar_Phase3_Draft_Metadata project. Class 2 (ground) LiDAR points in conjunction with the hydro breaklines were used to create a 3.125 ft, 10-ft, and 20 ft hydro-flattened Raster DEM. The Class 2 points were derived from the proeject data collected and processed at a USGS QL1 level of quality. Geographic Extent: 12 counties in North Carolina, covering approximately 5,060 total square miles. Counties covered in their entirety for this project included: Ashe, Watauga, Avery, Mitchell, Burke, Yancey, McDowell, Rutherford, Buncombe, Henderson, Haywood, and Jackson. Dataset Description: The Helene-North Carolina Priority 1 Lidar and Imagery project called for the planning, acquisition, and processing of lidar data to be collected at an approximate 8 points per square meter to meet USGS QL1 specifications. Project specifications are based on the USGS Lidar Base Specifications along with specific North Carolina Emergency Management standards for the North Carolina Floodplain Mapping Program for lidar classification types and specialized, derivative products. In addition to project oversight AECOM's performed an independent quality assurance effort against project specifications. This effort was limited to a 10% review of the lidar tiles and coincident vector Geodatabases in each county. Additionbally a randomized 5% review of the ESRI terrains, DEM, and intensity rasters was also performed.

To acquire detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments and elevation modeling, etc. Classified LAS files are used to show the manually reviewed bare earth surface. This allows the user to create intensity images, breaklines and raster DEMs. The purpose of these LiDAR data was to produce high accuracy 3D hydro-flattened digital elevation models (DEMs) with a 3.125 ft, 5-ft, and 10 ft cell size. These raw LiDAR point cloud data were used to create classified LiDAR LAS files, intensity images, 3D breaklines, and hydro-flattened DEMs as necessary.

Raster File Type = GeoTIFF; Bit Depth/Pixel Type = 32-bit float; Raster Cell Size = 3.125 ft, 5-ft, and 10 ft; Interpolation or Resampling Technique = Triangulated Irregular Network (TIN), Linear Interpolation, Proprietary; Required Vertical Accuracy = 0.196

Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners

To the extent possible under law, the U.S. Government has waived all copyright and related or neighboring rights to this dataset.

Data is available online for bulk or custom downloads

None

Users should be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions. Users should not use this data for critical applications without a full awareness of its limitations.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data, Edition 2 (2023) for a 22(cm) RMSEh horizontal positional accuracy Class.

The specifications require that only nonvegetated vertical accuracy (NVA) be computed for raw LiDAR data swath files. The vertical accuracy was tested with 81 independent survey points located in open terrain. These check points were not used in the calibration or post processing of the LiDAR data. The survey check points were distributed throughout the project area.Qualitative value:0.0219

, Test that produced the value: This data set was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data, Edition 2 (2023) for a 10 (cm) RMSEv Vertical Accuracy Class. NVA accuracy was found to be RMSEv = 2.19 (cm).

Datasets contain complete coverage of tiles. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. There are no void areas or missing data. The raw point cloud is of good quality and data pass Non-Vegetated Vertical Accuracy specifications.

Data cover the entire area specified for this project.