gov.noaa.nmfs.inport:73545 eng UTF8 dataset Elevation Office for Coastal Management 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 2026-08-21T12:55:27 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) EPSG::6319 2020 SC DNR Lidar: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC sc2020_5county_m10177_metadata 2020 creation 2021-05 publication NOAA/NMFS/EDM 73545 https://www.fisheries.noaa.gov/inport/item/73545 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/entwine/geoid18/10177/ept.json WWW:LINK-1.0-http--link Entwine Point Tile (EPT) Entwine Point Tile (EPT) is a simple and flexible octree-based storage format for point cloud data. The data is organized in such a way that the data can be reasonably streamed over the internet, pulling only the points you need. EPT files can be queried to return a subset of the points that give you a representation of the area. As you zoom further in, you are requesting higher and higher densities. A dataset in EPT will contain a lot of files, however, the ept.json file describes all the rest. The EPT file can be used in Potree and QGIS to view the point cloud. download https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=10178/details/10178 WWW:LINK-1.0-http--link Custom DEM Download Link to custom download, from the Data Access Viewer (DAV), the raster Digital Elevation Model (DEM) data that were created from this lidar data set. 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/lidar/viewer/v/noaapotree.html?r=https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/entwine/geoid18/10177/ept.json WWW:LINK-1.0-http--link Potree 3D View Link to view the point cloud (using the Entwine Point Tile (EPT) format) in the 3D Potree viewer. 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 as part of 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 the lidar point data, the bare earth Digital Elevation Models (DEMs) at a 5 ft grid spacing, created from the lidar point data, and the breakline and building polygon data are also available from the NOAA Digital Coast Data Access Viewer (DAV). 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). ESP Associates, South Carolina Department of Natural Resources (SCDNR) 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 asNeeded EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION 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 DOC/NOAA/NOS/OCM > Office of Coastal Management, 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). 2026. GCMD Keywords, Version 24. 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 Lidar project InPort otherRestrictions Cite As: Office for Coastal Management, [Date of Access]: 2020 SC DNR Lidar: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC [Data Date Range], https://www.fisheries.noaa.gov/inport/item/73545. 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 Office for Coastal Management or its partners. unclassified 2020 SC DNR Lidar DEM: 5 County (Cherokee, Chester, Fairfield, Lancaster, Union), SC NOAA/NMFS/EDM 73569 crossReference vector eng; US elevation MicroStation Connect Version 10.11; TerraScan Version 21.11; ESP Analyst; ESP Utilities; Microsoft Windows 10; ESRI ArcGIS 10.6.1.9270 -81.88 -80.39 34.16 35.194 | 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 The following are the USGS lidar fields in JSON: { "ldrinfo" : { "ldrspec" : "USGS-NGP Lidar Base Specification V2.1", "ldrsens" : "RIEGL VQ-1560i Sensors 3061 & 3546", "ldrmaxnr" : "Unlimited", "ldrnps" : "0.70", "ldrdens" : "2.00", "ldranps" : "0.70", "ldradens" : "2.00", "ldrfltht" : "2043", "ldrfltsp" : "150", "ldrscana" : "58.52", "ldrscanr" : "2000", "ldrpulsr" : "800", "ldrpulsd" : "3", "ldrpulsw" : "0.9", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.18", "ldrswatw" : "2289", "ldrswato" : "30", "ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B", "ldrcrs" : "NAD 1983 (2011) State Plane South Carolina International Feet" }, "ldraccur" : { "ldrchacc" : "0.196", "rawnva" : "0.098", "rawnvan" : "43", "clsnva" : "0.098", "clsnvan" : "43", "clsvva" : "0.180", "clsvvan" : "46" }, "lasinfo" : { "lasver" : "1.4", "lasprf" : "6", "laswheld" : "Withheld points were identified in these files using Class 11.", "lasolap" : "Swath overage points were identified in these files using the standard LAS overlap bit", "lasintr" : "16", "lasclass" : { "clascode" : "1", "clasitem" : "Processed, but unclassified" }, "lasclass" : { "clascode" : "2", "clasitem" : "Bare earth, ground" }, "lasclass" : { "clascode" : "3", "clasitem" : "Low Vegetation" }, "lasclass" : { "clascode" : "4", "clasitem" : "Medium Vegeation" }, "lasclass" : { "clascode" : "5", "clasitem" : "High Vegetation" }, "lasclass" : { "clascode" : "6", "clasitem" : "Buildings" }, "lasclass" : { "clascode" : "7", "clasitem" : "Low Noise" }, "lasclass" : { "clascode" : "8", "clasitem" : "Model Keypoints" }, "lasclass" : { "clascode" : "9", "clasitem" : "Water" }, "lasclass" : { "clascode" : "11", "clasitem" : "Withheld