Jeffrey Danielson / Dean Tyler *, U.S. Geological Survey, Physical Geographer Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS), Office for Coastal Management (OCM) 20170303 First raster digital data Topobathymetric Model, 1887 to 2016 0.1 Sioux Falls, SD U.S. Geological Survey https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6194 https://coast.noaa.gov/htdata/raster2/elevation/New_England_Coned_Topobathy_DEM_2016_6194 https://topotools.cr.usgs.gov/topobathy_viewer/ https://earthexplorer.usgs.gov/ https://viewer.nationalmap.gov/viewer/ Hurricane Sandy was the deadliest and most destructive hurricane of the 2012 Atlantic hurricane season, and the second-costliest with an estimated $71.4 billion (2013 USD). Hurricane Sandy affected 24 states, including the entire eastern seaboard with particularly severe damage in New Jersey and New York. In response to the storm, the U.S. Geological Survey (USGS) Coastal and Marine Geology Program in collaboration with the USGS National Geospatial Program (NGP), and National Oceanic and Atmospheric Administration (NOAA) developed a three-dimensional (3D) 1-meter topobathymetric elevation model (TBDEM) for the New England sub-region including the and adjacent coastline. High-resolution coastal elevation data is required to identify flood, hurricane, and sea-level rise inundation hazard zones and other earth science applications, such as the development of sediment transport and storm surge models. The new TBDEM consists of the best available multi-source topographic and bathymetric elevation data for New York, Connecticut, Rhode Island and Massachusetts coastal areas.The New England TBDEM integrates over 321 different data sources including topographic and bathymetric LiDAR point clouds, hydrographic surveys, side-scan sonar surveys, and multi-beam surveys obtained from USGS, NOAA, the U.S. Army Corps of Engineers (USACE), Federal Emergency Management Agency (FEMA), and other state and local agencies. The LiDAR and bathymetry 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 data. Because bathymetric data is typically referenced to tidal referenced datums (such as Mean High Water or Mean Low Water), all tidally-referenced heights were transformed into orthometric heights that are normally used for mapping elevation on land (based on the North American Vertical Datum of 1988). The spatial resolution is 1 meter and includes the coastal areas of New York, Connecticut, Rhode Island, and Massachusetts. The temporal range of the input topography and bathymetry is 1887 to 2016. As a collaboration between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program (CMGP), the National Geospatial Program (NGP), and the NOAA National Centers for Environmental Information (NCEI), the CoNED Applications Project integrates disparate light detection and ranging (LiDAR) and bathymetric data sources into a common 3D database aligned both vertically and horizontally to a common reference system. CoNED Project TBDEM elevation model development is focused in select regions around the U.S. Coast, such as in the Northern Gulf of Mexico (NGOM), the Hurricane Sandy Region, the San Francisco Bay Region, the Pacific Northwest, and the North Slope of Alaska. CoNED Project topobathymetric elevation model (TBDEM) 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 also to analyze the impact of various climate change scenarios on coastal regions. The raster elevation topobathymetric elevation product, the Federal Geographic Data Committee (FGDC) metadata, and the spatially referenced metadata are contained in the downloadable bundle. Spatially referenced metadata are contained within an ESRI geodatabase that contains footprints for each of the source input areas. The National Map provides basic elevation information for earth science studies and mapping applications in the United States. The data are utilized by the scientific and resource management communities for global change research, hydrologic modeling, resource monitoring, and mapping and visualization applications. References: USGS Butman, Bradford, Valentine, P.C., Middleton, T.J., and Danforth, W.W., 2007, A GIS Library of multibeam data for Massachusetts Bay and the Stellwagen Bank National Marine Sanctuary, Offshore of Boston, Massachusetts: U.S. Geological Survey Data Series 99, DVD-ROM. Gesch, D.B., 2007, The National Elevation Dataset, in Maune, D., ed., Digital Elevation Model Technologies and Applications: The DEM Users Manual, 2nd Edition, in Digital Elevation Model Technologies and Applications: The DEM Users Manual, 2nd Edition, Bethesda, Maryland, American Society for Photogrammetry and Remote Sensing, p. 99-118. 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 initiative-A call for action: U.S. Geological Survey Circular 1399, 35 p. Winters, W.J., Lorenson, T.D., and Paull, C.K., eds., 2007, Initial Report of the IMAGES VIII/PAGE 127 Gas Hydrate and Paleoclimate Cruise on the RV Marion Dufresne in the Gulf of Mexico, 2-18 July 2002: U.S. Geological Survey Open-File Report 2004-1358, one DVD, online at http://pubs.usgs.gov/of/2004/1358/ USGS - Woods Hole Coastal and Marine Science Center Barnhardt, Walter A., Andrews, Brian, D., and Butman, Bradford, 2005, High-Resolution Geologic Mapping of the Inner Continental Shelf: Nahant to Gloucester, Massachusetts: U.S. Geological Survey Open-File Report 2005-1293, online at http://woodshole.er.usgs.gov/pubs/of2005-1293/ McMullen, K.Y., Poppe, L.J., Signell, R.P., Denny, J.F., Crocker, J.M., Beaver, A.L., and Schattgen, P.T., 2006, Surficial Geology in Central Narragansett Bay, Rhode Island: Interpretations of Sidescan Sonar and Multibeam Bathymetry: U.S. Geological Survey Open-File Report 2006-1199, online at http://woodshole.er.usgs.gov/pubs/of2006-1199/ Poppe, Lawrence J., Ackerman, Seth