gov.noaa.nmfs.inport:53150 eng UTF8 dataset National Geodetic Survey resourceProvider NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact 2026-03-04T19:17:17 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) 2016-2017 NOAA NGS Topobathy: Coastal South Carolina 2018-08-24 publication NOAA/NMFS/EDM 53150 https://www.fisheries.noaa.gov/inport/item/53150 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information https://coast.noaa.gov WWW:LINK-1.0-http--link Office for Coastal Management Online Resource download https://coast.noaa.gov/dataviewer WWW:LINK-1.0-http--link Digital Coast Data Access Viewer Online Resource download https://coast.noaa.gov/digitalcoast/data/home.html WWW:LINK-1.0-http--link Digital Coast Online Resource download These data were collected by Quantum Spatial, Inc. (QSI) for the National Oceanic and Atmospheric Administration (NOAA), National Geodetic Survey (NGS), Remote Sensing Devision (RSD), Coastal Mapping Program (CMP) using a Riegl VQ880G system. The dataset includes topobathy data in a LAS 1.2 format file with the following classification: unclassified (1), ground (2), noise (7), overlap default (19), overlap ground (20), overlap water column (21), overlap water surface (22), water column (25), bathymetric bottom or submerged topography (26), water surface (27), and temporal bathy bottom (31), in accordance with project specifications. The contracted project consisted of approximately 519,590 acres along the Atlantic Coast of South Carolina. To ensure complete coverage and adequate point densities around survey area boundaries, the Area of Interest (AOI) was buffered by 100m. LAS files were compiled by 500 m x 500 m tiles. This lidar data (and digital camera imagery collected under the same task order) was required by National Oceanic and Atmospheric Administration (NOAA), the National Geodetic Survey (NGS), Remote Sensing Division Coastal Mapping Program (CMP) to enable accurate and consistent measurement of the national shoreline. The CMP works to provide a regularly updated and consistent national shoreline to define America's marine territorial limits and manage coastal resources. We request that you credit the National Oceanic and Atmospheric Administration (NOAA) when you use these data in a report, publication, or presentation. completed NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information pointOfContact NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information custodian notPlanned https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8575/supplemental/sc2016_ngs_topobathy_m8575.kmz This graphic shows the lidar footprint for the 2017 NOAA NGS topobathy lidar project of the South Carolina coast. EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > TOPOGRAPHICAL RELIEF MAPS EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > SEAFLOOR TOPOGRAPHY EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION theme Global Change Master Directory (GCMD) Science Keywords 17.0 CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > SOUTH CAROLINA place Global Change Master Directory (GCMD) Location Keywords 20.8 Geographic Information > LiDAR theme CoRIS Discovery Thesaurus EARTH SCIENCE > Land Surface > Topography> Terrain Elevation EARTH SCIENCE > Oceans > Bathymetry/Seafloor Topography > Bathymetry theme CoRIS Theme Thesaurus CoRIS theme NOAA NOS Harvest Catalog COUNTRY/TERRITORY > United States of America > South Carolina OCEAN BASIN > Atlantic Ocean >South Carolina place CoRIS Place Thesaurus 20161002 20170301 temporal DOC/NOAA/NOS/NGS > National Geodetic Survey, National Ocean Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 2017-04-24 publication 8.5 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 22. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian NGS Lidar project InPort otherRestrictions Cite As: National Geodetic Survey, [Date of Access]: 2016-2017 NOAA NGS Topobathy: Coastal South Carolina [Data Date Range], https://www.fisheries.noaa.gov/inport/item/53150. NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose. otherRestrictions Access Constraints: None otherRestrictions Use Constraints: 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. otherRestrictions Distribution Liability: Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the National Geodetic Survey, the Office for Coastal Management, or its partners. unclassified NOAA Data Management Plan (DMP) NOAA/NMFS/EDM 53150 https://www.fisheries.noaa.gov/inportserve/waf/noaa/nos/ngs/dmp/pdf/53150.pdf WWW:LINK-1.0-http--link NOAA Data Management Plan (DMP) NOAA Data Management Plan for this record on InPort. information crossReference vector eng; US elevation OS Independent D1/D2 area -80.041115 -79.98658 32.578384 32.691547 Acquisition Dates: 20161203, 20161209, 20161210, 20161228, 20161229, 20161230, 20170105, 20170228 and 20170301 2016-12-03 2017-03-01 D3 area -80.575337 -80.307752 32.254916 32.542629 Data acquired on 20161002, 20161211, 20161212, 20161213, 20161215, 20161216, 20161221, 20161222, 20161228, 20161229, 20161230, 