gov.noaa.nmfs.inport:67264 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::3857 EPSG::5703 2018 - 2019 USGS Lidar: GA Statewide ga2018_statewide_m9508_metadata 2018 creation publication NOAA/NMFS/EDM 67264 https://www.fisheries.noaa.gov/inport/item/67264 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_10_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for 10 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B7_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B7 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_9_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for 9 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B6_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B6 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B8_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B8 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_11_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for 11 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B4_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B4 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_12_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for 12 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B1_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B1 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B2_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B2 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B3_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B3 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://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B5_2018/ept.json WWW:LINK-1.0-http--link Entwine Point Tiles (EPT) for B5 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://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/GA_Statewide_2018_B18_DRRA/GA_Statewide_2018_B18_DRRA_WP_Report.pdf WWW:LINK-1.0-http--link USGS Work Package Report Link to the USGS work package report that provides project information, vertical accuracy results, classifications used, sensors used, and work unit information. download https://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/metadata/GA_Statewide_2018_B18_DRRA/ WWW:LINK-1.0-http--link USGS Provided Data Link to the additional information available for this data set from the USGS. This information includes reports, tile index shapefiles, and hydro breaklines. download https://usgs.entwine.io/data/view.html?r=[%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B1_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B2_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B3_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B4_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B5_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B6_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B7_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_B8_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_9_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_10_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_11_2018/ept.json%22,%22https://s3-us-west-2.amazonaws.com/usgs-lidar-public/GA_Statewide_12_2018/ept.json%22] 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 USGS task order 140G0218F0420 required Winter, 2018/Spring, 2019 LiDAR surveys to be collected over 32,562 square miles covering part or all of 82 counties in Georgia and 3 partial counties in South Carolina in support of the State of Georgia and the USGS 3DEP program. Aerial LiDAR data for this task order was planned, acquired, processed and produced at an aggregate nominal pulse spacing (ANPS) of 0.71 meters and in compliance with USGS National Geospatial Program LiDAR Base Specification version 1.3. Class 3 is Low Vegetation (0.5 - 5 ft) Class 4 is Medium Vegetation (5 - 20 ft) Class 5 is High Vegetation (> 20 ft) This metadata supports the data entry in the NOAA Digital Coast Data Access Viewer (DAV). For this data set, the DAV is leveraging the Entwine Point Tiles (EPT) hosted by USGS on Amazon Web Services. There are issues for this dataset leveraging the EPT format. See the completeness report section for more information. Aerial lidar was collected to support the mapping efforts of individual counties in the State of Georgia and the USGS 3DEP program. The Atlantic Group, LLC, USGS 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 unknown EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION theme Global Change Master Directory (GCMD) Science Keywords 23.3 CONTINENT CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GEORGIA 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 Lidar - partner (no harvest) project InPort 2023-01-24T00:00:00 There is misclassification of vegetation as ground. These misclassified points are marked as overlap. Including the overlap flagged points when deriving ground products can have poor and unusable results. Waters, Kirk user otherRestrictions Cite As: OCM Partners, [Date of Access]: 2018 - 2019 USGS Lidar: GA Statewide [Data Date Range], https://www.fisheries.noaa.gov/inport/item/67264. 