D., Doran, Elizabeth F., Moser, Marc, S., Stewart, Helen, F., Forfinski, Nicholas A., Gardner, Uther, L., and Keene, Jennifer A., 2006, Geologic Interpretation and Multibeam Bathymetry of the Sea floor in Southeastern Long Island Sound: U.S. Geological Survey Open-File Report 2006-1059, online at http://woodshole.er.usgs.gov/pubs/of2006-1059/ Poppe, Lawrence J., Ackerman, Foster, David, S., Blackwood, Dann, S., Butman, Bradford, Moser, S.K., and Stewart, H.F., 2006, Sea-Floor Character and Surface Processes in the Vicinity of Quicks Hole, Elizabeth Islands, Massachusetts: U.S. Geological Survey Open-File Report 2006-1357, online at http://woodshole.er.usgs.gov/pubs/of2006-1357/ McMullen, K.Y., Poppe, L.J., Twomey, E.R., Danforth, W.W., Haupt, T.A., and Crocker, J.M., 2007, Sidescan-Sonar Imagery, Multibeam Bathymetry, and Surficial Geologic Interpretations of the Sea Floor in Rhode Island Sound, off Sakonnet Point, Rhode Island: U.S. Geological Survey Open-File Report 2007-1150, online at http://woodshole.er.usgs.gov/pubs/of2007-1150/ McMullen, K.Y., Poppe, L.J., Denny, J.F., Haupt, T.A., and Crocker, J.M., 2007, Sidescan-Sonar Imagery and Surficial Geologic Interpretations of the Sea Floor in Central Rhode Island Sound: U.S. Geological Survey Open-File Report 2007-1366, online at http://woodshole.er.usgs.gov/pubs/of2007-1366/ Poppe, Lawrence J., Ackerman, Foster, David, S., Blackwood, Dann, S., Williams, Jeffress, S., Moser, M.S., Stewart, H.F., and Glomb, K.A., 2007, Sea-Floor Character and Sedimentary Processes of Great Round Shoal Channel, Offshore Massachusetts: U.S. Geological Survey Open-File Report 2007-1138, online at http://woodshole.er.usgs.gov/pubs/of2007-1138/ McMullen, K.Y., Poppe, L.J., Haupt, T.A., and Crocker, J.M., 2008, Sidescan-Sonar Imagery and Surficial Geologic Interpretations of the Sea Floor in Western Rhode Island Sound: U.S. Geological Survey Open-File Report 2008-1181, online at http://woodshole.er.usgs.gov/pubs/of2008-1181/ Poppe, L.J., McMullen, K.Y., Foster, D.S., Blackwood, D.S., Williams, S.J., Ackerman, S.D., Barnum, S.R., and Brennan, R.T., 2008, Sea-Floor Character and Sedimentary Processes in the Vicinity of Woods Hole, Massachusetts: U.S. Geological Survey Open-File Report 2008-1004, online at http://woodshole.er.usgs.gov/pubs/of2008-1004/ Poppe, L.J., Ackerman, S.D., McMullen, K.Y., Schattgen, P.T., Schaer, J.D., and Doran, E.F., 2008, Interpolation of Reconnaissance Multibeam and Single-Beam Bathymetry Offshore of Milford, Connecticut: U.S. Geological Survey Open-File Report 2008-1146, online at http://woodshole.er.usgs.gov/pubs/of2008-1146/ EAARL Wright, C.W., Kranenburg, C.J., Klipp, E.S., Troche, R.J., Fredericks, Xan, Masessa, M.L., and Nagle, D.B., 2014, EAARL-B coastal topography-Fire Island, New York, pre-Hurricane Sandy, 2012; seamless (bare earth and submerged): U.S. Geological Survey Data Series 888, http://dx.doi.org/10.3133/ds888 The data obtained through Earth Explorer, http://earthexplorer.usgs.gov, and The National Map Viewer, http://nationalmap.gov/viewer.html, is considered to be the "best available" data from the USGS. For questions on distribution, please refer to the Distribution Section, Contact Information. For processing, please see Data Quality Section, Processing Step, and Contact Information. 18870103 20160201 ground condition Complete As needed -74.786924 -69.761458 42.79872 40.377544 ISO 19115 Topic Category elevation None location imagery Base Maps Earth Cover 013 DTM USGS 3DEP-Coastal Zone Bathymetry Acoustic Sonar Digital Elevation Model Bathymetric 3D Elevation Program CZ Hydrologic Modeling Light Detection and Ranging CoNED CMGP 3DEP 3DEP-CZ LiDAR Topobathy U.S. Geological Survey Hydrologic Coastal National Elevation Database Topobathymetric Digital Terrain Model Coastal Marine and Geology Program DEM Coastal Zone American Society of Photogrammetry and Remote Sensing National Standards for Spatial Digital Accuracy Geographic Names Information System County of Tolland County of Fairfield County of Queens County of Barnstable County of Putnam County of Providence County of Westchester County of Bristol County of Hartford County of New Haven County of Ulster County of Nassau State of Connecticut State of Massachusetts County of Litchfield State of New York County of Orange County of Middlesex County of Bronx County of Newport County of Dutchess County of Norfolk County of Worcester County of New London County of Dukes County of New York County of Suffolk County of Kent County of Windham County of Washington State of Rhode Island County of Plymouth County of Nantucket County of Rockland 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 USA U.S. United States 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 Institute of Standards and Technology NY RI CT ME Any acquisition or use of these data signifies a user's agreement to comprehension and compliance of the USGS Standard Disclaimer. Ensure all portions of metadata are read and clearly understood before using these data in order to protect both user and USGS interests. There is no guarantee or warranty concerning the accuracy of the data. Users should be aware that temporal changes may have occurred since these data were collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. These data should not be used for navigation purposes. Acknowledgement of the originating agencies would be appreciated in products derived from these data. Any user who modifies the data is obligated to describe the types of modifications they perform. User specifically agrees not to misrepresent the data, nor to imply that changes made were approved or endorsed by the USGS. Please refer to http://www.usgs.gov/privacy.html for the USGS disclaimer. U.S. Geological Survey Jeffrey Danielson / Dean Tyler * Physical Geographer mailing and physical

