67591
2022 USGS CoNED Topobathymetric Model (1851 - 2020): Coastal Georgia
ga2022_coned_dem_m9559_metadata
Data Set
Published / External
49404
DEMs - partner (no harvest)
Project
Completed
2022
2022-06-30
To support Hurricane Florence impact modeling of storm-induced flooding and sediment transport, the U.S. Geological Survey (USGS) Coastal National Elevation Database (CoNED) Applications Project has created an integrated 1-meter topobathymetric digital elevation model (TBDEM) for coastal Georgia. High-resolution coastal topobathymetric data are required to characterize flooding, storms, and sea-level rise inundation hazard zones and other earth science applications, such as the development of sediment transport and storm surge models. This TBDEM consists of the best available multi-source topographic and bathymetric elevation data for Coastal Georgia including neighboring bays, estuaries, waterways, inlets, and islands. The Coastal Georgia TBDEM integrates 16 different data sources including topographic and bathymetric data, such as lidar point clouds and multi-beam acoustic surveys obtained USGS, the National Oceanic and Atmospheric Administration, the U.S. Army Corps of Engineers, and Federal Emergency Management Agency. The topographic and bathymetric surveys were sorted and prioritized based on survey date, accuracy, spatial distribution, and point density to develop a model based on the best available elevation and bathymetric data. Because bathymetric data are typically referenced to tidal datums, such as Mean High Water or Mean Low Water, all tidally referenced heights were transformed into orthometric heights based on the GEOID12B geoid, which is normally used for mapping elevation on land using the North American Vertical Datum of 1988. The spatial horizontal resolution is 1-meter with the general location ranging from the South Carolina border to the Georgia/Florida border. The overall temporal range of the input topography and bathymetry is 1851 to 2020 with a maximum depth extending to 44.4 meters. The topography surveys are from 1999-2020. The bathymetry surveys were acquired between 1851 and 2020.This data release was funded by the USGS Coastal and Marine Hazards and Resources Program (CMHRP) for coastal Georgia.
As a collaboration between the U.S. Geological Survey (USGS) Coastal and Marine Hazards and Resources Program, the USGS National Geospatial Program, and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information, the USGS Coastal National Elevation Database (CoNED) Applications Project integrates disparate light detection and ranging (lidar) and bathymetric data sources into a common three-dimensional (3D) database aligned both vertically and horizontally to a common reference system. The CoNED Projectâs topobathymetric digital elevation model (TBDEM) development is focused on select regions around the United States Coast, such as the Northern Gulf of Mexico, Coastal Carolinas, Georgia, Northeast, California Coast, Pacific Northwest, and the North Slope of Alaska. CoNED Project TBDEMs provide a required seamless elevation product for several science application studies, such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, tsunami impact assessment, and to analyze the impact of various climate change scenarios on coastal regions. The raster TBDEM product in Cloud Optimized GeoTIFF (COG) format, the Federal Geographic Data Committee (FGDC) formatted metadata, spatially referenced metadata, and the spatial metadata data dictionary are contained in the downloadable bundle. Spatially referenced metadata are contained in both an ESRI file geodatabase and Open Geospatial Consortium (OGC) GeoPackage formats that contains footprints for each of the input source areas. References: Danielson, J.J., Poppenga, S.K., Brock, J.C., Evans, G.A., Tyler, D.J., Gesch, D.B., Thatcher, C.A., and Barras, J.A., 2016, Topobathymetric elevation model development using a new methodology-Coastal National Elevation Database: Journal of Coastal Research, SI no. 76, p. 75-89, at http://dx.doi.org/10.2112/SI76-008. Thatcher, C.A., Brock, J.C., Danielson, J.J., Poppenga, S.K., Gesch, D.B., Palaseanu-Lovejoy, M.E., Barras, J.A., Evans, G.A., and Gibbs, A.E., 2016, Creating a Coastal National Elevation Database (CoNED) for science and conservation applications: Journal of Coastal Research, SI no. 76, p. 64-74, at http://dx.doi.org/10.2112/SI76-007. Gesch, Dean B., Oimoen, Michael J., and Evans, Gayla A., 2014, Accuracy assessment of the U.S. Geological Survey National Elevation Dataset, and comparison with other large-area elevation datasets-SRTM and ASTER: U.S. Geological Survey Open-File Report 2014-1008, 10 p., at http://dx.doi.org/10.3133/ofr20141008. Sugarbaker, L.J., Constance, E.W., Heidemann, H.K., Jason, A.L., Lukas, Vicki, Saghy, D.L., and Stoker, J.M., 2014, The 3D Elevation Program initiativeâA call for action: U.S. Geological Survey Circular 1399, 35 p Carswell, W.J., Jr., 2013, The 3D Elevation ProgramâSummary for California: U.S. Geological Survey Fact Sheet 2013â3056, 2 p., http://pubs.usgs.gov/fs/2013/3056/
The data obtained through ScienceBase at https://www.sciencebase.gov/catalog/item/627aa0d1d34e8d45aa6e4e72 the "best available" data from the USGS. For questions on distribution, please refer to the Distribution Section, Contact Information. For processing, please refer to the Data Quality Section, Processing Step, Contact Information.
