gov.noaa.nmfs.inport:71179 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 2026-04-30T00:00:00 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) point 165228593 NAD83(2011) / UTM zone 16N2008-11-12publicationEuropean Petroleum Survey Grouphttps://apps.epsg.org/api/v1/CoordRefSystem/6345/export/?format=gmlurn:ogc:def:crs:EPSG:63456.18.3 2022 NOAA OCM Topobathy Lidar: Washington Island, WI wi2022_wash_isl_m9949 2022 creation 2023-01-18 publication NOAA/NMFS/EDM 71179 https://www.fisheries.noaa.gov/inport/item/71179 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/geoid18/9949/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=9956/details/9956 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/geoid18/9949/supplemental/GreenBay_Topobathy_Lidar_Project_Report_508OCM.pdf WWW:LINK-1.0-http--link Lidar Report Link to the Dewberry lidar report. download https://coast.noaa.gov/lidar/viewer/v/noaapotree.html?r=https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/entwine/geoid18/9949/ept.json WWW:LINK-1.0-http--link 3D Viewer (Potree NOAA) 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 These data were collected by Dewberry using a CZMIL Super Nova system. The data were acquired from 20220719 through 20220816. The data include topobathy data in LAS 1.4 format classified as unclassified (1); ground (2); low noise (7); high noise (18); bathymetric bottom (40); water surface (41); derived water surface (42); submerged object, not otherwise specified (e.g., wreck, rock, submerged piling) (43); and no bottom found (bathymetric lidar point for which no detectable bottom return was received) (45). This dataset consists of approximately 219 square miles of data along the shores of Green Bay and contains 2,630 500 m x 500 m LAS tiles. In addition to the lidar point data, topobathy bare earth Digital Elevation Models (DEMs) at a 1 meter grid spacing, created from the lidar point data are available from the NOAA Digital Coast. A link to this data is provided in the URL section of this metadata record. This data set contains point cloud data(' in LAZ (compressed LAS) format', ''). The data may have been reprojected or otherwise modified from the original data in an automated process. Disregard projection information in this abstract and refer to the spatial reference section. This dataset has two primary goals to fill critical gaps in our understanding of benthic habitat within Lake Michigan and northern Green Bay. The first goal is the collection of new bathymetric lidar to support multiple agencies including NOAA; US Fish and Wildlife Service; state agencies with Michigan and Wisconsin; and other regional partners' mapping and modeling needs by expanding existing high resolution bathymetry coverage in northern Green Bay. The second goal is to use this bathymetry in the creation of new benthic mapping products using the Coastal and Marine Ecological Classification Standard (CMECS). We request that you credit the National Oceanic and Atmospheric Administration (NOAA) when you use these data in a report, publication, or presentation: Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA) The custom download may be cited as National Oceanic and Atmospheric Administration (NOAA) Digital Coast Data Access Viewer. Charleston, SC: NOAA Office for Coastal Management. Accessed 2026-06-21 at https://coast.noaa.gov/dataviewer. 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/geoid18/9949/supplemental/wi2022_green_bay_m9949.kmz This graphic shows the lidar coverage for the 2022 topobathy lidar acquisition around Washington Island in northern Green Bay. kmz EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > BATHYMETRY > COASTAL BATHYMETRY EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL 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 > GREAT LAKES CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > WISCONSIN 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 Lidar project InPort otherRestrictions This data set was compiled dynamically. It will be removed 10 days after 2026-06-21 from the NOAA system. Cite As: Office for Coastal Management, [Date of Access]: 2022 NOAA OCM Topobathy Lidar: Washington Island, WI [Data Date Range], https://www.fisheries.noaa.gov/inport/item/71179. 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 This data set was compiled dynamically. It will be removed 10 days after 2026-06-21 from the NOAA system. Access Constraints: None otherRestrictions This data set was compiled dynamically. It will be removed 10 days after 2026-06-21 from the NOAA system. 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 This data set was compiled dynamically. It will be removed 10 days after 2026-06-21 from the NOAA system. 