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 2018 - 2019 USGS Lidar DEM: GA Statewide NOAA/NMFS/EDM 75831 crossReference vector eng; US elevation -85.619201 -80.819437 30.348528 35.011998 Dates of collection for B4 (Block 4A). | Currentness: Ground Condition 2019-03-29 2019-04-16 Dates of collection for B1. | Currentness: Ground Condition 2019-01-27 2019-04-22 Dates of collection for B2. | Currentness: Ground Condition 2019-01-28 2019-04-24 Dates of collection for B3 (Block 3). | Currentness: Ground Condition 2019-03-23 2019-04-24 Date of collection for B5 (Block 11). | Currentness: Ground Condition 2019-01-22 2019-04-23 Dates of collection for B6 (Block 7). | Currentness: Ground Condition 2018-11-29 2019-04-22 Dates of collection for B7 (Block 4B). | Currentness: Ground Condition 2018-11-27 2019-04-03 Dates of collection for B8 (Block 5). | Currentness: Ground Condition 2018-11-28 2019-01-28 Dates of collection for B9 (Block 6). | Currentness: Ground Condition 2018-12-05 2019-03-18 Dates of collection for B10 (Block 9). | Currentness: Ground Condition 2019-02-08 2019-04-23 Dates of collection for B11(Block 8). | Currentness: Ground Condition 2019-01-26 2019-04-23 Dates of collection for B12 (Block 10). | Currentness: Ground Condition 2019-02-08 2019-04-23 Prime Contractor: The Atlantic Group, LLC. Lidar data were acquired and calibrated by The Atlantic Group. All follow-on processing was completed by the prime contractor. The following are the USGS lidar fields in JSON: { "ldrinfo" : { "ldrspec" : "Base Specifications 1.3", "ldrsens" : "Leica ALS70-HP", "ldrmaxnr" : "5", "ldrnps" : "0.5097", "ldrdens" : "3.8487", "ldranps" : "0.5052", "ldradens" : "3.9173", "ldrfltht" : "2000", "ldrfltsp" : "130", "ldrscana" : "45", "ldrscanr" : "35.1", "ldrpulsr" : "265", "ldrpulsd" : "4", "ldrpulsw" : "0.30", "ldrwavel" : "1064", "ldrmpia" : "1", "ldrbmdiv" : "0.15", "ldrswatw" : "1663", "ldrswato" : "20", "ldrgeoid" : "National Geodetic Survey (NGS) Geoid12B" }, "ldraccur" : { "ldrchacc" : "0", "rawnva" : "0", "rawnvan" : "0", "clsnva" : "0", "clsnvan" : "0", "clsvva" : "0", "clsvvan" : "0" }, "lasinfo" : { "lasver" : "1.4", "lasprf" : "6", "laswheld" : "Withheld (ignore) points were identified in these files using the standard LAS Withheld bit.", "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 (0.5 – 5 feet)" }, "lasclass" : { "clascode" : "4", "clasitem" : "Medium Vegetation (5 – 20 feet)" }, "lasclass" : { "clascode" : "5", "clasitem" : "High Vegetation (>20 feet)" }, "lasclass" : { "clascode" : "6", "clasitem" : "Building footprints" }, "lasclass" : { "clascode" : "7", "clasitem" : "Low Noise" }, "lasclass" : { "clascode" : "9", "clasitem" : "Water" }, "lasclass" : { "clascode" : "17", "clasitem" : "Bridge Decks" }, "lasclass" : { "clascode" : "18", "clasitem" : "High Noise" }, "lasclass" : { "clascode" : "20", "clasitem" : "Ignored ground (breakline proximity)" }, "lasclass" : { "clascode" : "21", "clasitem" : "Snow (where reliable identifiable)" }, "lasclass" : { "clascode" : "22", "clasitem" : "Temporal Exclusion (typically non-favored data in intertidal zones)" } }} Zip Zip LAS/LAZ - LASer 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 U.S. Geological Survey 12201 Sunrise Valley Drive Reston VA 20191 USA https://usgs.gov WWW:LINK-1.0-http--link USGS Home Home page for USGS information distributor https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9508/details/9508 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://rockyweb.usgs.gov/vdelivery/Datasets/Staged/Elevation/LPC/Projects/GA_Statewide_2018_B18_DRRA/ WWW:LINK-1.0-http--link Bulk Download Bulk download of data files in LAZ format, based on a horizontal datum/projection of Albers Conic, NAD83(2011), meters (EPSG: 6350) and a vertical datum of NAVD88 (GEOID12B) and units in meters (EPSG: 5703). This url links to the USGS copy of the files, from which the Entwine Point Tile files originated. These have not been reviewed by OCM and the link is provided here for convenience. download dataset Vertical Positional Accuracy This data set was produced to meet ASPRS Positional Accuracy Standard for Digital Geospatial Data (2014) for a 10-cm RMSEz Vertical Accuracy Class. The terms NVA (Non-vegetated Vertical Accuracy) and VVA (Vegetated Vertical Accuracy) are from the ASPRS Positional Accuracy Standards for Digital Geospatial Data v1.3 (2014). The term NVA refers to assessments in clear, open areas (which typically produce only single lidar returns); the term VVA refers to assessments in vegetated areas (typically characterized by multiple return lidar). USGS Determined Vertical Accuracy Non-Vegetated Vertical Accuracy (NVA) = 7.2 cm RMSE Vegetated Vertical Accuracy (VVA) = 18.69 cm at the 95th Percentile Completeness Report Area of interest covers project area. 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 NVA 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. There are issues in this dataset related to ground classification and overlap flags. Some areas have vegetation, including trees, classified as ground, but also marked as overlap. If the overlap data is included, derived products may not be representative of the ground. Data stored in EPT format does not include the overlap flag and there is no way to filter out the misclassifications. As of January 2023, the NOAA Data Access Viewer is leveraging EPT format data and has this problem. Conceptual Consistency All lidar data and lidar derived data covers the entire area of interest. 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. Low confidence polygons have been delivered with this dataset. These polygons represent areas where heavy vegetation or inundated areas greatly diminish penetration of the lidar pulse, resulting in a bare earth surface that is potentially less accurate due to the lack of lidar returns from the ground beneath the vegetation or surface water. Low confidence polygons delineate areas where conformance to VVA standards may not be met. The low confidence polygons created for this dataset were delineated according to the criteria and assumptions outlined in the ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014). Low confidence areas are identified using a ground density raster. All areas with a Nominal Ground Point Density less than the threshold of 0.5 pts/m2 are identified as low confidence cells in the ground density raster. The low confidence cells are exported to polygons and aggregated