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE
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 > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM)
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > BATHYMETRY > COASTAL BATHYMETRY
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
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > GEORGIA
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
USGS Metadata Identifier
USGS:5d7641bee4b0c4f70d01f564
Theme
3DEP
Theme
CoNED
Theme
Coastal Zone
Theme
Coastal and Marine Hazards and Resources Program
Theme
Hurricane Florence
Theme
Light Detection and Ranging
Theme
National Standards for Spatial Digital Accuracy
Theme
Sonar
Theme
U.S. Geological Survey
Theme
USGS
Spatial
Geographic Names Information System
County of Brantley, GA
Spatial
Geographic Names Information System
County of Bryan, GA
Spatial
Geographic Names Information System
County of Bulloch, GA
Spatial
Geographic Names Information System
County of Camden, GA
Spatial
Geographic Names Information System
County of Charlton, GA
Spatial
Geographic Names Information System
County of Chatham, GA
Spatial
Geographic Names Information System
County of Effingham, GA
Spatial
Geographic Names Information System
County of Glynn, GA
Spatial
Geographic Names Information System
County of Liberty, GA
Spatial
Geographic Names Information System
County of Long, GA
Spatial
Geographic Names Information System
County of McIntosh, GA
Spatial
Geographic Names Information System
County of Screven, GA
Spatial
Geographic Names Information System
County of Wayne, GA
Spatial
U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D.C., National Instit
GA
Spatial
U.S. Department of Commerce, 1987, Codes for the identification of the States, the District of Columbia and the outlying areas of the United States, and associated areas (Federal Information Processing Standard 5-2): Washington, D.C., National Instit
Georgia
Spatial
U.S. Department of Commerce, 1995, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions, Federal Information Processing Standard 10-4,): Washington, D.C., National Institute of Standards and Technology
U.S.
Spatial
U.S. Department of Commerce, 1995, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions, Federal Information Processing Standard 10-4,): Washington, D.C., National Institute of Standards and Technology
US
Spatial
U.S. Department of Commerce, 1995, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions, Federal Information Processing Standard 10-4,): Washington, D.C., National Institute of Standards and Technology
USA
Spatial
U.S. Department of Commerce, 1995, Countries, dependencies, areas of special sovereignty, and their principal administrative divisions, Federal Information Processing Standard 10-4,): Washington, D.C., National Institute of Standards and Technology
United States
Office for Coastal Management
Charleston
SC
Data Set
Elevation
As Needed
Raster Digital Data Set
W. Matthew Cushing, Tyler, D.J., Danielson, J.J., Sandra Poppenga, Sean Beverly, Rakibul Shogib, 2021, Topobathymetric Model of Coastal Georgia, 1851 to 2020: U.S. Geological Survey data release, at https://doi.org/10.5066/P9J11VV6
Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty.
Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office for Coastal Management or its partners.
Please refer to the Data Quality Section, Source Citations for original source data information., W. Matthew Cushing (ORCID: 0000-0001-5209-6006) Dean Tyler (ORCID: 0000-0002-1542-7539) Jeffrey Danielson (ORCID: 0000-0003-0907-034X) Sandra Poppenga (ORCID: 0000-0002-2846-6836) Sean Beverly (ORCID: 0000-0002-4825-4056) Rakibul Shogib (ORCID: 0000-0001-6524-7838)
Data Steward
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Distributor
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Metadata Contact
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Point of Contact
2022
Organization
NOAA Office for Coastal Management
NOAA/OCM
coastal.info@noaa.gov
2234 South Hobson Ave
Charleston
SC
29405-2413
(843) 740-1202
https://coast.noaa.gov
NOAA Office for Coastal Management Home Page
Online Resource
Ground Condition
-82.15
-80.77
32.835
30.43
Range
1851
2020
Yes
Vertical
EPSG:5703
NAVD88 height
North American Vertical Datum 1988
1
Gravity-related height
H
metre
up
Projected
EPSG:6346
NAD83(2011) / UTM zone 17N
NAD83 (National Spatial Reference System 2011)
GRS 1980
6378137
298.257222101
NAD83(2011)
UTM zone 17N
Transverse Mercator
Latitude of natural origin
0° 0' 0" N
Longitude of natural origin
81° 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
Unclassified
Data is available online for bulk and 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.
