gov.noaa.nmfs.inport:73569 eng UTF8 dataset Elevation OCM Partners 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 2026-04-30T00:00:00 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) EPSG::6360 EPSG::6570 2020 SC DNR Lidar DEM: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC 2020 creation 2023-08-16 publication NOAA/NMFS/EDM 73569 https://www.fisheries.noaa.gov/inport/item/73569 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/dataviewer/#/lidar/search/where:ID=10177/details/10177 WWW:LINK-1.0-http--link Custom Point Download Link to custom download, from the Data Access Viewer (DAV), the lidar point data from which these raster Digital Elevation Model (DEM) data were created. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/10177/breaklines/index.html WWW:LINK-1.0-http--link Breaklines/Building Polygons Link to the breaklines and building polygons footprint. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/10177/supplemental/5_Counties_Acquisition_Rpt.pdf WWW:LINK-1.0-http--link Lidar Acquisition Report Link to the lidar acquisition report. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/10177/supplemental/5_Counties_Processing_Rpt.pdf WWW:LINK-1.0-http--link Lidar Processing Report Link to the lidar data processing report. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/10177/supplemental/5_Counties_Report_of_Survey.pdf WWW:LINK-1.0-http--link Lidar Survey Report Link to the lidar survey report. download https://coast.noaa.gov/dataviewer/ WWW:LINK-1.0-http--link NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) The Data Access Viewer (DAV) allows a user to search for and download elevation, imagery, and land cover data for the coastal U.S. and its territories. The data, hosted by the NOAA Office for Coastal Management, can be customized and requested for free download through a checkout interface. An email provides a link to the customized data, while the original data set is available through a link within the viewer. download Original Dataset Description: Aerial lidar data was collected for a 5-county project area which encompassed the South Carolina Counties of Cherokee, Union, Chester, Lancaster, and Fairfield. Lidar data for the project was collected by Quantum Spatial as part of the ESP team, between January 16, 2020 and February 15, 2020 using 2 Leica ALS80 sensors; serial numbers 3061 and 3546. Data was collected at a 0.7 meter aggregate nominal post spacing (ANPS). ESP Associates (ESP) used commercial off the shelf software as well as proprietary software and methods to classify the lidar point cloud to the following classifications: 1-Unclassified, 2-Ground, 3-Low Vegetation 0.5-3ft in height, 4-Medium Vegetation 3-10ft in height, 5-High Vegetation 10-220ft in height, 6-Buildings at 500 sq ft of area or more, 7-Low Noise, 8-Model Keypoints, 9-Water, 11-Witheld Points (exceed scan angle limit), 13-Roads contained in SC road centerlines database, 17-Bridge Decks, 18-High Noise, 20-Ignored Ground due to breakline proximity, 21-Culverts. ESP produced 3D breaklines to supplement the lidar ground and road classifications to produce hydro flattened DEMs for the project area. All data were tiled to the SC DNR tile scheme consisting of 5,000 feet by 5,000 ft tiles and named in accordance with the "ORTHOGRID" attribute of the scheme. The NOAA Office for Coastal Management (OCM) received a copy of this data from the South Carolina Department of Natural Resources (SC DNR). The data were processed to the NOAA Digital Coast Data Access Viewer (DAV) to make the data available for bulk and custom downloads. In addition to these bare earth Digital Elevation Model (DEM) data, breaklines and building polygon data, and the lidar point data that these DEM data were created from, are also available. These data are available for download at the links provided in the URL section of this metadata record. The purpose of this project was to perform lidar collection and processing and produce derivative products such as intensity images, hydro-flattened DEMs, hydro-breakline layers, and a classified LiDAR point cloud. The data will support flood modeling, contour generation and other uses, as needed, by the South Carolina Department of Natural Resources (SCDNR). South Carolina Department of Natural Resources (SC DNR) 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 EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM) theme Global Change Master Directory (GCMD) Science Keywords 23.3 CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > SOUTH CAROLINA VERTICAL LOCATION > LAND SURFACE place Global Change Master Directory (GCMD) Location Keywords 23.3 LIDAR > Light Detection and Ranging instrument Global Change Master Directory (GCMD) Instrument Keywords 23.3 Airplane > Airplane platform Global Change Master Directory (GCMD) Platform Keywords 23.3 DEMs - partner (no harvest) project InPort otherRestrictions Cite As: OCM Partners, [Date of Access]: 2020 SC DNR Lidar DEM: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC [Data Date Range], https://www.fisheries.noaa.gov/inport/item/73569. 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: This data was produced for the SC DNR according to specific project requirements. This information is provided "as is". Further documentation of this data can be obtained by contacting: SC DNR, 1000 Assembly St Suite 123, Columbia, SC 29201. 