USGS Earth Resources Observation & Science (EROS) Center

Science and Applications Branch

47914 252nd Street

Sioux Falls SD 57198-0001 US 605-594-6148 / 605-594-2624 * 605-594-6589 daniels@usgs.gov / dtyler@usgs.gov * 0800 - 1600 CT, M - F (-6h CST/-5h CDT GMT) Please refer to the Data Quality Section, Source Citations for original source data information. None Unclassified None Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1.4959 Visual inspection Visual inspection The horizontal accuracy for the integrated topobathymetric model was not assessed quantitatively. The vertical accuracy of the input topographic data varies depending on the input source. Because the input elevation data were derived primarily from LiDAR, the vertical accuracy ranges from 15 to 20 centimeters in root mean square error (RMSE). The vertical accuracy for the integrated topobathymetric model was not assessed quantitatively. NOAA, National Geodetic Survey (NGS) 20140901 map ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid12b/data/4800/ onLine 2014 publication date Topobathymetric LiDAR This data set is an LAZ (compressed LAS) format file containing LIDAR point cloud data. These data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using a Riegl VQ820G system. The data were acquired from 20140108 - 20140522 in four missions. U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center Unknown http://pubs.usgs.gov/ds/0888/ onLine 2012 publication date pre-Hurricane Sandy (October 2012 hurricane) EAARLB These remotely sensed, geographically referenced elevation measurements of LiDAR-derived submerged topography datasets were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida. USGS Unknown map http://nationalmap.gov/viewer.html onLine 2011 2014 publication date Topographic LiDAR USGS historical and current 3 Bare-earth DEMs (3D) National Elevation Data. NOAA Digital Coast Unknown https://coast.noaa.gov/dataviewer onLine 2008 2012 publication date New_York_PutnmanCounty, 2008, NOAA 1-meter; Connecticut, Fairfield County, 2010, USGS 1-meter; Connecticut, Litchfield-FairField, 2011, USACE 1-meter; Connecticut Coastline, Post_Sandy, 2012, USACE 1-meter 2012 USACE Post Sandy Topographic LiDAR: Coastal Connecticut - "This data has been acquired and developed by the U.S. Corps of Engineers ST. Louis District to collect and deliver topographic elevation point data derived from multiple return light detection and ranging (LiDAR) measurements for the 116 sq. mile project area encompassing the entire coastal region of the State of Connecticut. Fugro EarthData, Inc. acquired 46 flight lines in 4 lifts from November 14, 2012 to December 16, 2012." Connecticut_Litchfield_FairField_2011_USACE_1m - "The purpose of this LiDAR data was to produce high accuracy 3D elevation products, including tiled LiDAR in LAS 1.2 format, 3D breaklines, and 1 m cell size hydro flattened Digital Elevation Models (DEMs). This data was produced for the U.S. Corp of Engineers and USDA-NRCS Connecticut for use in projects dealing with conservation planning, design, research, floodplain mapping, dam safety assessments, and hydrologic modeling." Collected 20111213 to 20111219. LiDAR Elevation Data Collection - Putnam County, NY, 2008 (NYSDEC) - "Summary of the surface elevation data collection project in Putnam County, NY (NYSDEC) 2008. Products generated include LiDAR point data in LAS Binary format v1.1. In the spring of 2008, The Sanborn Map Company, Inc. (Sanborn) acquired 111 square miles of terrestrial LiDAR data in Putnam County, NY. An Optech ALTM 2050 Airborne LiDAR sensor was used for the collection. The LiDAR data associated with this metadata file is in LAS binary format, version 1.1." NOAA Digital Coast Unknown https://coast.noaa.gov/dataviewer/#/ onLine 2006 2011 publication date FEMA Topographic LiDAR: Connecticut Coastline Survey, 2006, 1-meter; FEMA Massachusetts-New_Hampshire, Merrimack, 2011, 1-meter FEMA Topographic LiDAR NOAA, National Centers for Environmental Information (NCEI) Unknown http://www.ngdc.noaa.gov/mgg/bathymetry/relief.html ; http://maps.ngdc.noaa.gov/viewers/bathymetry/ onLine 1887 2013 publication date Bathymetry Multiple Data; D00102; D00111; D00149; F00321; F00323; F00325; F00340; F00341; F00364; F00365; F00367; F00375; F00376; F00378; F00379; F00406; F00411; F00491; F00522; F00545; F00550; F00559; H01802; H04797; H05045; H05141; H05223; H05341; H05342; H05343; H05343; H05400; H05401; H05543; H05553; H05588; H05589; H05610; H05621; H05622; H05623; H05628; H05629; H05630; H05670; H05733; H05734; H05880; H05881; H05882; H06123; H06124; H06125; H06330; H06348; H06349; H06350; H06442; H06443; H06444; H06445; H06446; H06468; H06469; H06470; H06471; H06472; H06473; H06533; H06534; H06561; H06562; H06563; H06642; H06643; H06668; H06859; H06863; H06970; H06995; H07060; H07061; H07062; H07063; H07066; H07159; H07640; H07715; H07724; H07841; Bathymetry, 