into larger shapes. Areas of expected low density in the ground, such as water or where buildings/structures have been removed, are deleted from the aggregated low confidence polygons. The size of all polygons is then calculated and polygons below the minimum size threshold of 5 acres are removed from the final low confidence polygon dataset. The GA Statewide lidar was ingested into the Data Access Viewer for custom product generation by leveraging USGS hosted Entwine Point Tiles. Aircraft and Sensor Information and Flight Plan Execution: Atlantic operated a Cessna (N732JE) outfitted with a Leica ALS70-HP LiDAR system during the collection of the project area. Atlantic acquired 212 passes of the AOI as a series of perpendicular and/or adjacent flight-lines executed in 25 flight missions conducted between February 8, 2019 and April 23, 2019. Onboard differential Global Navigation Satellite System (GNSS) unit(s) recorded sample aircraft positions at 2 hertz (Hz) or more frequency. LiDAR data was only acquired when a minimum of six (6) satellites were in view. Twenty-two (22) Continuously Operating Reference Stations (CORS) were used to control the LiDAR acquisition for the defined project area. 2019-04-23T00:00:00 Ground Control Survey: A total of 124 ground survey points were collected in support of this project, including 31 LiDAR Control Points (LCP), 46 Non-vegetated Vertical Accuracy (NVA) and 47 Vegetated Vertical Accuracy (VVA). Point cloud data accuracy was tested against a Triangulated Irregular Network (TIN) constructed from LiDAR points in clear and open areas. A clear and open area can be characterized with respect to topographic and ground cover variation such that a minimum of five (5) times the Nominal Pulse Spacing (NPS) exists with less than 1/3 of the RMSEZ deviation from a low-slope plane. Slopes that exceed ten (10) percent were avoided. Each land cover type representing ten (10) percent or more of the total project area were tested and reported with a VVA. In land cover categories other than dense urban areas, the tested points did not have obstructions forty-five (45) degrees above the horizon to ensure a satisfactory TIN surface. The VVA value is provided as a target. It is understood that in areas of dense vegetation, swamps, or extremely difficult terrain, this value may be exceeded. The NVA value is a requirement that must be met, regardless of any allowed “busts” in the VVA(s) for individual land cover types within the project. Checkpoints for each assessment (NVA and VVA) are required to be well-distributed throughout the land cover type, for the entire project area. 2019-04-23T00:00:00 LiDAR Point Cloud Generation: Atlantic used Leica software products to download the IPAS ABGNSS/IMU data and raw laser scan files from the airborne system. Waypoint Inertial Explorer is used to extract the raw IPAS ABGNSS/IMU data, which is further processed in combination with controlled base stations to provide the final Smoothed Best Estimate Trajectory (SBET) for each mission. The SBETs are combined with the raw laser scan files to export the LiDAR ASCII Standard (*.las) formatted swath point clouds. 2019-04-23T00:00:00 LiDAR Calibration: Using a combination of GeoCue, TerraScan and TerraMatch; overlapping swath point clouds are corrected for any orientation or linear deviations to obtain the best fit swath-to-swath calibration. Relative calibration was evaluated using advanced plane-matching analysis and parameter corrections derived. This process was repeated interactively until residual errors between overlapping swaths, across all project missions, was reduced to ≤2cm. A final analysis of the calibrated lidar is preformed using a TerraMatch tie line report for an overall statistical model of the project area. Individual control point assessments for this project can be found in Section VI of this report. Upon completion of the data calibration, a complete set of elevation difference intensity rasters (dZ Orthos) are produced. A user-defined color ramp is applied depicting the offsets between overlapping swaths based on project specifications. The dZ orthos provide an opportunity to review the data calibration in a qualitative manner. Atlantic assigns green to all offset values that fall below the required RMSDz requirement of the project. A yellow color is assigned for offsets that fall between the RMSDz value and 1.5x of that value. Finally, red values are assigned to all values that fall beyond 1.5x of the RMSDz requirements of the project. 2021-12-01T00:00:00 LiDAR Classification: Multiple automated filtering routines are applied to the calibrated LiDAR point cloud identifying and extracting bare-earth and above ground features. GeoCue, TerraScan, and TerraModeler software was used for the initial batch processing, visual inspection and any manual editing of the LiDAR point clouds. Atlantic utilized collected breakline data to preform classification for class 9 (Water). 2022-03-22T00:00:00 Original point clouds in LAS/LAZ format were restructured as Entwine Point Tiles and stored on Amazon Web Services. The data were re-projected horizontally to WGS84 Web Mercator (EPSG 3857). Vertically, no changes were made to the vertical datum (NAVD88 GEOID12B; EPSG 5703). U.S. Geological Survey processor References to the entwine point tiles and data reports were ingested into the Digital Coast Data Access Viewer. No changes to the data were made at this point. The Data Access Viewer will access the point cloud as it resides on AWS under the usgs-lidar-public container. 2022-05-19T00:00:00 Office for Coastal Management processor Entwine Point Tiles on AWS USGS https://usgs.entwine.io/ WWW:LINK-1.0-http--link USGS Entwine Point Cloud Source Citation URL information publisher