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 Office for Coastal Management or its partners. unclassified 2020 SC DNR Lidar: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC NOAA/NMFS/EDM 73545 crossReference grid eng; US elevation -81.87 -80.39 34.16 35.19 Dates of collection for the 5 County project in South Carolina. | Currentness: Ground Condition 2020-01-16 2020-02-15 Complete descriptions of this dataset and of the project design, aerial data collection, and processing steps are included in the Acquisition, Report of Survey, and Post-Processing reports for this project. Zip GeoTIFF Uncompressed 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://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10178/details/10178 WWW:LINK-1.0-http--link Customized Download Create custom data files by choosing data area, map projection, file format, etc. A new metadata will be produced to reflect your request using this record as a base. download https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/SC_5County_DEM_2020_10178/index.html WWW:LINK-1.0-http--link Bulk Download Bulk download of data files in GeoTiff format, South Carolina State Plane NAD83(2011), international feet coordinates and NAVD88 (Geoid12B) elevations in feet. download dataset Horizontal Positional Accuracy The DEMs are generated from the source lidar and 3D breaklines mapped from the lidar surface. ESP does not perform horizontal accuracy checks on the DEMs or breaklines. Both system and project calibrations were conducted by the acquisition vendor which included the use of ground suvey control. Cross flights were utilized to assist in swath to swath matching and to improve relative accuracy.This data set was produced to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data, Edition 1, Version 1.0.0 (2014) for a 0.95 ft (29 cm) RMSEx/RMSEy Horizontal Accuracy Class which equates to Positional Horizontal Accuracy = +/- 1.86 ft (57 cm) at a 95% confidence level. A horizontal accuracy assessment was not conducted for this project due to the lack of photo-identifiable checkpoints. Vertical Positional Accuracy DEMs were derived from the project source lidar and 3D breaklines products mapped from the lidar surface. The process generates DEMs by assigning the average of the lidar bare ground and road points located within each pixel of the GeoTIFF DEM product. Vertical testing of the resultant DEM is achieved by comparing the project lidar checkpoints against a TIN surface of the DEM product. As TINs are an interpolated surface, some minor elevations differences can be expected that do not exceed the minimum accuracy required. The project specifications required that Non-Vegetated Vertical Accuracy (NVA) and Vegetated Vertical Accuracy (VVA) be computed for calibrated and classified lidar point cloud files. The required vertical accuracy (ACCz) is: 19.6 cm at a 95% confidence level for NVA, and 30 cm at the 95th percentile for VVA, derived according to ASPRS Positional Accuracy Standards for Digital Geospatial Data, Edition 1, Version 1.0.0 for Vertical Accuracy Class 10-cm (RMSEz = 10 cm). The NVA was tested with 92 checkpoints located in bare earth and urban (non-vegetated) areas across the 5-county project block. These check points were not used in the calibration or post processing of the lidar point cloud data. A total of 68 checkpoints were used for the VVA calculation across the 5-county area. The checkpoints were distributed throughout the project area and were surveyed using GPS techniques. See Report of Survey for additional survey methodologies. Elevations from the classified lidar TIN surface were measured for the x,y location of each check point. Elevations interpolated from the lidar surface were then compared to the elevation values of the surveyed control points. ACCz has been tested to meet 19.6 cm or better Non-Vegetated Vertical Accuracy at 95% confidence level using RMSE(z) x 1.9600 as defined by the National Standards for Spatial Data Accuracy (NSSDA); assessed and reported using National Digital Elevation Program (NDEP)/ASRPS Guidelines. This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.33 ft (10 cm) RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz =0.09 ft (2.7 cm), equating to +/- 0.18 ft (5.5 cm) at 95% confidence level. This DEM dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 0.33 ft (10 cm) RMSEz Vertical Accuracy Class or ACCz of 0.98 ft (30 cm). Actual VVA accuracy was found to be +/- 0.42 ft (12.8 cm) at the 95th percentile. The 5% outliers consisted of 3 checkpoints that are larger than the 95th percentile. These checkpoints have DZ values ranging between 0.45 ft (13.7 cm) to 0.68 ft (20.7 cm). Completeness Measure These LAS data files include 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 point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications. Completeness Report 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 passes Non-Vegetated Vertical Accuracy specifications. Conceptual Consistency Data covers the project boundary. Data were collected by the Quantum Spatial, Inc., for the South Carolina Department of Natural Resources (SC DNR). The data were provided to the NOAA Office for Coastal Management (OCM) and processed to make it available for custom download from the NOAA Digital Coast Data Access Viewer (DAV) and for bulk download from AWS S3. Data was acquired by Quantum Spatial for the 5-county lidar project. The project area encompassed approximately 3,016 square miles. Data were collected using linear mode Leica ALS-80 sensors, serial numbers 3061 and 3546. The data were