This data set contains aggregated topographic ranges, radii, and related data along each observational pass during which Clementine LIDAR laser range data were acquired. The data were created using preliminary spacecraft timing, orientation, and orbital solutions. The laser ranges have been converted from counts to meters using a calibration factor of 39.972 m per count. Timing information may have substantial errors owing to spacecraft computer resets and clock ambiguity. The lidar electronics triggered on photon pulses continuously, and recorded up to four pulses within a programmable range window. The last trigger before and the first trigger after the range window were also recorded. Usually, but not always, the first trigger within the range window was the valid range. For a few laser shots, multiple pulses were detected within the expected time interval for lunar reflections.

The Oahu, Hawaii Elevation Data Task Order involves collecting and delivering topographic elevation point data derived from multiple return light detection and ranging (LiDAR) measurements on the island of Oahu in Hawaii. The Statement of Work (SOW) for the area covering the northern 2/3 of Oahu was developed by the National Oceanic and Atmospheric Administration's (NOAA) Office for Coastal Ma...

If you are interested in obtaining a copy of this data, see LIO Support - Large Data Ordering Instructions. Data can be requested by project area or a set of tiles. To determine which project contains your area of interest or to view single tiles, zoom in on the map above and click. For bulk tile orders follow the link in the Additional Documentation section below to download the tile index in shapefile format. Data sizes by project area are listed below.

The Ontario Point Cloud (Lidar-Derived) consists of points containing elevation and intensity information derived from returns collected by an airborne topographic lidar sensor. The minimum point cloud classes are Unclassified, Ground, Water, High and Low Noise. The data is structured into non-overlapping 1-km by 1-km tiles in LAZ format.

This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters, accuracy and sensors may vary by project. Some project have additional classes, such as vegetation and buildings. See the detailed User Guide and contractor metadata reports linked below for additional information, including information about interpreting the index for placement of data orders.

Raster derivatives have been created from the point clouds. These products may meet your needs and are available for direct download. For a representation of bare earth, see the Ontario Digital Terrain Model (Lidar-Derived). For a model representing all surface features, see the Ontario Digital Surface Model (Lidar-Derived).

You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page.

Additional Documentation

Ontario Classified Point Cloud (Lidar-Derived) - User Guide (DOCX)

OMAFRA Lidar 2016-18 - Cochrane - Additional Metadata (PDF) OMAFRA Lidar 2016-18 - Peterborough - Additional Metadata (PDF) OMAFRA Lidar 2016-18 - Lake Erie - Additional Metadata (PDF) CLOCA Lidar 2018 - Additional Contractor Metadata (PDF) South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Huron - Additional Metadata (PDF) OMAFRA Lidar 2022 - Lake Simcoe - Additional Metadata (PDF) Huron-Georgian Bay Lidar 2022-23 - Additional Metadata (Word) Kawartha Lakes Lidar 2023 - Additional Metadata (Word) Sault Ste Marie Lidar 2023-24 - Additional Metadata (Word) Thunder Bay Lidar 2023-24 - Additional Metadata (Word) Timmins Lidar 2024 - Additional Metadata (Word)

OMAFRA Lidar Point Cloud 2016-18 - Cochrane - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2016-18- Peterborough - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2016-18 - Lake Erie - Lift Metadata (SHP) CLOCA Lidar Point Cloud 2018 - Lift Metadata (SHP) South Nation Lidar Point Cloud 2018-19 - Lift Metadata (SHP) York-Lake Simcoe Lidar Point Cloud 2019 - Lift Metadata (SHP) Ottawa River Lidar Point Cloud 2019-20 - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2022 - Lake Huron - Lift Metadata (SHP) OMAFRA Lidar Point Cloud 2022 - Lake Simcoe - Lift Metadata (SHP) Eastern Ontario Lidar Point Cloud 2021-22 - Lift Medatadata (SHP) DEDSFM Huron-Georgian Bay Lidar Point Cloud 2022-23 - Lift Metadata (SHP) DEDSFM Kawartha Lakes Lidar Point Cloud 2023 - Lift Metadata (SHP) DEDSFM Sault Ste Marie Lidar Point Cloud 2023-24 - Lift Metadata (SHP) DEDSFM Sudbury Lidar Point Cloud 2023-24 - Lift Metadata (SHP) DEDSFM Thunder Bay Lidar Point Cloud 2023-24 - Lift Metadata (SHP) DEDSFM Timmins Lidar Point Cloud 2024 - Lift Metadata (SHP) GTA 2023 - Lift Metadata (SHP)