1887 to 2013, NOAA, National Centers for Environmental Information NOAA Digital Coast 2013 https://coast.noaa.gov/htdata/lidar1_z/geoid12a/data/3664/ onLine 2013 publication date USACE Topobathy Lidar: Long Island, New York, 2013 Topobathymetric LiDAR U.S. Geological Survey, Customer Service Representative 2015 raster digital data https://lta.cr.usgs.gov/coned_tbdem onLine 2015 publication date USGS Topobathy 2015, 1-Meter CoNED 1-Meter Topobathymetric Elevation Model (TBDEM) Woods Hole Coastal and Marine Science Center Unknown http://woodshole.er.usgs.gov/pubs/ ; * http://pubs.usgs.gov/of/ onLine Unknown publication date Bathymetry Bathymetry from Woods Hole Coastal and Marine Science Center, Woods Hole, Massachusetts , U.S. Geological Survey, Coastal and Marine Geology Program NOAA's National Centers for Environmental Information (NCEI) 2016 http://www.ngdc.noaa.gov/mgg/inundation/sandy/sandy_geoc.html onLine 2016 publication date Topobathy NOAA's National Centers for Environmental Information (NCEI) has developed a suite of digital elevation models (DEMs) of the U.S. Atlantic Coast impacted by Hurricane Sandy in October 2012. These DEMs are the initial part of a planned framework for a seamless depiction of merged bathymetry and topography along U.S. coasts. The principal methodology for developing the integrated topobathymetric elevation model can be organized into three main components. The "topography component" consists of the land-based elevation data, which is primarily comprised from high-resolution 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 boats rather than bathymetry acquired from LiDAR. The most common forms of bathymetry that are used include: 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) 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 end product 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 NAVD88 and NAD83, UTM. If the source data is not NAVD88, transform the input LiDAR data to NAVD88 reference frame using current National Geodetic Survey (NGS) geoid models. Likewise, if required, convert the input source data to NAD83 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) 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 3-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 Root Mean Square Error (RMSE). 20160404 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 is 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 spatial 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 (Root Mean Square Error) 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. 20160411 Mosaic Dataset Processing (Integration) Component: a) Determined priority of input data based on project characteristics, including acquisition dates, cell size, retention of features, water surface treatment, visual inspection and presence of artifacts. b) Develop an ArcGIS geodatabase (Mosaic Dataset) and spatial seamlines for each individual topographic (minimum convex hull boundary) and bathymetric raster layer included in the integrated elevation model. c) Generalize seamline edges to smooth transition boundaries between neighboring raster layers and split complex raster datasets with isolated regions into individual unique raster groups. d) Develop an integrated shoreline transition zone from the best available topographic and bathymetric data to blend the topographic and bathymetric elevation sources. Where feasible, use the minimum convex hull boundary, create a buffer to logically mask input topography/bathymetry data. Then, through the use of TINs, interpolate the selected topographic and bathymetric points to gap-fill, if required any near-shore holes in the bathymetric coverage. Topobathymetric LiDAR data sources such as the EAARL-B or CZMIL systems provide up-to-date, high-resolution data along the critical land/water interface within inter-tidal zone. e) Prioritize and spatially sort the input topographic and bathymetric raster layers based on date of acquisition and accuracy to sequence the raster data in the integrated elevation model. f) Based on the prioritization, spatially mosaic the input raster data sources to create a seamless topobathymetric composite at a cell size of 3 meters using blending (spatial weighting). g) Performed a visual quality assurance (Q/A) assessment on the output composite to review the mosaic seams for artifacts. h) Generate spatially referenced metadata for each unique data source. The spatially reference metadata consists of a group of geospatial polygons that represent the spatial footprint of each data source used in the generation of the topobathymetric dataset. Each polygon is to be populated with 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, bathymetric LiDAR, multi-beam bathymetry, single-beam bathymetry, etc.). 20160418 U.S. Geological Survey Jeffrey Danielson / Dean Tyler * Physical Geographer mailing and physical