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 2022 NOAA OCM Topobathy Lidar DEM: Washington Island, WI NOAA/NMFS/EDM 71220 crossReference vector eng; US elevation OS Independent -87.041476 -86.664068 45.131468 45.445808 | Currentness: Ground Condition 2022-07-19 2022-08-16 Data include all lidar returns. Outliers or false returns (e.g., returns from birds, atmospheric particles, and/or system noise) may be present in the data. An automated ground classification algorithm was used to determine bare earth point classification. It should be noted that not all returns were correctly classified; therefore the user should examine for acceptability. LAS/LAZ - LASer Zip LAS/LAZ - LASer 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=9949/details/9949 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/geoid18/9949/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 Only checkpoints photo-identifiable in the intensity imagery can be used to test the horizontal accuracy of the lidar. Photo-identifiable checkpoints in intensity imagery typically include checkpoints located at the ends of paint stripes on concrete or asphalt surfaces or checkpoints located at 90 degree corners of different reflectivity, e.g. a sidewalk corner adjoining a grass surface. The xy coordinates of checkpoints, as defined in the intensity imagery, are compared to surveyed xy coordinates for each photo-identifiable checkpoint. These differences are used to compute the tested horizontal accuracy of the lidar. As not all projects contain photo-identifiable checkpoints, the horizontal accuracy of the lidar cannot always be tested. Vertical Positional Accuracy The vertical accuracy of the classified lidar was tested by Dewberry with 46 independent survey checkpoints. The survey checkpoints are evenly distributed throughout the project area and are located in areas of non-vegetated terrain, including bare earth, open terrain, and urban terrain (22); vegetated terrain, including forest, brush, tall weeds, crops, and high grass (14); and submerged bottom areas (10). The vertical accuracy is tested by comparing survey checkpoints to a triangulated irregular network (TIN) that is created from the lidar ground and submerged bottom points. Checkpoints are always compared to interpolated surfaces created from the lidar point cloud because it is unlikely that a survey checkpoint will be located at the precise location of a discrete lidar point. All checkpoints located in non-vegetated terrain were used to compute the Non-vegetated Vertical Accuracy (NVA). Project specifications require a NVA of 19.6 cm at the 95% confidence level based on RMSEz (10 cm) x 1.9600. All checkpoints located in vegetated terrain were used to compute the Vegetated Vertical Accuracy (VVA). Project specifications require a VVA of 30.0 cm based on the 95th percentile. All checkpoints located in bathymetric areas were used to compute an accuracy value for the bathymetric data. Project specifications require the vertical accuracy for bathymetric data to be 29.4 cm or better at the 95% confidence level based on depth-dependent RMSEz (15.0 cm) x 1.9600. This lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual NVA accuracy was found to be RMSEz = 7.2 cm, equating to +/- 14.2 cm at the 95% confidence level. This lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 10 cm RMSEz Vertical Accuracy Class. Actual VVA accuracy was found to be +/- 18.2 cm at the 95th percentile. The 5% outliers consisted of 1 checkpoint that was larger than the 95th percentile. This checkpoint has a DZ value of 18.5 cm This lidar dataset was tested to meet ASPRS Positional Accuracy Standards for Digital Geospatial Data (2014) for a 15.0 cm RMSEz Vertical Accuracy Class. Actual Bathymetric accuracy was found to be RMSEz = 13.2 cm, equating to +/- 25.8 cm at the 95% confidence level Quantitation Limits Data include all lidar returns. Outliers or false returns (e.g., returns from birds, atmospheric particles, and/or system noise) may be present in the data. An automated ground classification algorithm was used to determine bare earth point classification. It should be noted that not all returns were correctly classified; therefore the user should examine for acceptability. Completeness Report Data covers the project boundary. Conceptual Consistency Not applicable This data was collected by Dewberry for the NOAA Office for Coastal Management (OCM). The data was provided to NOAA OCM where it was processed to the NOAA Digital Coast Data Access Viewer (DAV) to make the data available for custom and bulk download. Data were processed to an initial LAS format using Teledyne CARIS software. CARIS was also utilized for GPS and inertial processing, and Terrasolid and LAStools were used for data visualization, 3D editing, and export to final LAS/LAZ. Data were processed using NAD83(2011) horizontal and vertical datums. The data are in UTM Zone 16 coordinates and NAVD88 elevations in meters. The data classifications are: unclassified (1); ground (2); noise (7); water surface (topographic sensor) (18); bathymetric bottom (40); water surface (41); derived water surface (42); submerged object, not otherwise specified (e.g., wreck, rock, submerged piling) (43); and no bottom found (bathymetric lidar point for which no detectable bottom return was received) (45). 