This dataset contains a bare-earth digital elevation model (DEM) for Northampton and Accomack Counties, Virginia based on data collected March 25-30, 2010 and processed to yield bare-earth elevations. It was created using LiDAR by Sanborne Geosystems under a contract with the Virginia Information Technologies Agency (VITA) with funding from The Nature Conservancy, USGS and the Virginia Coast Reserve Long-term Ecological Research project of the University of Virginia. Original LiDAR point data (approximately 1 meter spacing) was used to create a digital elevation model (DEM) with a cell resolution of 10 ft. (3.048 m). The DEM data layer is in the State Plane coordinate system (U.S. Feet) and uses the NAVD88 vertical datum with the 2009 Geoid for elevation in feet. As detailed in the included quality report, elevations are accurate to 0.65 feet or better. Water areas have been hydroflattened and may also include salt marsh areas that were inundated at the time of the flights. As a result, water areas were given a default minimum elevation below the minimum elevation measured by LiDAR over a given area and dependent on tidal cycle. Areas at or below this minimum elevation within the water mask may include salt marsh and tidal flats as well as open water. The elevation of the hydroflattening varies spatially. Salt marsh areas within the water mask were later determined by VCRLTER staff based on the following factors: (1) present as marsh (code 18) in the NOAA CCAP 2006 land cover layer and not included as an open water feature in the 2010 USGS National Hydrography Dataset, (2) minimum contiguous area of 1800 square meters, approximately equal to two 30 meter resolution CCAP pixel cells, and (3) includes extensive areas of salt marsh within north-south flight line “stripesâ€, primarily the seaside lagoons and marshes south of Parramore Island and the town of Wachapreague plus Chesapeake Bay marshes immediately north of Tangier Island (and excludes edge-only areas elsewhere). Two polygon shapefiles have been added to this dataset: one shapefile shows the region-specific water masks and includes the elevation of the masks (in meters, not feet); the other shapefile shows areas of saltmarsh hidden within the water mask and includes a recommended replacement elevation (0.404 meters) based on the average above-water-mask LiDAR elevations of all CCAP-minus-NHD-water-determined marshes of all seaside marshes south of Chincoteague Inlet. The two polygon shapefiles have been reprojected to the WGS84 UTM zone 18N coordinate system, and the NAVD88 vertical elevations converted from feet to meters.

This dataset is a digital elevation model (DEM) of the beach topography of Lake Superior at Minnesota Point, Duluth, Minnesota. The DEM has a 1-meter (m; 3.28084 foot [ft]) cell size and was created from a LAS dataset of terrestrial light detection and ranging (LiDAR) data with an average point spacing of 0.137 m (0.45 ft). LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019).

This dataset is a LAS (industry-standard binary format for storing lidar point clouds) dataset containing light detection and ranging (lidar) data and sonar data representing the beach and near-shore bathymetry of Lake Superior at Minnesota Point, near the Duluth entry, Duluth, Minnesota. Average point spacing of the LAS files in the dataset are as follows: lidar, 0.055 meters (m); multibeam sonar, 0.511 m; single-beam sonar, 1.687 m. The LAS dataset was used to create digital elevation models (DEMs) of 10 m (32.8084 feet) and 1 m (3.28084 feet) cell size, of the approximate 1.78 square kilometer surveyed area. Lidar data were collected November 01, 2022 using a boat mounted Velodyne VLP-16 unit and methodology similar to that described by Huizinga and Wagner (2019). Multibeam sonar data were collected October 31-November 01, 2022 using a Norbit integrated wide band multibeam system compact (iWBMSc) sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected November 01, 2022 using a Ceescope echosounder and methodology similar to that described by Wilson and Richards (2006). This project followed similar methods to that of Wagner, Lund, and Sanks (2020), who completed a similar survey in 2019.