delivered in the State Plane coordinate system, international feet, South Carolina, horizontal datum NAD83, vertical datum NAVD88, U.S. Survey Feet, Geoid 12B. Deliverables for the project included a raw (unclassified) calibrated lidar point cloud and an acquisition report The lidar calibration process was conducive to postprocessing an accurate data set. Significant attention was given to GPS baseline distances and GPS satellite constellation geometry and outages during the trajectory processing. Verification that proper ABGPS surveying techniques were followed including: pre and post mission static initializations and review of In-air Inertial Measurement Unit (IMU) alignments, if performed, both before and after on-site collection activities to ensure proper self-calibration of the IMU accelerometers and gyros were achieved. Cross flights were planned throughout the project area across all flightlines and over roadways where possible. The cross-flights provided a common control surface used to remove any vertical discrepancies in the lidar data between flightlines and aided in the bundle adjustment process with review of the roll, pitch, heading (omega, phi, kappa). The cross-flight design was critical to ensure flight line ties across the sub-blocks and the entire project area. The areas of overlap between flightlines were used to calibrate (aka boresight) the lidar point cloud to achieve proper flight line to flight line alignment in all 6 degrees of freedom. This included adjustment of IMU and scanner-related variables such as roll, x, y, z, pitch, heading, and timing interval (calibration range bias by return) Each lidar mission flown was independently reviewed, bundle adjusted (boresighted), and/if necessary, improved by a hands-on boresight refinement in the office. Once the relative accuracy adjustment was complete, the data was adjusted to the high order GPS calibration control to achieve a zero-mean bias for fundamental accuracy computation, verification, and reporting. Internal accuracy testing procedures and methods were compliant with SCDNR and USGS specifications. Field survey was conducted for Cherokee, Lancaster, Fairfield, Chester, and Union Counties to establish ground survey control in support of lidar data calibration processes and to establish independent lidar checkpoints used to internally verify calibration results. A total of 70 calibration survey points were established for the purpose of data calibration and a total of 161 checkpoints comprised of bare earth, forested, urban, low and medium height vegetation types were used to verify calibration results independent of the calibration process. Each location was double-occupied to validate accuracy. The control was used to facilitate calibration of lidar flight lines/blocks, perform mean adjustment, and test final fundamental accuracy of the data. Control was established under the following conditions: 1. Located only in open terrain where there is a high probability that the sensor will have detected the ground surface without influence from surrounding vegetation. 2. On flat or uniformly sloping terrain at least five (5) meters away from any breakline where there is a change in slope. 3. Checkpoint accuracy satisfied a Local Network accuracy of 5 cm at the 95% confidence level. 4. Field photos will be taken of each point, in multiple directions (generally cardinal directions). ESP prepared and delivered a Report of Survey which included a "as collected" control locations map, survey methodology, QA/QC methodology, control coordinates, field pictures, and any field comments. As part of this deliverable, Excel .CSV files were delivered with the control coordinates and elevation values for calibration and checkpoint locations. The report was signed and sealed by the surveyor in charge. National Geodetic Survey data sheets were included for any Network Control Points used to control the topographic data acquisition and ground surveys. The ESP team utilized multiple software and data management methods throughout the lidar processing workflow. The workflow post-acquisition began at team member Quantum's production facility with the lidar calibration process. The calibration process ensured that all lidar acquisition missions were carried out in a manner conducive to postprocessing an accurate data set. Significant attention was given to GPS baseline distances and GPS satellite constellation geometry and outages during the trajectory processing. Verification that proper Airborne GPS (AGPS) surveying techniques were followed including: pre and post mission static initializations and review of In-air IMU alignments, if performed, both before and after on-site collection to ensure proper self-calibration of IMU accelerometers and gyros were achieved. Relative accuracy was achieved by establishing cross flights throughout each project block area across all flight lines and over roadways where possible. The cross-flight provides a common control surface used to remove any vertical discrepancies in the lidar data between flight lines and aids in bundle adjustment process with review of roll, pitch, heading (omega, phi, kappa). The cross-flight is critical to ensure flight line ties across the sub-blocks and the entire project area. Areas of overlap between flight lines are used to calibrate the lidar point cloud to achieve proper flight line to flight line alignment in all 6 degrees of freedom. This includes adjustment of IMU and scanner-related variables such