2023-01-17T00:00:00 The boresight for each lift was done individually as the solution may change slightly from lift to lift. The initial points for each mission calibration were inspected for flight line errors, flight line overlap, slivers or gaps in the data, point data minimums, or issues with the lidar unit or GPS. Roll, pitch and scanner scale were optimized during the calibration process until the relative accuracy was met. Dewberry utilized Bayesmap StripAlign for this alignment procedure. This alignment procedure corrected systematic issues globally, per aircraft lift, per flightline, and finally based on local errors along the flight trajectory. Error adjustments included internal sensor parameters. Due to the complex geometric relationship of the elliptical scan pattern the forward and reverse directions must be aligned independently. Additionally, since the green and NIR scanner map different surfaces, they were also aligned independently, then corrected to match each other. Difference rasters (DZ orthos) were generated, adjustment parameters were reviewed, and registration/match regions were reviewed to ensure data quality. A final vertical accuracy check of the boresighted flight lines was completed against the surveyed check points after the z correction to ensure the requirement of NVA = 19.6 cm 95% Confidence Level was met. Point classification was performed according to USGS Lidar Base Specification 2.1. Bare earth DEMs were exported from the classified point cloud. Synthetic points generated by CZMIL refraciton correction algorithms are present in this dataset. Please see the final project report for more details on the synthetic points 2023-01-17T00:00:00 Dewberry used algoritms in TerraScan to create the intial ground/submerged topography surface. Dewberry used rasterized aggregate extents of refracted points to create automated 2-D breaklines with LAStools and ArcGIS. Light travels at different speeds in air versus water and its speed and direction of travel change when it enters the water column. The refraction correction process accounts for this difference by adjusting the depth (distance traveled) and horizontal position (change of angle/direction) of the lidar points acquired within water. These breaklines delineate areas where the refraction correction was applied to the lidar data by CZMIL's automated refraction correction software based on the software's detection of water. The class 42 synthetic surface is generated by the software as a reference surface from which to perform the correction. Dewberry used the 2-D refraction extents and additional bathy features to classify the bathymetric bottom and ground points properly in TerraScan. Geometrically unused points at the edges of flight lines were flagged using the withheld bit. This includes synthetically generated class 42 (synthetic water surface) points at the edges of flight lines. All class 42 points were flagged using the synthetic bit. The withheld bit was set on class 7 and class 18 in TerraScan after all classification was complete. All lidar data was peer-reviewed. Dewberry's QAQC also included creating void polygons for use during review. All necessary edits were applied to the dataset. LASTools software was used to update LAS header information, including all projection and coordinate reference system information. The final lidar data are in LAS format 1.4 and point data record format 6. All data was then verified by an Independent QC department within Dewberry. The independent QC was performed by separate analysts who did not perform manual classification or editing. The independent QC involved quantitative and qualitative reviews. 2023-01-17T00:00:00 The NOAA Office for Coastal Management (OCM) received 2630 topobathy las files from Dewberry for northern Green Bay, Wisconsin. The lidar data had elevation and intensity measurements. The data were in UTM Zone 16N (NAD83 2011), meters coordinates and NAVD88 (Geoid18) elevations in meters. The data were classified as: 1 - Unclassified, 2 - Ground, 7 - Low Noise, 18 - High Noise, 40 - Bathymetric Point, 41 - Water Surface , 42 - Derived Water Surface , 43 - Submerged Object, 45 - No bathymetric bottom found. OCM processed all classifications of points to the Digital Coast Data Access Viewer (DAV). Classes available on the DAV are: 1, 2, 7, 18, 40, 41, 42, 43, 45. 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, by flight ID, the gps times, and intensity ranges. 2. Internal OCM scripts were run on the las files to, convert from UTM Zone 16N (NAD83 (2011) meters coordinates to geographic coordinates, to convert from NAVD88 meters elevations to ellipsoid elevations using the NOAA NGS Geoid18 model, to assign the geokeys, to sort the data by gps time and zip the data to database and to AWS S3. 2023-10-20T00:00:00 Office for Coastal Management processor LAS Files 2023-10-24 publication NOAA Office for Coastal Management (OCM) originator The dataset has been mosaiced, reprojected, and clipped as needed from the original input files using PDAL and GDAL commands. 2026-06-21NOAA Office for Coastal Managementcoastal.info@noaa.govprocessor