2018 NRCS Lidar DEM: Calhoun, Clarendon and Orangeburg Counties, SC

The Digital Elevation Model dataset consists of tiled LiDAR DEM Images. Each file contains a Raster Image of the Digital Elevation Model. The Geographical Extent of this dataset covers approximately 2215 square miles for the QL2 area covering Calhoun, Clarendon and Orangeburg counties in SC. The flight plan consisted of 201 survey lines and 3 control lines.

Ground Conditions: water at normal levels; no unusual inundation; no snow; leaf off

This metadata record supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the GeoTIFF files hosted by USGS on Amazon Web Services.

The USGS/NGTOC and US Forest Service contracted Digital Aerial Solutions, LLC to obtain professional services related to the planning, acquisition and development of Light Detection and Ranging (Lidar) data and derivative products. The task order is for a QL2 Lidar survey to be collected over Calhoun, Clarendon and Orangeburg counties in SC. The deliverable products would be used by the USGS/NGTOC and US Forest Service for conservation planning, design, research, floodplain mapping, wetlands identification, dam safety assessments, hydrologic modeling, and other environmental purposes.

All Lidar data and associated products were acquired, calibrated, and used in the creation of Lidar derived products by Digital Aerial Solutions, LLC. Raster File Type = IMG Bit Depth/Pixel Type = 32-bit float Raster Cell Size = 1 Meter Interpolation or Resampling Technique = Bilnear Interpolation Required Vertical Accuracy = 19.6 cm NVA

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

Data is available online for bulk and custom downloads.

No restrictions apply to this data. The data represented is the result of data collection and processing per contract specifications and indicates the general existing conditions at the time of the data collection. As such, it is only valid for its intended use, content, time, and accuracy specifications. The user is responsible for the results of any application of the data for other than its intended purpose.

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be aware that temporal changes may have occurred since this data set was collected and some parts of this data may no longer represent actual surface conditions.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.

Acknowledgment of the US Geological Survey would be appreciated for products derived from these data. The data represented is the result of data collection and processing per contract specifications and indicates the general existing conditions at the time of the data collection. As such, it is only valid for its intended use, content, time, and accuracy specifications. The user is responsible for the results of any application of the data for other than its intended purpose.

Inertial Explorer ver: 8.6; Leica CloudPro Ver:1.2.1; GeoCue Ver: 2014.1.21.4; Microstation V8i; Terresolid ver: 2015; LP360 ver: 2014.1.51.1; Arcmap ver: 10.4; Global Mapper ver: 16

Horizontal error in lidar derived elevation data is largely a function of positional error as derived from the Global Navigation Satellite System (GNSS), attitude (angular orientation) error (as derived from the INS) and flying altitude; and can be estimated based on these parameters.

This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.226 Meters RMSEx / RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy =+/- 0.783 Meters at a 95% confidence level Estimated LiDAR Horizontal Error Per Point.

Vertical Accuracy of the bare-earth lidar data was assessed and reported in accordance with the ASPRS Positional Accuracy Standards for Digital Geospatial Data. One-Hunderd Thirty-Five (135) surveyed points were measured for the purpose of assessing the accuracy of the SC East Central QL2 data (76 NVA + 59 VVA). Both data sets, Lidar and Digital Elevation Models (DEMs) have been tested for their individual vertical accuracy levels. The Lidar was tested by using interpolation while the DEMs where tested by extracting the elevation of a pixel containing the checkpoint. Required Non Vegetated Vertical Accuracy (NVA): 0.196 Meters. Required Vegetated Vertical Accuracy (VVA): 0.294 Meters.

DEM: Tested to be 0.111 meters NVA at 95-percent confidence level using RSME(z) x 1.9600 as defined by the National Standards for spatial Data Accuracy (NSSDA). The root mean square error vertical (RMSEz) was computed to be 0.055 meters. The NVA of the Classified LiDAR point cloud was calculated against TINs derived from the final calibrated and controlled swath data using 76 NVA checkpoints located in Bare Earth land cover class.

DEM: Tested 0.113 meters VVA at 95th percentile in all vegetated land cover categories combined using the absolute value 95th percentile error as defined by the National Standards for spatial Data Accuracy (NSSDA). The VVA of the Classified LiDAR point cloud was calculated against TINs derived from the final calibrated and controlled swath data using 59 VVA checkpoints located in the Brushlands, Trees, Tall Weeds and Crops land cover categories.

The raw LAS data files included all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Fundamental Vertical Accuracy specifications. Void areas (i.e., areas outside the project boundary but within the tiling scheme) are coded using a unique NODATA value. This value is identified in the appropriate location within the file header.

Aerial LiDAR data covers the entire 2,215 square mile Area of Interest intended for this project task. All LiDAR Point Cloud tiles show no edge artifacts or mismatches from tile to tile. Void areas (i.e., areas outside the project boundary but within the tiling scheme) are coded using a unique “NODATA” value. This value is identified in the appropriate location within the file header. Data cover the entire area specified for this project.

Data is backed up to tape and to cloud storage.

The NOAA Office for Coastal Management (OCM) ingested references to the USGS GeoTIFF files that are hosted on Amazon Web Services (AWS), into the Digital Coast Data Access Viewer (DAV). The DAV accesses the raster data as it resides on AWS.