56773 NOAA_MD1702_Topobathy_DEM.xml Data Set Published / External 47844 DEMs Project Completed 2019 This data was collected by NOAA using a Riegl VQ880G sensor. The data was acquired August 5, 2017. The data includes topobathy data in LAS 1.2 format classified as created,unclassified (1); ground (2); topographic noise (7); bathymetric noise (22); water column (25); bathymetric bottom (26); water surface (27); International Hydrographic Organization S-57 object; not otherwise specified (30), in accordance with project specifications. The project consists of approximately 34 square miles of data along the shores of St. Jeromes Creek. This dataset contains 342 500 m x 500 m lidar tiles. St. Jeromes Creek has been identified as having critical topographic and bathymetric data gaps by NOAA. This lidar data will fill those critical gaps. The full workflow used for this project is found in the final project report submitted to NOAA. Theme Global Change Master Directory (GCMD) Science Keywords EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION Theme Global Change Master Directory (GCMD) Science Keywords EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > SEAFLOOR TOPOGRAPHY Theme Global Change Master Directory (GCMD) Science Keywords EARTH SCIENCE > OCEANS > COASTAL PROCESSES > COASTAL ELEVATION Theme ISO 19115 Topic Category elevation Spatial Global Change Master Directory (GCMD) Location Keywords CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA Spatial Global Change Master Directory (GCMD) Location Keywords VERTICAL LOCATION > LAND SURFACE Spatial Global Change Master Directory (GCMD) Location Keywords VERTICAL LOCATION > SEA FLOOR Instrument Global Change Master Directory (GCMD) Instrument Keywords LIDAR > Light Detection and Ranging Platform Global Change Master Directory (GCMD) Platform Keywords Airplane > Airplane Theme DEM Office for Coastal Management Charleston SC Data Set Elevation None Planned Elevation Data Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the National Geodetic Survey, the Coastal Services Center, or its partners. Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA) Data Steward 2019 Organization Office for Coastal Management OCM https://ror.org/05v14bq57 2234 South Hobson Avenue Charleston SC 29405-2413 https://www.coast.noaa.gov/ Distributor 2019 Organization Office for Coastal Management OCM https://ror.org/05v14bq57 2234 South Hobson Avenue Charleston SC 29405-2413 https://www.coast.noaa.gov/ Metadata Contact 2019 Organization Office for Coastal Management OCM https://ror.org/05v14bq57 2234 South Hobson Avenue Charleston SC 29405-2413 https://www.coast.noaa.gov/ Point of Contact 2019 Organization Office for Coastal Management OCM https://ror.org/05v14bq57 2234 South Hobson Avenue Charleston SC 29405-2413 https://www.coast.noaa.gov/ Ground Condition -76.386945 -76.304493 38.165636 38.020557 Discrete 2017-08-05 Projected EPSG:6347 NAD83(2011) / UTM zone 18N NAD83 (National Spatial Reference System 2011) GRS 1980 6378137 298.257222101 NAD83(2011) UTM zone 18N Transverse Mercator Latitude of natural origin 0° 0' 0" N Longitude of natural origin 75° 0' 0" W Scale factor at natural origin 0.9996 False easting 500000 metre False northing 0 metre 1 Easting E metre east 2 Northing N metre north Vertical EPSG:5703 NAVD88 height North American Vertical Datum 1988 1 Gravity-related height H metre up Unclassified Data is available online for custom downloads None 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. https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=8778 2019 Organization Office for Coastal Management https://ror.org/05v14bq57 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. Zip Zip https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/NGS_MD_StJeromesCreek_DEM_2017_8778/index.html 2019 Organization Office for Coastal Management https://ror.org/05v14bq57 Bulk Download Bulk download of data files in the original coordinate system. img IMG - ERDAS Imagine https://noaa-nos-coastal-lidar-pds.s3.amazonaws.com/laz/geoid12b/8777/supplemental/md2017_ngs_topobathy_stjeromecreek_m8777.kmz Browse graphic Browse Graphic KML This graphic displays the footprint for this lidar data set. https://coast.noaa.gov/ NOAA's Office for Coastal Management (OCM) website Online Resource HTML Information on the NOAA Office for Coastal Management (OCM) https://coast.noaa.gov/dataviewer/ NOAA's Office for Coastal Management (OCM) Data Access Viewer (DAV) Online Resource HTML 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. OS Independent NOAA acquired and calibrated all lidar data and Dewberry classified this data and created derivative products. As such, Dewberry did not perform any absolute positional accuracy testing on this dataset. The DEMs are derived from the source lidar and inherit the accuracy of the source data. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production. NOAA acquired and calibrated all lidar data and Dewberry classified this data and created derivative products. NOAA collected lidar data to meet 15cm vertical accuracy at 1 sigma. Dewberry did not perform any absolute positional accuracy testing on this dataset. The DEMs are derived from the source lidar and inherit the accuracy of the source data. The DEMs are created using controlled and tested methods to limit the amount of error introduced during DEM production. Data covers the project boundary. Not applicable Lidar was acquired by NOAA and processed by Dewberry. 1 Data for the St. Jeromes Creek project was acquired by NOAA using a Riegl VQ880G sensor. All delivered lidar data is referenced to: Horizontal Datum-NAD83 (2011) epoch: 2010 Projection-UTM Zone 18 North Horizontal Units-meters Vertical Datum-NAD83(2011) epoch: 2010 Vertical Units-meters This dataset encompasses 342 500m x 500m tiles. Both green lidar data and NIR lidar data were acquired. NOAA acquired, calibrated, and performed the refraction correction of the lidar data. Light travels at different speeds in air versus water and its direction of travel or angle is changed or refracted when entering the water column. The refraction correction process corrects for this difference by adjusting the depth (distance traveled) and horizontal position (change of angle/direction) of the lidar data acquired within water. Dewberry received the calibrated green and NIR data and verified complete coverage. Relative accuracy of the green swaths compared to overlapping and adjacent green swaths as well as the relative accuracy of green swaths compared to overlapping and adjacent NIR swaths was verified through the use of Delta-Z (DZ) orthos created in GeoCue software. Intraswath or within a swath relative accuracy was verified using Quick Terrain Modeler. Profiles of elevated planar features, such as roofs, were used to verify horizontal alignment between overlapping swaths. Dewberry used algorithms in TerraScan to create the intial ground/submerged topography surface. Dewberry created 2-D breaklines by digitizing breaklines in a 2-D environment using intensity imagery as a reference. Dewberry used the 2-D breaklines to classify the bathymetric bottom and ground points properly in TerraScan. 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. GeoCue software was used to update LAS header information, including all projection and coordinate reference system information. The final lidar data is in LAS format 1.2 and point data record format 3. The final classificaton scheme is as follows: 1-Unclassified 2-Ground 7-Topographic Noise 22-Bathymetric Noise 25-Water Column 26-Bathymetric Bottom 27-Water Surface 30-International Hydrograpic Organization (IHO) S-57 Object 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. 2019-02-01T00:00:00 Organization National Geodetic Survey NGS https://ror.org/02f762h70 1315 East-West Hwy Silver Spring MD 20910 https://geodesy.noaa.gov/ 2 Dewberry made a copy of the final lidar data and transformed the data from ellipsoid heights to orthometric heights, referenced to NAVD88 Geoid 12B, meters. The lidar data in orthometric heights was used to create the final topobathymetric DEMs in orthometric heights Lidar data was converted to a LAS Dataset. Lidar data classified as ground (2) and submerged topography (26) were then used to generate a raster in IMG format with 1 meter pixel resolution. The output raster was created over the full AOI area to reduce edge-matching issues and improve seamlessness. The raster was clipped to the tile grid and named according to project specifications to result in tiled topobathymetric DEMs. All tiled DEMs incorporate the use of the void polygons. The void polygons represent bathymetric areas with no bathymetric bottom returns and are set as NoData in the DEMs. Void polygon creation is described in the final project report and the void polygon metadata. A confidence layer has been created and provided to NOAA as part of the deliverables. Except where there are not enough lidar data points in a pixel to calulate a standard deviation value, the confidence layer is a raster product in IMG format with 1 meter square pixels. The confidence layer provides a standard deviation value for every pixel by calculating the standard deviation of all ground and/or submerged topography lidar points that are located within a single pixel. The confidence layer pixels align to the pixels in the topobathy DEMs. The confidence layer can be displayed by unique values or classified into desired bins/ranges for analysis over larger areas. 2019-03-01T00:00:00 gov.noaa.nmfs.inport:56773 Maryellen Sault 2019-07-01T09:17:57 SysAdmin InPortAdmin 2026-03-04T19:17:25 2024-01-10 Office for Coastal Management OCM 1002 Public No No 2022-03-16 1 Year 2023-03-16