Points" }, "lasclass" : { "clascode" : "13", "clasitem" : "Roads" }, "lasclass" : { "clascode" : "17", "clasitem" : "Bridge Decks" }, "lasclass" : { "clascode" : "18", "clasitem" : "High Noise" }, "lasclass" : { "clascode" : "20", "clasitem" : "Ignored Ground" }, "lasclass" : { "clascode" : "21", "clasitem" : "Culverts" } }} Zip LAS/LAZ - LASer LAZ 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=10177/details/10177 WWW:LINK-1.0-http--link Customized Download Create custom data files by choosing data area, product type, map projection, file format, datum, etc. A new metadata will be produced to reflect your request using this record as a base. Change to an orthometric vertical datum is one of the many options. download https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid18/10177/index.html WWW:LINK-1.0-http--link Bulk Download Bulk download of data files in LAZ format, geographic coordinates, orthometric heights. Note that the vertical datum (hence elevations) of the files here are different than described in this document. They will be in an orthometric datum. download dataset Horizontal Positional Accuracy Horizontal accuracy in lidar can only be checked if a checkpoint is located at the ends or corners of linear features on the ground, such as the end of parking lot paint stripes. The x,y coordinates of surveyed checkpoints are compared against the corresponding lidar elevation in the intensity images. The elevation deltas are used to compute the horizontal accuracy. This process requires lidar that is dense enough to render the linear features as viewable. Because of this, horizontal accuracy cannot be measured for all lidar projects. Both system and project calibrations were conducted by the acquisition vendor which included the use of ground survey 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 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 lidar 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 =0.18 ft (6.1 cm), equating to +/- 0.40 ft (12.2 cm) at 95% confidence level. 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). 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 Report 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. Conceptual Consistency Data covers the project boundary. The NOAA Office for Coastal Management (OCM) received the elevation data for the 5 County (Cherokee, Chester, Fairfield, Lancaster, Union) lidar project from the South Carolina Department of Natural Resources (SCDNR). NOAA OCM processed the data to the NOAA Digital Coast Data Access Viewer (DAV) to make the data publicly available for bulk and custom downloads. Data for was acquired by Quantum Spatial for the 5-county lidar project. The project area encompassed approximately 3,016 square miles, of which: 1. Cherokee County covered 450 square miles 2. Chester County covered 608 square miles 3. Fairfield County covered 762 square miles 4. Lancaster County covered 645 square miles 5. Union County covered 556 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. 2020-04-01T00:00:00 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 2020-02-01T00:00:00 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 the 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 the bundle adjustment process with review of the 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. The areas of overlap between flight lines are 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 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 (bore sighted), 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, 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 the 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 projec 2020-06-01T00:00:00 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. 2020-11-01T00:00:00 The NOAA Office for Coastal Management received the 2020 SCDNR 5 County Lidar dataset from the SCDNR. The data were in SC State Plane NAD83(2011), int feet coordinates and the elevations were in NAVD88(Geoid12B), US survey feet. The data were classified as: 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. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 17, 18, 21. OCM performed the following processing on the data for Digital Coast storage and provisioning purposes: 1. An internal OCM script was run to check the number of points by classification and by flight ID and the gps and intensity ranges. 2. Internal OCM scripts were run on the laz files to: a. Convert the files from SC State Plane NAD83(2011), International feet coordinates to geographic coordinates b. Convert the files from NAVD88 (Geoid12B) elevations to ellipsoid (NAD83 2011) elevations c. Convert the files from elevations in feet to meters d. Convert the points classified as 20 - Ignored Ground to 10 - Ignored Ground to conform to an OCM internal lidar domain profile e. Assign the geokeys, to sort the data by gps time and zip the data to database and to AWS S3 2024-10-16T00:00:00 Office for Coastal Management processor Lidar Data for the SC 2020 5 County Lidar Project SCDNR originator