47914 252nd Street

USGS Earth Resources Observation & Science (EROS) Center

Science and Applications Branch

Sioux Falls SD 57198-0001 US 605-594-6148 / 605-594-2624 * 605-594-6589 daniels@usgs.gov / dtyler@usgs.gov * 0800 - 1600 CT, M - F (-6h CST/-5h CDT GMT) Data were received from USGS by NOAA and ingested into the Digital Coast system for download via custom processing and ftp. Metadata was modified to reflect distribution through this mechanism. 20170301 NOAA Office for Coastal Management (OCM) mailing and physical

2234 South Hobson Ave.

Charleston SC 29405-2413 843-740-1202 coastal.info@noaa.gov Raster Grid Cell 411192 204107 1 Universal Transverse Mercator 18 0.999600 -75.000000 0.000000 500000.000000 0.000000 coordinate pair 1.000000 1.000000 meters North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 North American Vertical Datum of 1988 1.000000 meters Implicit coordinate This collection of high-resolution coastal elevation data is available in a user-friendly Georeferenced Tagged Image File Format (GeoTIFF). The elevation model has floating point numeric values. Areas where data is incomplete due to lack of full image coverage or NoData are represented with the numeric value of -3.40282346639e+038. Spatially referenced metadata are contained within an ESRI vector shapefile that contains footprints with accompanying attribute fields for each of the source input areas. None NOAA Office for Coastal Management mailing and physical

2234 South Hobson Avenue

Charleston SC 29405-2413 843-740-1202 coastal.info@noaa.gov Downloadable Data Although these data have been processed successfully on a computer system at the USGS, no warranty expressed or implied is made by the USGS regarding the use of the data on any other system, nor does the act of distribution constitute any such warranty. Data may have been compiled from various outside sources. Spatial information may not meet National Map Accuracy Standards. This information may be updated without notification. The USGS, NOAA, NOAA OCM and it partners shall not be liable for any activity involving these data, installation, fitness of the data for a particular purpose, its use, or analyses results. This data can be obtained on-line at the following URL: https://coast.noaa.gov/dataviewer/#/lidar/search/where:ID=6194 20170303 NOAA Office for Coastal Management mailing and physical

2234 South Hobson Avenue

Charleston SC 29405-2413 843-740-1202 coastal.info@noaa.gov FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998