20161231, 20170102, 20170104 and 20170219 2016-10-02 2017-02-19 D4 area -80.893994 -80.574798 32.117508 32.372078 Data acquired on 20161213, 20170102, 20170104, 20170111, 20170112, 20170113, 20170115 , 20170118, 20170119 and 20170204 2016-12-11 2017-02-04 D5 area -81.092181 -80.787823 31.878403 32.189411 Data acquired on 20170112, 20170113, 20170115, 20170118, 20170119, 20170120, 20170129, 20170130, 20170201, 20170202, and 20170204 2017-01-12 2017-02-04 D6 area -79.933722 -79.609965 32.647866 32.905082 Data acquired on 20161203, 20161210, 20170109, 20170110, 20170210, 20170211, 20170212 , 20170213, 20170214, 20170228 and 20170301 2016-12-03 2017-03-01 D7 area -79.717039 -79.327277 32.886564 33.117057 Data acquired from 20170212-20170214, 20170217-20170221 2017-02-12 2017-02-21 D8 area -79.428248 -79.130611 33.064631 33.228379 Data acquired from 20170218-20170221 and 20170226-20170226 2017-02-18 2017-02-27 The data includes all lidar returns. An automated grounding classification algorithm was used to determine bare earth and submerged topography point classification. The automated grounding was followed with manual editing. false eng false Other NOAA NGS Topobathy Lidar Class Scheme: Coastal South Carolina 2024-02-01 publication LAS/LAZ - LASer Zip Zip Zip NOAA Office for Coastal Management (843) 740-1202 2234 South Hobson Ave Charleston SC 29405-2413 coastal.info@noaa.gov https://coast.noaa.gov WWW:LINK-1.0-http--link NOAA Office for Coastal Management Website NOAA Office for Coastal Management Home Page information distributor https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/8575/index.html WWW:LINK-1.0-http--link Bulk Download Simple download of data files. download https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8575 WWW:LINK-1.0-http--link Customized Download Create custom data files by choosing data area, product type, map projection, file format, datum, etc. download dataset Representativeness Absolute accuracy was assessed using both Non-Vegetated Vertical Accuracy (NVA) and Vegetated Vertical Accuracy (VVA) survey methods. Survey checkpoints were evenly distributed, as much as possible, throughout the project area. NVA compares known ground check point data that were withheld from the calibration and post-processing of the LiDAR point cloud to the triangulated surface generated by the LiDAR points that were calibrated and post-processed. NVA is a measure of the accuracy of LiDAR point data in open areas with level slope (less than 20 degrees) where the LiDAR system has a high probability of measuring the ground surface and is evaluated at the 95% confidence interval (1.96*RMSE.). Ground check points located in land cover categories other than bare earth, urban, or submerged topography were used to compute the Vegetated Vertical Accuracy (VVA). QSI assessed three land cover categories: tall grass, brush and small trees, and forested. Vertical Positional Accuracy D1/D2 dataset tested 0.301 m vegetated vertical accuracy at 95th percentile using 9 mixed landclass points. The non-vegetated accuracy (NVA) tested 0.060 m vertical accuracy at 95% confidence level in open terrain using 23 ground check points based on RMSEz (0.031 m) x 1.9600. The bathymetric vertical accuracy tested 0.231 m vertical accuracy at 95% confidence level in submerged topography using 38 submerged control points, based on RMSEz (0.118 m) x 1.9600. D3 dataset tested 0.049 m vegetated vertical accuracy at 95th percentile using 2 mixed landclass points. The non-vegetated accuracy (NVA) tested 0.068 m vertical accuracy at 95% confidence level in open terrain using 30 ground check points based on RMSEz (0.035 m) x 1.9600. The bathymetric vertical accuracy tested 0.082 m vertical accuracy at 95% confidence level in submerged topography using 31 submerged control points, based on RMSEz (0.042 m) x 1.9600. D4 dataset tested 0.108 m non-vegetated vertical accuracy at 95% confidence level in open terrain using 21 ground check points, based on RMSEz (0.055 m) x 1.9600. D5 dataset tested 0.052 m vegetated vertical accuracy at 95th percentile using 3 mixed landclass points. The non-vegetated accuracy (NVA) tested 0.035 m vertical accuracy at 95% confidence level in open terrain using 30 ground check points based on RMSEz (0.018 m) x 1.9600. The bathymetric vertical accuracy tested 0.073 m vertical accuracy at 95% confidence level in submerged topography using 8 submerged control points, based on RMSEz (0.035 m) x 1.9600. D6 dataset tested 0.294 m vegetated vertical accuracy at 95th percentile using 11 mixed landclass points. The non-vegetated accuracy (NVA) tested 0.043 m vertical accuracy at 95% confidence level in open terrain using 64 ground check points based on RMSEz (0.22 m) x 1.9600. The bathymetric vertical accuracy tested 0.062 m vertical accuracy at 95% confidence level in submerged topography using 8 submerged control points, based on RMSEz (0.031 m) x 1.9600. D7 dataset tested 0.107 m vegetated vertical accuracy at 95th percentile using 8 mixed landclass points. The non-vegetated accuracy (NVA) tested 0.047 m vertical accuracy at 95% confidence level in open terrain using 46 ground check points based on RMSEz (0.24 m) x 1.9600. The bathymetric vertical accuracy tested 0.132 m vertical accuracy at 95% confidence level in submerged topography using 52 submerged control points, based on RMSEz (0.067 m) x 1.9600. Due to marshy terrain, no survey checkpoints, ground check points, or submerged topobathy checkpoints were able to be collected within the D8 delivery area. Therefore, the NVA, VVA, and submerged topography accuracies were unable to be assessed for the D8 Delivery area. Green and NIR LiDAR data were acquired with the Riegl sensor VQ-880G. QSI reviewed flight lines to ensure complete coverage and positional accuracy of the laser points. The collected LiDAR data is processed in the field by QSI to allow QA\QC measures. An initial SBET was created in POSPAC MMS 7.1 and used in RiProcess which applies pre-calibrated angular misalignment corrections of scanner position to extract the raw point cloud into geo-referenced LAS files. These files were inspected for sensor malfunctions and then passed through automated classification routines (TerraScan) to develop a rough topo-bathymetric ground model for an initial assessment of bathymetric coverage. QSI concurrently conducted multiple static Global Navigation Satellite System (GNSS) ground surveys (1 Hz recording frequency). After the airborne survey, the static GPS data were triangulated with nearby Continuously Operating Reference Stations (CORS) using the Online Positioning User Service (OPUS) for precise positioning. Multiple independent sessions over the same monument were processed to confirm antenna height measurements and to refine position accuracy. QSI then resolved kinematic corrections for aircraft position data using kinematic aircraft GPS and static ground GPS data. A final smoothed best estimate trajectory (SBET) was developed. Sensor head position and attitude are calculated throughout the survey. The software Trimble Business Center v.3.90, Blue Marble Geographic Calculator 2016, and PosPac MMS 7.1 SP3 are used for these processes. Next, QSI used RiProcess 1.8.1 to calculate laser point positioning of the Riegl VQ-880G data by associating SBET positions to each laser point return time, scan angle, intensity, etc. A raw laser point cloud is created in Riegl data format. Within RiProcess the RiHydro tool was used to classify water surface and create a water surface model. QSI used the green water surface points and as needed NIR water surface points to create water surface models. These models are used in the RiHydro refraction tool to determine the depth of bathymetric points and are created for single swaths to ensure temporal differences and wave or water surface height variations between flight lines do not impact the refraction of the bathymetric data. All LiDAR data below water surface models were classified as water column to be refracted. The refraction tool corrects for this difference by adjusting depth (distance traveled) and horizontal position (change of angle/direction) of the LiDAR data. Using raster-based QC methods, the output data is verified to ensure the refraction tool functioned properly. QSI used their proprietary LASMonkey refraction tool to correct some refraction in back bay/lake pond areas where RiHydro refraction was found to be inadequate. Once all green data had been refracted it was exported to LAS 1.2 format and combined into 500 m x 500 m tiles. Data was then further calibrated using TerraScan, TerraModeler, and TerraMatch. QSI used custom algorithms in TerraScan to create the initial ground/submerged topography surface. Relative accuracy of the green swaths was compared to overlapping and adjacent swaths and verified through the use Delta-Z (DZ) orthos created using QSI's DZ Ortho creator. Absolute vertical accuracy of the calibrated data was assessed using ground RTK survey data and complete coverage was again verified. QSI then performed manual editing to review all classification and improve the final topobathy surface. QSI's LasMonkey was used to update LAS header information, including all projection and coordinate reference system information. The final LiDAR data are in LAS format 1.2 and point data record format 3. The NOAA Office for Coastal Management (OCM) received files in las format. The files contained lidar elevation and intensity measurements. The data were in UTM Zone 17 coordinates and ellipsoid elevations in meters. OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. Converted from UTM Zone 17 to geographic coordinates 2. Sorted by gps time 3. Compressed the data using laszip 4. Converted laz files to version 1.4 5. Reclassified overlap classes 19 to 1, 20 to 2, 21 to 25 and 22 to 27 with overlap flags The data have the following classification: unclassified (1), ground (2), noise (7), water column (25), bathymetric bottom or submerged topography (26), water surface (27), and temporal bathy bottom (31) Office for Coastal Management processor Lidar