Digital Elevation Model (DEM) derived from lidar data.

LiDAR data collection was performed utilizing a Leica ALS-50 sensor, collecting multiple return x, y, and z data as well as intensity data. LiDAR data was processed to achieve a bare ground surface, and was delivered in LAS format. Classified LAS data was also used as a base for collection of hydro features, delivered in MicroStation v8...

Axis Geospatial collected 1265 square miles in the South Carolina county of Berkeley, and 1124 sq miles in Charleston County. Precision Aerial Reconnaissance collected 965 square miles in Williamsburg county. The nominal pulse spacing for this project was 1 point every 0.7 meters. Dewberry used proprietary procedures to classify the LAS according to project specifications: 1-Unclassified, 2-G...

These data were created as part of the National Oceanic and Atmospheric Administration Office for Coastal Management's efforts to create an online mapping viewer called the Sea Level Rise and Coastal Flooding Impacts Viewer. It depicts potential sea level rise and its associated impacts on the nation's coastal areas. The purpose of the mapping viewer is to provide coastal managers and scientists with a preliminary look at sea level rise and coastal flooding impacts. The viewer is a screening-level tool that uses nationally consistent data sets and analyses. Data and maps provided can be used at several scales to help gauge trends and prioritize actions for different scenarios. The Sea Level Rise and Coastal Flooding Impacts Viewer may be accessed at: https://coast.noaa.gov/slr. This metadata record describes the South Carolina Central digital elevation model (DEM), which is a part of a series of DEMs produced for the National Oceanic and Atmospheric Administration Office for Coastal Management's Sea Level Rise and Coastal Flooding Impacts Viewer described above. This DEM includes the best available lidar known to exist at the time of DEM creation that met project specifications. This DEM includes data for Charleston, Berkeley and Dorchester Counties. The DEM was produced from the following lidar data sets: 1. 2017 SC DNR Lidar DEM: Charleston County, SC 2. 2017 SC DNR Lidar DEM: Berkeley County, SC 3. 2007 SC DNR Lidar DEM: Dorchester County, SC The DEM is referenced vertically to the North American Vertical Datum of 1988 (NAVD88, Geoid12B) with vertical units of meters and horizontally to the North American Datum of 1983 (NAD83). The resolution of the DEM is approximately 3 meters.

BERKELEY, CHARLESTON, ORANGEBURG LIDAR DATA COLLECTION Lidar Data Acquisition and Processing Production Task Charleston County Contract Number: 6004 RFQ Number: 6004-25C Woolpert Order No: 10020258 CONTRACTOR: Woolpert Lidar data is a remotely sensed high-resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. This task order requires lidar data to be acquired over Charleston County (+/- 1,197 square miles). This lidar data set is comprised of lidar point cloud data, raster DEMs, raster DSMs, raster intensity imagery, and GPS flight line trajectory data. The task required the lidar data to be collected at a nominal pulse spacing (NPS) of 1.15 feet. The lidar dataset was produced using a horizontal datum/projection of NAD83, State Plane South Carolina, International Feet and a vertical datum of NAVD88 (Geoid 18), International Feet. Tidal areas in Charleston's data acquisition were collected within +/- 2 hours of low tide. Additional deliverables include control data and tile index in Esri shapefile format, lidar processing and survey reports in PDF format, and project-level FGDC CSDGM metadata in XML format. This data was provided to the NOAA Office for Coastal Management (OCM) by the Charleston County Public Works Department, for the purpose of making the data publicly available for custom and bulk downloads from the NOAA Digital Coast Data Access Viewer.

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