2022-07-29
https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=9559/details/9559
2022
Organization
NOAA Office for Coastal Management
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
2022-07-29
https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/CoNED_GA_DEM_2022_9559/index.html
2022
Organization
NOAA Office for Coastal Management
Bulk Download
Bulk download of data files in the original coordinate system.
GeoTIFF
GeoTIFF
https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/CoNED_GA_DEM_2022_9559/supplemental/ga2022_coned_m9559.kmz
Browse Graphic
Browse Graphic
KMZ
Link to the data set footprint.
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.
https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/CoNED_GA_DEM_2022_9559/supplemental/index.html
Geospatial Metadata
Online Resource
Zip
Link to the spatial metadata data dictionary and the spatially referenced metadata in ESRI file geodatabase (gdb) and Open Geospatial Consortium (OGC) GeoPackage (gpkg) formats.
https://www.usgs.gov/special-topics/coastal-national-elevation-database-applications-project
USGS CoNED Applications Project
Online Resource
HTML
Link to the USGS CoNED Applications Project
For usability, Esri ArcGIS 10.8.1, Esri ArcGIS Pro 2.9, GeoCue LP360, Global Mapper, Geospatial Data Abstraction Library (GDAL), or equivalent GIS processing software and supporting operating systems are suggested for viewing the spatial metadata.
The horizontal accuracy for the integrated topobathymetric digital elevation model (TBDEM) was not assessed quantitatively.
Integrated TBDEM Vertical Accuracy Assessment (GEOID12B).
The TBDEM root mean square error (RMSE) over the land and nearshore area is 0.46 meters versus 86 National Oceanic and Atmospheric Administration (NOAA) National Geodetic Survey (NGS) Global Positioning System (GPS) on Benchmarks (GPSonBM) control distributed throughout the high-resolution lidar areas.
Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details
No formal logical accuracy tests were conducted.
This CoNED data set for coastal Georgia was provided to NOAA OCM by USGS for inclusion in the NOAA Digital Coast Data Access Viewer.
2007 Florida Division of Emergency Management (FDEM) Lidar Project: Nassau County
2008-01-01
Discrete
2007
https://coast.noaa.gov/htdata/lidar1_z/
Nassau County, FL
2007 South Carolina LiDAR: Charleston (partial), Jasper, and Colleton Counties
2008-03-26
Discrete
2007
https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/
Charleston, Colleton, Jasper Counties, SC
2009 Chatham County, GA, Lidar DEM
2012-01-01
Discrete
2009
https://coast.noaa.gov/htdata/lidar1_z/
Chatham County, GA
2010 ARRA Lidar: Allendale County (SC)
2011-05-01
Discrete
2010
https://coast.noaa.gov/htdata/lidar1_z/
Allendale county SC, USA
2010 ARRA Lidar: Hampton County (SC)
2011-05-01
Range
2010-03-14
2010-03-20
https://chs.coast.noaa.gov/htdata/lidar1_z/geoid18/data/4803/
Hampton County SC
2010 Coastal Georgia Elevation Project Lidar Data (Bryan County)
2011-04-01
Discrete
2010
https://coast.noaa.gov/htdata/lidar1_z/
Bryan County, GA (only 2/3 southeastern 1/2; northwestern half not available)
2010 Lidar DEM: Coastal Georgia
2010-01-01
Range
2010-01-01
2010-03-31
https://coast.noaa.gov/htdata/lidar1_z/
Brantley, Camden, Charlton, Long, McIntosh, and Wayne counties of GA, USA
2016 USACE NCMP Topobathy Lidar: Florida East Coast
2016-12-15
Discrete
2016
https://coast.noaa.gov/htdata/lidar1_z/
Florida East Coast
2016 USACE Post-Matthew Topobathy Lidar: Southeast Coast (VA, NC, SC, GA and FL)
2017-02-15
Range
2016-10-01
2016-12-01
https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/USACE_post_matthew_DEM_2016_6234/index.html
VA, NC, SC, GA and FL
2016-2017 NOAA NGS Topobathy: Coastal South Carolina
2018-08-24
Discrete
2016
https://coast.noaa.gov/htdata/lidar1_z/
Coastal SC
2017 USACE FEMA Topobathy Lidar: Florida East Coast, Florida Keys, and Collier County (Post-Irma)
2017-10-02
Discrete
2017
https://coast.noaa.gov/htdata/lidar1_z/
FL East Coast, Keys, and Collier County
Continuously Updated Digital Elevation Model (CUDEM) - Third Arc-Second Resolution Bathymetric-Topographic Tiles
2019-01-24
Range
1851
2018
https://noaa-nos-coastal-lidar-pds.s3.us-east-1.amazonaws.com/dem/NCEI_third_Topobathy_2014_8580/
Coast of NC, SC, GA and FL
Elevation Void Fill (method used to interpolate elevation in cases where no-data gap occurs)
2021-01-01
Discrete
2021