Ontario Classified Point Cloud (Lidar-Derived) - Tile Index (SHP)

Ontario Lidar Project Extents (SHP)

Data Package Sizes

LEAP 2009 - 22.9 GB

OMAFRA Lidar 2016-18 - Cochrane - 442 GB OMAFRA Lidar 2016-18 - Lake Erie - 1.22 TB OMAFRA Lidar 2016-18 - Peterborough - 443 GB

GTA 2014 - 57.6 GB GTA 2015 - 63.4 GB Brampton 2015 - 5.9 GB Peel 2016 - 49.2 GB Milton 2017 - 15.3 GB Halton 2018 - 73 GB

CLOCA 2018 - 36.2 GB

South Nation 2018-19 - 72.4 GB

York Region-Lake Simcoe Watershed 2019 - 75 GB

Ottawa River 2019-20 - 836 GB

Lake Nipissing 2020 - 700 GB

Ottawa-Gatineau 2019-20 - 551 GB

Hamilton-Niagara 2021 - 660 GB

OMAFRA Lidar 2022 - Lake Huron - 204 GB OMAFRA Lidar 2022 - Lake Simcoe - 154 GB

Belleville 2022 - 1.09 TB

Eastern Ontario 2021-22 - 1.5 TB

Huron Shores 2021 - 35.5 GB

Muskoka 2018 - 72.1 GB Muskoka 2021 - 74.2 GB Muskoka 2023 - 532 GB The Muskoka lidar projects are available in the CGVD2013 or CGVD28 vertical datums. Please specifify which datum is needed when ordering data.

Digital Elevation Data to Support Flood Mapping 2022-26:

Huron-Georgian Bay 2022 - 1.37 TB Huron-Georgian Bay 2023 - 257 GB Huron-Georgian Bay 2023 Bruce - 95.2 GB Kawartha Lakes 2023 - 385 GB Sault Ste Marie 2023-24 - 1.15 TB Sudbury 2023-24 - 741 GB Thunder Bay 2023-24 - 654 GB Timmins 2024 - 318 GB

GTA 2023 - 985 GB

Status On going: Data is continually being updated

Maintenance and Update Frequency As needed: Data is updated as deemed necessary

Contact Ontario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

Zoom in on the map above and click your area of interest or use the Tile Index linked below to determine which package(s) you require for download. The DTM data is available in the form of 1-km by 1-km non-overlapping tiles grouped into packages for download.This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters and sensors may vary by project. See the detailed User Guide linked below for additional information.

You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page.

Now also available through a web service which exposes the data for visualization, geoprocessing and limited download. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection.

For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca.

Service Endpoints

https://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer https://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer (Government of Ontario Internal Users)

Additional Documentation

Ontario DTM (Lidar-Derived) - User Guide (DOCX)

OMAFRA Lidar 2016-2018 -Cochrane-Additional Contractor Metadata (PDF) OMAFRA Lidar 2016-2018 -Peterborough-AdditionalContractorMetadata (PDF) OMAFRA Lidar 2016-2018 -Lake Erie-AdditionalContractorMetadata (PDF) CLOCA Lidar 2018 - Additional Contractor Metadata (PDF) South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Huron - Additional Contractor Metadata (PDF) OMAFRA Lidar 2022 - Lake Simcoe - Additional Contractor Metadata (PDF) Huron-Georgian Lidar 2022-23 - Additional Contractor Metadata (Word) Kawartha Lakes Lidar 2023 - Additional Contractor Metadata (Word) Sault Ste Marie Lidar 2023-24 - Additional Contractor Metadata (Word) Thunder Bay Lidar 2023-24 - Additional Contractor Metadata (Word) Timmins Lidar 2024 - Additional Contractor Metadata (Word)

Ontario DTM (Lidar-Derived) - Tile Index (SHP) Ontario Lidar Project Extents (SHP)