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated bathymetric-topographic DEMs are used to support tsunami forecasting and modeling efforts at the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory (PMEL). The DEMs are part of the tsunami forecast system SIFT (Short-term Inundation Forecasting for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers, and are used in the MOST (Method of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation, and inundation. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the Canadian Hydrographic Service (CHS), the Puget Sound Lidar Consortium (PSLC), the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX), Canadian Digital Elevation Data (CDED) and other international, federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datums of Mean High Water (MHW) and North American Vertical Datum of 1988 (NAVD 88) and horizontal datum of World Geodetic System 1984 (WGS 84). Grid spacings for the DEMs range from 1/3 arc-second (~10 meters) to 3 arc-seconds (~30 meters).The DEM Global Mosaic is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), along with the global GEBCO_2014 grid: http://www.gebco.net/data_and_products/gridded_bathymetry_data. NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service is a general-purpose global, seamless bathymetry/topography mosaic. It combines DEMs from a variety of near sea-level vertical datums, such as mean high water (MHW), mean sea level (MSL), and North American Vertical Datum of 1988 (NAVD88). Elevation values have been rounded to the nearest meter, with DEM cell sizes going down to 1 arc-second. Higher-resolution DEMs, with greater elevation precision, are available in the companion NAVD88: http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042 and MHW: http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799 mosaics. By default, the DEMs are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Please see NCEI's corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. In this visualization, the elevations/depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png.A map service showing the location and coverage of land and seafloor digital elevation models (DEMs) available from NOAA's National Centers for Environmental Information (NCEI). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. Layers available in the map service: Layers 1-4: DEMs by Category (includes various DEMs, both hosted at NCEI, and elsewhere on the web); Layers 6-11: NCEI DEM Projects (DEMs hosted at NCEI, color-coded by project); Layer 12: All NCEI Bathymetry DEMs (All bathymetry or bathy-topo DEMs hosted at NCEI).This is an image service providing access to bathymetric/topographic digital elevation models stewarded at NOAA's National Centers for Environmental Information (NCEI), with vertical units referenced to mean high water (MHW). NCEI builds and distributes high-resolution, coastal digital elevation models (DEMs) that integrate ocean bathymetry and land topography to support NOAA's mission to understand and predict changes in Earth's environment, and conserve and manage coastal and marine resources to meet our Nation's economic, social, and environmental needs. They can be used for modeling of coastal processes (tsunami inundation, storm surge, sea-level rise, contaminant dispersal, etc.), ecosystems management and habitat research, coastal and marine spatial planning, and hazard mitigation and community preparedness. This service provides data from many individual DEMs combined together as a mosaic. By default, the rasters are drawn in order of cell size, with higher-resolution grids displayed on top of lower-resolution grids. If overlapping DEMs have the same resolution, the newer one is shown. Alternatively, a single DEM or group of DEMs can be isolated using a filter/definition query or using the 'Lock Raster 'mosaic method in ArcMap. This is one of three services displaying collections of DEMs that are referenced to common vertical datums: North American Vertical Datum of 1988 (NAVD88): http://noaa.maps.arcgis.com/home/item.html?id=e9ba2e7afb7d46cd878b34aa3bfce042, Mean High Water (MHW): http://noaa.maps.arcgis.com/home/item.html?id=3bc7611c1d904a5eaf90ecbec88fa799, and Mean Higher High Water: http://noaa.maps.arcgis.com/home/item.html?id=9471f8d4f43e48109de6275522856696. In addition, the DEM Global Mosaic is a general-purpose global, seamless bathymetry/topography mosaic containing all the DEMs together. Two services are available: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff Elevation Values: http://noaa.maps.arcgis.com/home/item.html?id=c876e3c96a8642ab8557646a3b4fa0ff and Color Shaded Relief: http://noaa.maps.arcgis.com/home/item.html?id=feb3c625dc094112bb5281c17679c769. Please see the corresponding DEM Footprints map service: http://noaa.maps.arcgis.com/home/item.html?id=d41f39c8a6684c54b62c8f1ab731d5ad for polygon footprints and more information about the individual DEMs used to create this composite view. This service has several server-side functions available. These can be selected in the ArcGIS Online layer using 'Image Display ', or in ArcMap under 'Processing Templates '. None: The default. Provides elevation/depth values in meters relative to the NAVD88 vertical datum. ColorHillshade: An elevation-tinted hillshade visualization. The depths are displayed using this color ramp: http://gis.ngdc.noaa.gov/viewers/images/dem_color_scale.png. GrayscaleHillshade: A simple grayscale hillshade visualization. SlopeMapRGB: Slope in degrees, visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/SlopeMapLegend_V7b.png. SlopeNumericValues: Slope in degrees, returning the actual numeric values. AspectMapRGB: Orientation of the terrain (0-360 degrees), visualized using these colors: http://downloads.esri.com/esri_content_doc/landscape/AspectMapLegendPie_V7b.png. AspectNumericValues: Aspect in degrees, returning the actual numeric values.