https://pro.arcgis.com/en/pro-app/latest/help/analysis/raster-functions/elevation-void-fill-function.htm
NC, SC, and GA
NOAA NCEI CUDEM 1/3-1/9 Channel Filter
2021-01-01
Discrete
2021
https://pro.arcgis.com/en/pro-app/latest/help/analysis/raster-functions/elevation-void-fill-function.htm
GA
USACE NCMP Topobathy Lidar East Coast (NY, NJ, DE, MD, VA, NC, SC, GA)
2017-01-01
Discrete
2017
https://coast.noaa.gov/htdata/lidar1_z/
NY, NJ, DE, MD, VA, NC, SC, and GA
USGS NED 1/3 arc-second
2013-01-01
Range
1999
2013
https://www.sciencebase.gov/catalog/item/4f70aa9fe4b058caae3f8de5
GA
1
The principal methodology for developing the integrated topobathymetric digital elevation model (TBDEM) can be organized into three main components. The "topography component" consists of the land-based elevation data, which is primarily comprised from high-density lidar data. The topographic source data will include lidar data from different sensors (Topographic, Bathymetric) with distinct spectral wavelengths (NIR-1064nm, Green-532nm). The "bathymetry component" consists of hydrographic sounding (acoustic) data collected using watercraft rather than bathymetry acquired from green laser lidar within an airborne platform. The most common forms of bathymetric acquisitions include are multi-beam, single-beam, and swath. The final component, "integration", encompasses the assimilation of the topographic and bathymetric data along the near-shore based on a predefined set of priorities. The land/water interface (+1 m- -1.5 m elevation) is the most critical area, and green laser systems, such as the Experimental Advanced Airborne Research lidar (EAARL-B) and the Coastal Zone Mapping and Imaging Lidar (CZMIL) that cross the near-shore interface are valuable in developing a seamless transition. The TBDEM created from the topography and bathymetry components is a raster with associated spatial masks and metadata that can be passed to the integration component for final model incorporation.
Topo/Bathy Creation Steps: Topography Processing Component: a) Quality control check the vertical and horizontal datum and projection information of the input lidar source to ensure the data is referenced to the North American Vertical Datum of 1988 (NAVD88), the North American Datum of 1983 (NAD83), and the Universal Transverse Mercator (UTM) projection. If the source data is not NAVD88, transform the input lidar data to NAVD88 reference frame using current National Geodetic Survey (NGS) geoid models and NOAA’s Vertical Datums Transformation (VDatum) software. Likewise, if required, convert the input source data to NAD83 2011 and reproject to UTM. b) Check the classification of the topographic lidar data to verify the data are classified with the appropriate classes. If the data have not been classified, then classify the raw point cloud data to non-ground (class 1) ground (class 2), and water (class 9) classes using LP360-Classify. c) Derive associated breaklines from the classified lidar to capture internal water bodies, such as lakes and ponds and inland waterways. Inland waterways and water bodies will be hydro-flattened where no bathymetry is present. d) Extract the ground returns from the classified lidar data and randomly spatial subset the points into two-point sets based on the criteria of 95 percent of the points for the "Actual Selected" set and the remaining 5 percent for the "Test Control" set. The "Actual Selected" points will be gridded in the terrain model along with associated breaklines and masks to generate the topographic surface, while the "Test Control" points will be used to compute the interpolation accuracy, Root Mean Square Error (RMSE) from the derived surface. e) Generate the minimum convex hull boundary from the classified ground lidar points that creates a mask that extracts the perimeter of the exterior lidar points. The mask is then applied in the terrain to remove extraneous terrain artifacts outside of the extent of the ground lidar points. f) Using a terrain model based on triangulated irregular networks (TINs), grid the "Actual Selected" ground points using breaklines and the minimum convex hull boundary mask at a 1-meter spatial resolution using a natural neighbor interpolation algorithm. g) Compute the interpolation accuracy by comparing elevation values in the "Test Control" points to values extracted from the derived gridded surface; report the results in terms of RMSE.