OMAFRA Lidar DTM 2016-2018 -Cochrane- Breaklines (SHP) OMAFRA Lidar DTM 2016-2018 -Peterborough-Breaklines (SHP) OMAFRA Lidar DTM 2016-2018 -Lake Erie-Breaklines (SHP) CLOCA Lidar DTM 2018-Breaklines (SHP) South Nation Lidar DTM 2018-19-Breaklines (SHP) Ottawa-Gatineau Lidar DTM 2019-20 - Breaklines (SHP) OMAFRA Lidar DTM 2022 - Lake Huron - Breaklines (SHP) OMAFRA Lidar DTM 2022 - Lake Simcoe - Breaklines (SHP) Eastern Ontario Lidar DTM 2021-22 - Breaklines (SHP) Muskoka Lidar DTM 2018 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) Muskoka Lidar DTM 2021 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) Muskoka Lidar DTM 2023 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP) DEDSFM Huron-Georgian Bay 2022-23 - Breaklines (SHP) DEDSFM Kawartha Lakes 2023 - Breaklines (SHP) DEDSFM Sault Ste Marie 2023-24- UTM16 - Breaklines (SHP) DEDSFM Sault Ste Marie 2023-24- UTM17 - Breaklines (SHP) DEDSFM Sudbury 2023-24 - Breaklines (SHP) DEDSFM Thunder Bay 2023-24 - Breaklines (SHP) DEDSFM Timmins 2024 - Breaklines (SHP)

Product PackagesDownload links for the Ontario DTM (Lidar-Derived) (Word) Projects: LEAP 2009 GTA 2014-18 OMAFRA 2016-18 CLOCA 2018 South Nation CA 2018-19 Muskoka 2018-23 York-Lake Simcoe 2019 Ottawa River 2019-20 Ottawa-Gatineau 2019-20 Lake Nipissing 2020 Hamilton-Niagara 2021 Huron Shores 2021 Eastern Ontario 2021-22 OMAFRA Lake Huron 2022 OMAFRA Lake Simcoe 2022 Belleville 2022 Digital Elevation Data to Support Flood Mapping 2022-26

Huron-Georgian Bay 2022-23 Kawartha Lakes 2023 Sault Ste Marie 2023-24 Sudbury 2023-24 Thunder Bay 2023-24 Timmins 2024

Greater Toronto Area Lidar 2023

Status On going: Data is continually being updated

Maintenance and Update Frequency As needed: Data is updated as deemed necessary

Contact Ontario Ministry of Natural Resources - Geospatial Ontario,geospatial@ontario.ca

This zip file contains LIDAR, Digital Terrain Models (DTM's), surface, and breakline datasets covering the extent of Peoria County. The LIDAR data was captured during spring leaf-off in 2008. There are eight databases in Esri's file geodatabase format which are broken down by eight areas in the County. The DTM's conform to the ASPRS Class I Standards using the Illinois State Plane West coordinate system. Please contact us if you would like a copy of the data.More recent LIDAR data for Peoria County, IL was captured in 2012 by the State of Illinois through the Illinois Height Modernization Program (ILHMP). Please click Here to read about the program and data available for download.Contact InformationPeoria County GISEmail: gis@peoriacounty.orgPhone: 309-495-4840This data is bound to the Peoria County GIS Open Data License Agreement which can be found here: https://data-peoriacountygis.opendata.arcgis.com/pages/peoria-county-gis-open-data-license-agreement.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between October 25th and 31st, 2020 at several sites in eastern Iowa using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topographic light detection and ranging (lidar) data that was collected between December 7th, 2019 and November 19th, 2020 using wide area mapping lidar systems for the USGS 3D Elevation Program (3DEP). The goal was to compare and validate the airborne lidar data to topographic, structural, and infrastructural data collected through more traditional means (e.g., Global Navigational Satellite System (GNSS) surveying). Evaluating these data will provide valuable information on the performance of wide area topographic lidar mapping capabilities that are becoming more widely used in 3DEP. The airborne lidar was collected to support the U.S. Department of Agriculture (USDA) Natural Resources Conservation Service (NRCS) Hig ...

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface.

Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

This dataset contains a seamless high resolution, two-meter, topographic lidar digital elevation model (DEM) of the Lower Texas Coast. The elevations in this DEM represent the topographic bare-earth surface. The dataset is a fusion of several airborne topographic light detection and ranging (lidar) surveys acquired by various surveyors between the years 2007 – 2019 where coverage is primarily from 2018 and 2019. The landward extent of the lidar surveys selected for the creation of this DEM is determined by the boundary of the ADvanced CIRCulation (ADCIRC) TX2008_R35H computational mesh obtained from the Computational Hydraulics Group at The University of Texas at Austin. The spatial reference used for the tiles in the DEM is in Universal Transverse Mercator (UTM) Zone 14 in units of meters and in conformance with the North American Datum of 1983 (NAD83). All bare earth elevations are referenced to the North American Datum of 1988 (NAVD88). The 2-meter DEM of the upper Texas coast is available under GRIIDC Unique Dataset Identifier (UDI): HI.x833.000:0009 (DOI: 10.7266/2MYPTJ7Y).

LiDAR is a remote sensing technique that uses laser light to detect, range, or identify remote objects based on light reflected by the object or emitted through it subsequent fluorescence. Airborne ranging LiDAR is now being applied in coastal environments to produce accurate, cost-efficient elevation datasets with high data density. The USGS in cooperation with NASA and NPS is using airborne LiDAR to measure the topography of Assateague Island National Seashore land features. Elevation measurements were collected over Assateague Island National Seashore using the NASA Experimental Advanced Airborne Research LiDAR (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure subaerial and submarine coastal topography. With the NASA EAARL LiDAR system, submarine data is generally acquired to a maximum of approximately 1.5 secchi depths (a measure of water clarity). The system uses a high frequency laser beam directed at the earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The Experimental Advanced Airborne Research LiDAR, developed by the NASA Wallops Flight Facility (WFF) in Virginia, measures ground elevation with a vertical resolution of roughly 15 centimeters. A sampling rate of up to 3 kHz results in an extremely dense spatial elevation data set. For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

This lidar dataset was collected by the National Center for Airborne Laser Mapping (NCALM) for Alison Duvall at the University of Washington. The survey area consists of a single polygon located Northwest of Watsonville, California . The survey area covers approximately 45 km²

Publications associated with this dataset can be found at NCALM's Data Tracking Center

This dataset comprises a 1-m-resolution digital elevation model (DEM) of the Sertengshan Piedmont Fault in Northern China acquired by an airborne LiDAR survey. The LiDAR data were collected by the Aerospace ShuWei Company in Beijing, China in August 2019, using a Riegl VUX-1LR airborne LiDAR system mounted on a DM-150W fixed-wing unmanned aerial vehicle (UAV). The LiDAR data cover about a 1-km-wide swath along ~185 km section of the Sertengshan Piedmont Fault. The average point density is higher than 4 points/m2 and as high as 10 points/m2 in some local areas. The vertical accuracy of the LiDAR data is demonstrated to be better than 10 cm.

Elevation maps (also known as Digital Elevation Models or DEMs) of Cape Cod National Seashore were produced from remotely-sensed, geographically-referenced elevation measurements in cooperation with NASA and NPS. Point data in ascii text files were interpolated in a GIS to create a grid or digital elevation model (DEM) of each beach surface. Elevation measurements were collected in Massachusetts, over Cape Cod National Seashore using the NASA Experimental Advanced Airborne Research LiDAR (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation and coastal topography. The system uses high frequency laser beams directed at the earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the beach at approximately 60 meters per second while surveying from the low-water line to the landward base of the sand dunes. The EAARL, developed by the National Aeronautics and Space Administration (NASA) located at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of 15 centimeters. A sampling rate of 3 kHz or higher results in an extremely dense spatial elevation data set. Over 100 kilometers of coastline can be easily surveyed within a 3- to 4-hour mission time period. The ability to sample large areas rapidly and accurately is especially useful in morphologically dynamic areas such as barrier beaches. Quick assessment of topographic change can be made following storms comparing measurements against baseline data. When subsequent elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding coastal development. For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

A topographic lidar survey was conducted from September 5 to October 11, 2012, for the barrier islands of Alabama, Mississippi and southeast Louisiana, including the coast near Port Fourchon. Most of the data were collected September 5-10, 2012, with a reflight conducted on October 11, 2012, to increase point density in some areas. The data were collected at a nominal pulse space of 1-meter (m) and processed to identify bare earth elevations. Bare earth Digital Elevation Models(DEMs) were generated based on these data. Aero-Metric, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process the lidar data. The bare earth DEMs are 32-bit floating point ERDAS Imagine (IMG) files with a horizontal spatial resolution of 1-m by 1-m. They are projected to UTM zone 15N or 16N NAD83 meters. Their vertical datum is NAVD88 (GEOID12) meters. The DEMs are organized on a 2-kilometer (km) by 2-km tiling scheme that covers the entire survey area. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

The EarthScope Northern California Lidar project acquired high resolution lidar topographic data along major active faults in the Northern San Andreas Fault system, as part of the EarthScope Facility project funded by the National Science Foundation (NSF).