This dataset contains a series of high resolution raster Digital Elevation Models (DEM) (1m resolution) around the coastal perimeter of Torres Strait community islands (Badu, Boigu, Dauan, Erub, Hammond, Iama, Mabuiag, Masig, Mer, Moa, Poruma, Saibai, Ugar, Warraber). This dataset was developed for the purpose of mapping levels of coastal inundation under different sea level rise and storm tide scenarios. To enable the creation of maps of the various scenarios from the DEM the Highest Astronomical Tide (HAT) and storm surge values for 1yr, 100yr and 1000yr Annual Return Interval (ARI) relative to the Mean Sea Level (MSL) for each island were compiled from Harper (2011). These height thresholds are provided in spreadsheet format.

The DEM dataset was produced predominantly from LiDAR (light detection and ranging) surveys taken in 2011 and provided to the Torres Strait Regional Authority (TSRA) by the Department of Natural Resources and Mines, Queensland Government.

LiDAR data is a remote sensing technology that measures distance by illuminating a target with a laser and analysing the reflected light. For the Torres Strait region LiDAR aircraft were used to collect height values above sea level to gain a very accurate and detailed coverage of the terrain of the islands captured.

The data captured was then modelled using ArcMap software to calculate a DEM for each island. Due to the large size of some of the islands only areas subject to inundation were processed and included in this dataset. The XYZ LiDAR data was captured and grouped into 1x1km tiles. These 1x1km areas were then merged to follow the coastline of each island from 1 data file for small islands, such as Masig through to 49 files for large islands such as Saibai. The entire dataset is made up from 112 separate DEM files. The XYZ data was converted to TIN files, then transformed from TIN to a DEM raster. The DEM raster has a projection of GDA94 / MGA Zone 55.

The height datum used in this dataset is the Australian Height Datum (AHD) which approximates to Mean Sea Level (MSL). Height datums in the Torres Strait have been unofficially revised by DERM from a Spatial Infrastructure Audit that was conducted in 2011.

The raster files are intended to be displayed by classifying different levels of coastal inundation as specified in Harper (2011). Each island has a different conversions between MSL to HAT and storm surge levels. These must be applied appropriately to the DEM of each island in order to assess the potential inundation hazards.

Limitations:

The LiDAR used to create the DEM did not measure heights below the level of the water at the time that the measurements were taken. As a result the DEM cuts off at the level of the tide when the LiDAR was taken. For some islands the DEM goes down to below the Mean Sea Level (MSL), while in others it only goes down to the MSL+0.6m. This makes this dataset unsuitable for investigating low tide effects. In addition to this the DEM is not clipped to the coastline and so areas that were covered in water the DEM shows an interpolation between the heights of closest neighbouring coastline (due to the TIN process). This must be considered when using this dataset for a purpose other than looking at high tide conditions.

In this dataset most of the base data was from LiDAR data. However for the Moa communities of Saint Pauls and Kubin no LiDAR data was available and so datasets developed by Dr Kevin Parnell from Schlenker Orthophotography were used instead. This data that was captured in 1999. This data is not as accurate as LiDAR data and this should be kept in mind when analysing these areas. A tender has been released for capture of LiDAR data for Saint Pauls and Kubin to occur in 2014.