2021-11-08T00:00:00
2
Bathymetry Processing Component: a) Quality control check the vertical and horizontal datum and projection information of the input bathymetric source to ensure the data is referenced to NAVD88 and NAD83, UTM. If the source data are not NAVD88, transform the input bathymetric data to NAVD88 reference frame using VDatum. Likewise, if required, convert the input source data to NAD83 and reproject to UTM. b) Prioritize and spatially sort the bathymetry based on date of acquisition, spatial distribution, accuracy, and point density to eliminate any outdated or erroneous points and to minimize interpolation artifacts. c) Randomly subset the bathymetric points into two-point sets based on the criteria of 95 percent of the points for the "Actual Selected" set and the remaining 5 percent for the "Test Control" set. The "Actual Selected" points will be gridded in the empirical Bayesian krigging model along with associated masks to generate the bathymetric surface, while the "Test Control" points will be used to compute the interpolation accuracy (RMSE) from the derived surface. d) Spatially interpolate bathymetric single-beam, multi-beam, and hydrographic survey source data using an empirical Bayesian krigging gridding algorithm. This approach uses a geostatistical interpolation method that accounts for the error in estimating the underlying semivariogram (data structure - variance) through repeated simulations. e) Cross validation - Compare the predicted value in the geostatistical model to the actual observed value to assess the accuracy and effectiveness of model parameters by removing each data location one at a time and predicting the associated data value. The results will be reported in terms of RMSE. f) Compute the interpolation accuracy by comparing elevation values in the "Test Control" points to values extracted from the derived gridded surface; report the results in terms of RMSE.
2021-11-08T00:00:00
3
Integration Component: a.) Analyze the input data priority based on project characteristics, including acquisition dates, cell size, retention of features, water surface treatment, visual inspection, and presence of artifacts. b.) Prioritize and spatially sort the input topographic, topobathymetric, and bathymetric raster layers based on date of survey acquisition date, accuracy, spatial distribution, and point density to sequence the raster data in the integrated elevation model. c.) Develop an ArcGIS geodatabase (Mosaic Dataset) and spatial seamlines for each individual topographic, topobathymetric, and bathymetric raster layer included in the integrated elevation model. d.) Create an overview project masking polygon (based on final pilot study AOI) e.) Using Grid Index Features, create a 6000x6000 fishnet feature class for tile-based integration processing f.) Create simple raster (vector) boundaries (custom simple_raster_bnd_batch tool) from the final set of input rasters based on the input priority. The rasters should be prioritized with the highest priority ranking on top and so forth. g.) Generate spatially referenced metadata for each input raster (custom make spatial metadata tool) from the simple raster boundary files, based on the input priority. The boundaries should be prioritized with the lowest priority (input raster layer) ranking on top and so forth. The spatially referenced metadata consists of the group of geospatial polygons that represent the spatial footprint of each data source used in the generation of the TBDEM. Each polygon is populated with raster metadata attributes that describe the source data, such as, resolution, acquisition date, source name, source organization, source contact, source project, source URL, and data type (topographic lidar, topobathymetric lidar, multibeam bathymetry, single-beam bathymetry, etc.). h.) Generalize seamline edges to smooth transition boundaries between neighboring raster layers and split complex raster datasets with isolated regions into individual unique raster groups. i.) Using the spatial metadata and tile fishnet, spatially mosaic (custom make micro mosaic dataset tool) the input raster data sources based on priority to create a seamless topobathymetric composite at a cell size of 1-meter using a linear spatial blending (ten pixel overlapping area) technique between input source layers. j.) Perform a visual quality assurance (Q/A) assessment on the output TBDEM composite to review the integrated mosaic for artifacts and anomalies.
2021-11-08T00:00:00
4
The NOAA Office for Coastal Management (OCM) received one tif file for the topobathymetric data for coastal Georgia from the USGS Coastal National Elevation Database (CoNED) Applications Project for inclusion in the NOAA Digital Coast Data Access Viewer. The data were in UTM Zone 17 NAD83(2011), meters coordinates and in NAVD88 (Geoid12B) elevations in meters. The data were at a 1m grid spacing. The data were retiled to 961, cloud optimized GeoTiffs using gdal_retile.py and the horizontal (6346) and vertical (5703) EPSG codes were assigned.
2022-07-29T00:00:00
Organization
Office for Coastal Management
OCM
2234 South Hobson Avenue
Charleston
SC
29405-2413
https://www.coast.noaa.gov/
gov.noaa.nmfs.inport:67591
Rebecca Mataosky
2022-07-29T15:19:46
Kirk Waters
2024-01-10T19:26:10
2024-01-10
OCM Partners
OCMP
1002
Public
No
2022-08-01
1 Year
2023-08-01