Publications associated with this dataset can be found at NCALM's Data Tracking Center

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return. Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected between June and October 2018.An ordnance datum (OD) is a vertical datum used as the basis for deriving heights on maps. This data is referenced to the Malin Head Vertical Datum which is the mean sea level of the tide gauge at Malin Head, County Donegal. It was adopted as the national datum in 1970 from readings taken between 1960 and 1969 and all heights on national grid maps are measured above this datum. Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.Digital Surface Models (DSM) are earth models in its current state. For example, a DSM includes elevations from buildings, tree canopy, electrical power lines and other features.Hillshading is a method which gives a 3D appearance to the terrain. It shows the shape of hills and mountains using shading (levels of grey) on a map, by the use of graded shadows that would be cast by high ground if light was shining from a chosen direction.This data shows the hillshade of the DTM.This data was collected by BlueSky and GeoAeroSpace and provided to the Geological Survey Ireland. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution is 1m.Both a DTM and DSM are raster data. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. This data has a grid cell size of 1 meter by 1 meter. This means that each cell (pixel) represents an area of 1 meter squared.

Hydro-Flattened Bare Earth DTM - 1m resolution. The dataset contains the 1m Digital Surface Model for the District of ColumbiaSome areas have limited data. The lidar dataset redaction was conducted under the guidance of the United States Secret Service. Except for classified ground points and classified water points, all lidar data returns and collected data were removed from the dataset within the United States Secret Service 1m redaction boundary generated for the 2017 orthophoto flight

This lidar dataset was collected as part of an NCALM Seed grant for Conor McMahon at the University of California, Santa Barbara. This dataset was collected to provide riparian vegetation mapping, classification, and measure historic drought response on the San Pedro river. The study area is located east of Sierra Vista, Arizona and covers approximately 81.5 km2. Publications associated with this dataset can be found at NCALM's Data Tracking Center

A first-surface topography Digital Elevation Model (DEM) mosaic for the Little Pine Island Bayou Corridor Unit of Big Thicket National Preserve in Texas was produced from remotely sensed, geographically referenced elevation measurements collected on January 15, 21, 22, 26, and 30, 2014 by the U.S. Geological Survey, in cooperation with the National Park Service - Gulf Coast Network. Elevation measurements were collected over the area using the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 55 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point density of 1.4 points per square meter. A peak sampling rate of 15-30 kilohertz results in an extremely dense spatial elevation dataset. More than 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development.

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return. Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected on 25th March 2015.An ordnance datum (OD) is a vertical datum used as the basis for deriving heights on maps. This data is referenced to the Malin Head Vertical Datum which is the mean sea level of the tide gauge at Malin Head, County Donegal. It was adopted as the national datum in 1970 from readings taken between 1960 and 1969 and all heights on national grid maps are measured above this datum. Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.Digital Surface Models (DSM) are earth models in its current state. For example, a DSM includes elevations from buildings, tree canopy, electrical power lines and other features. Hillshading is a method which gives a 3D appearance to the terrain. It shows the shape of hills and mountains using shading (levels of grey) on a map, by the use of graded shadows that would be cast by high ground if light was shining from a chosen direction.This data shows the hillshade of the DSM.This data was collected by New York University. All data formats are provided as GeoTIFF rasters. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. NYU data has a grid cell size of 1meter by 1meter. This means that each cell (pixel) represents an area of 1meter squared.

The U.S. Geological Survey (USGS) St. Petersburg Coastal and Marine Science Center (SPCMSC) in Florida and the USGS Lower Mississippi-Gulf Water Science Center (LMG WSC) in Montgomery, Alabama, collaborated to gather alongshore terrestrial-based lidar beach elevation data at Fire Island, New York. This high-resolution elevation dataset was collected on June 11, 2014, to characterize beach topography and document ongoing beach evolution and recovery, and is part of the ongoing beach monitoring within the Hurricane Sandy Supplemental Project GS2-2B. This USGS data series includes the resulting processed elevation point data (xyz) and an interpolated digital elevation model (DEM).