as roll, x, y, z, pitch, heading, and timing interval (calibration range bias by return). Each LiDAR mission flown was independently reviewed, bundle adjusted, and/if necessary, improved by a hands-on boresight refinement in the office. Once the relative accuracy adjustment was complete, data was adjusted to the high order GPS calibration control to achieve a zero-mean bias for fundamental accuracy computation, verification, and reporting. Internal accuracy testing procedures, methods were compliant with ASPRS and USGS specifications. ESP utilized a combination of Terrasolid products and proprietary software such as ESP Analyst and ESP Utilities to conduct post-calibration, lidar point cloud processing tasks. The lidar classification process encompassed a series of automated and manual steps to classify the calibrated point cloud dataset. Each project represents unique characteristics in terms of cultural features (urbanized vs. rural areas), terrain type, and vegetation coverage. These characteristics were thoroughly evaluated at the onset of the project to ensure that the appropriate automated filters were applied and that subsequent manual filtering yielded correctly classified data. Automated filtering macros, which may contain one or more filtering algorithms, were developed and executed to derive LAS files with points separated into the different classification groups as defined in the ASPRS classification table. The macros were tested in several portions of project area to verify the appropriateness of the filters. At times, a combination of several filter macros optimized the filtering based on the unique characteristics of the project. Automatic filtering generally yields a ground surface that is 85-90% valid, so additional editing (hand filtering) was required to produce a more robust ground surface. The data were classified as follows: Class 1 = Unclassified (non-ground) Class 2 = Ground (bare earth) Class 3 = Low Vegetation Class 4 = Medium Vegetation Class 5 = High Vegetation Class 6 = Buildings Class 7= Low Noise Class 8 = Model Keypoints Class 9 = Water Class 11 = Withheld Points Class 13 = Roads Class 17 = Bridge Decks Class 18 = High Noise Class 20 = Ignored Ground (breakline proximity buffer) Class 21 = Culverts. Header records for the LAS files were reviewed to ensure that the expected classifications were present along with project information, x/y/z limits and scale, and that time, intensity and angle were also populated. ESP technicians reviewed the auto-classified lidar point clouds to manually re-classify (or hand-filter) "noise" and other features that may have remained in the ground classification as well as to correct any gross mis-classifications by the software. Cross-sections and TIN surfacing tools were used to assist technicians in the reclassification of non-ground data artifacts. Certain features such as berms, hilltops, cliffs and other features that may have been aggressively auto-filtered had points re-classified into the ground classification. Conversely, above-ground artifacts such as decks, bushes, and other subtle features that may have remained in the ground classification after automated filtering were corrected via a manual editing process. Hydro-flattening breaklines were collected and compiled using proprietary techniques within ESP Analyst software for drainage features that drain approximately 0.5 sq. mi. or more. A minimum of four feature attributes we included in the linework 1. Single Line Stream (Polyline Z), 2. Stream Centerline/Connector (Polyline Z), 3. Stream Banks (Polygon Z), 4. Waterbodies (Polygon Z) Centerlines were captured for all streams that were > 20 feet in width as well as for lakes and ponds. Banks and centerlines/connectors were captured for streams >20 feet in width and closed water bodies and islands that equaled or exceeded 1 acre in surface area were delineated. Line intersections were noded and linework for adjoining counties in the project were edge-matched in the z,y and z. In addition, lines were collected under bridge locations to ensure that the TIN would be enforced around bridge abutments. To ensure that only closed water bodies that met the SCDNR criteria were drawn, ESP utilized a minimum map unit (MMU) tool within ESP Analyst to assist the technicians in determining whether or not island, ponds and other closed water bodies needed to be collected based on the project minimum map units of >1 acre for permanent islands and >1 acre for closed water bodies. ESRI geodatabase files were created by county, containing all linework. ESP generated hydro-flattened DEMs using the classified ground and road lidar points in conjunction with the collected hydro-flattening and under-bridge breaklines. The DEMs were generated using ESP's proprietary ESP Utilities software and then inspected for completeness and hydro-enforcement. DEMs were generated at a 5-ft resolution in ESRI Grid format. The NOAA Office for Coastal Management (OCM) received the files in GeoTiff format from the South Carolina Department of Natural Resources (SC DNR). The bare earth raster file was at a 5 foot grid spacing. The data were in South Carolina State Plane NAD83(2011), international feet coordinates and in NAVD88 (Geoid12B) elevations in feet. OCM copied the raster files to https for Digital Coast storage and provisioning purposes. 2024-09-23T00:00:00 Office for Coastal Management processor Data provided by SC DNR South Carolina Department of Natural Resources (SC DNR) originator