References:

Harper Bruce, Mason Luciano, Botev Ivan, Smith Mitchell, Callaghan Jeff (2011). "Torres Strait Extreme Water Level Study". Systems Engineering Australia Pty Ltd. Accessible from http://www.tsra.gov.au/_data/assets/pdf_file/0006/2004/tsewls_finalreport_lowres.pdf

description: LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser range finding, GPS positioning and inertial measurement technologies; LIDAR instruments are able to make highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures and vegetation. Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, 262 flight lines of high density (submeter ground sample distance) data were collected over areas in Bay, Calhoun, Jackson and Washington Counties in Florida. This data set was collected at the same time as the collection for Jefferson County, FL. Collectively, these data sets cover approximately 1201 square miles. The data acquisition occurred in 17 missions between February 22, 2007 and March 13, 2007. Multiple returns were recorded for each laser pulse along with an intensity value for each return. This data was collected at sub-meter resolution to provide average point spacing of 0.7 m for collected points. Up to 5 returns were recorded for each pulse in addition to an intensity value.; abstract: LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser range finding, GPS positioning and inertial measurement technologies; LIDAR instruments are able to make highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures and vegetation. Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, 262 flight lines of high density (submeter ground sample distance) data were collected over areas in Bay, Calhoun, Jackson and Washington Counties in Florida. This data set was collected at the same time as the collection for Jefferson County, FL. Collectively, these data sets cover approximately 1201 square miles. The data acquisition occurred in 17 missions between February 22, 2007 and March 13, 2007. Multiple returns were recorded for each laser pulse along with an intensity value for each return. This data was collected at sub-meter resolution to provide average point spacing of 0.7 m for collected points. Up to 5 returns were recorded for each pulse in addition to an intensity value.

The 2006 OSIP bare-earth Digital Elevation Model (DEM) was derived from digital LiDAR data was collected during the months of March and May (leaf-off conditions). The DEM data covers the entire land area of the northern tier of Ohio (approximately 23,442 square miles. The DEM is delivered in county sets, consisting of 5,000' x 5,000' size tiles that correspond to the tile sizes for the OSIP 1FT imagery products. Where the State borders other states (land only), the entire border of the State is buffered by at least 1,000-feet. Along the Lake Erie Shoreline ortho coverage is buffered beyond the shoreline a minimum distance of 2,500-feet. The file naming convention is as follows: Nxxxxyyy = 5,000' x 5,000' Tiles located in the Ohio State Plane Coordinate System (North Zone). Sxxxxyyy = 5,000' x 5,000' Tiles located in the Ohio State Plane Coordinate System (South Zone). Please note that xxxx and yyy represent the easting and northing coordinates (respectively) in state plane feet, The naming convention for each tile is based upon (the bottom most-left pixel). The full county mosaic is an aggregation of the tiles by county. The mosaic is devloped in the Ohio State Plane Coordinate System (North Zone).. The DEM tiles were provided in ESRI ArcINFO GRID raster and ASCII grid formats, with only the LiDAR in LAS Format containing the above ground and bare-earth LiDAR features. Ownership of the data products resides with the State of Ohio. Orthophotography and ancillary data products produced through this contract are public domain data. The LiDAR used to generate the DEM was acquired Statewide to provide a solid and very accurate base to use during the image rectification process. This same LiDAR can be supplemented with 3D breaklines to generate 2-foot and/or 4/5-foot contours. The average post spacing between LiDAR points is 7-feet. The flying altitude was 7,300-feet AMT, with the targeted flying speed at 170 knots.

Indiana's Statewide Lidar data is produced at 1.5-meter average post spacing for all 92 Indiana Counties covering more than 36,420 square miles. New Lidar data was captured except where previously captured Lidar data exists, or the participating County bought-up to a higher resolution of 1.0-meter average post spacing Lidar data. Existing Lidar data exists for: Porter, Steuben, Noble, De Kalb, Allen, Madison, Delaware, Hendricks, Marion, Hancock, Morgan, Johnson, Shelby, Monroe, and portions of Vermillion, Parke, Vigo, Clay, Sullivan, Knox, Gibson, and Posey. These existing Lidar datasets were seamlessly integrated into this new statewide dataset. From this seamless Lidar product a statewide 5-foot post spacing hydro-flattened DEM product was created and is also available. See the FGDC Metadata provided for more details.

This statewide project is divided into three geographic areas captured over a 3-year period (2011-2013):
Area 1 (2011) Indiana central counties: St. Joseph, Elkhart, Starke, Marshall, Kosciusko, Pulaski, Fulton, Cass, Miami, Wabash, Carroll, Howard, Clinton, Tipton, Boone, Hendricks, Marion, Morgan, Johnson, Monroe, Brown, Bartholomew, Lawrence, Jackson, Orange, Washington, Crawford, and Harrison.

Area 2 (2012) Indiana eastern counties: LaGrange, Steuben, Noble, DeKalb, Whitley, Allen, Huntington, Wells, Adams, Grant, Blackford, Jay, Hamilton, Madison, Delaware, Randolph, Hancock, Henry, Wayne, Shelby, Rush, Fayette, Union, Decatur, Franklin, Jennings, Ripley, Dearborn, Ohio, Scott, Jefferson, Switzerland, Clark, and Floyd.

Area 3 (2013) Indiana western counties: Lake, Porter, LaPorte, Newton, Jasper, Benton, White, Warren, Tippecanoe, Fountain, Montgomery, Vermillion, Parke, Putnam, Vigo, Clay, Owen, Sullivan, Greene, Knox, Daviess, Martin, Gibson, Pike, Dubois, Posey, Vanderburgh, Warrick, Spencer, and Perry.

Funders of OpenTopography Hosting of the Indiana Statewide Lidar and DEM data: USDA NRCS, Indiana, ISPLS Foundation, Indiana Geographic Information Office, Indiana Office of Technology, Indiana Geological Survey, Surdex Corporation, Vectren Energy Delivery, Indiana, Woolpert, Inc., and Individual IGIC Member Donations from Jim Stout, Jeff McCann, Cele Morris, Becky McKinley, Phil Worrall, and Andy Nicholson.

To explore a web map of topographic differencing for the entire state of Indiana click here

Indiana's Statewide Lidar data is produced at 1.5-meter average post spacing for all 92 Indiana Counties covering more than 36,420 square miles. New Lidar data was captured except where previously captured Lidar data exists, or the participating County bought-up to a higher resolution of 1.0-meter average post spacing Lidar data. Existing Lidar data exists for: Porter, Steuben, Noble, De Kalb, Allen, Madison, Delaware, Hendricks, Marion, Hancock, Morgan, Johnson, Shelby, Monroe, and portions of Vermillion, Parke, Vigo, Clay, Sullivan, Knox, Gibson, and Posey. These existing Lidar datasets were seamlessly integrated into this new statewide dataset. From this seamless Lidar product a statewide 5-foot post spacing hydro-flattened DEM product was created and is also available. See the FGDC Metadata provided for more details.

This statewide project is divided into three geographic areas captured over a 3-year period (2011-2013):
Area 1 (2011) Indiana central counties: St. Joseph, Elkhart, Starke, Marshall, Kosciusko, Pulaski, Fulton, Cass, Miami, Wabash, Carroll, Howard, Clinton, Tipton, Boone, Hendricks, Marion, Morgan, Johnson, Monroe, Brown, Bartholomew, Lawrence, Jackson, Orange, Washington, Crawford, and Harrison.

Area 2 (2012) Indiana eastern counties: LaGrange, Steuben, Noble, DeKalb, Whitley, Allen, Huntington, Wells, Adams, Grant, Blackford, Jay, Hamilton, Madison, Delaware, Randolph, Hancock, Henry, Wayne, Shelby, Rush, Fayette, Union, Decatur, Franklin, Jennings, Ripley, Dearborn, Ohio, Scott, Jefferson, Switzerland, Clark, and Floyd.

Area 3 (2013) Indiana western counties: Lake, Porter, LaPorte, Newton, Jasper, Benton, White, Warren, Tippecanoe, Fountain, Montgomery, Vermillion, Parke, Putnam, Vigo, Clay, Owen, Sullivan, Greene, Knox, Daviess, Martin, Gibson, Pike, Dubois, Posey, Vanderburgh, Warrick, Spencer, and Perry.

Funders of OpenTopography Hosting of the Indiana Statewide Lidar and DEM data: USDA NRCS, Indiana, ISPLS Foundation, Indiana Geographic Information Office, Indiana Office of Technology, Indiana Geological Survey, Surdex Corporation, Vectren Energy Delivery, Indiana, Woolpert, Inc., and Individual IGIC Member Donations from Jim Stout, Jeff McCann, Cele Morris, Becky McKinley, Phil Worrall, and Andy Nicholson.

To explore a web map of topographic differencing for the entire state of Indiana click here