This data was collected by the Geological Survey Ireland, the Department of Culture, Heritage and the Gaeltacht, the Discovery Programme, the Heritage Council, Transport Infrastructure Ireland, New York University, the Office of Public Works and Westmeath County Council. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution varies depending on survey requirements. Resolutions for each organisation are as follows: GSI – 1m DCHG/DP/HC - 0.13m, 0.14m, 1m NY – 1m TII – 2m OPW – 2m WMCC - 0.25m 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. The grid cell size varies depending on the organisation that collected it. GSI 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.

This Data Series Report contains lidar elevation data collected 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. Lidar data exchange format (LAS) 1.2 formatted point data files were generated based on these data. The point cloud data were processed to extract bare earth data; therefore, the point cloud data are organized into only four classes: 1-unclassified, 2-ground, 7-noise and 9-water. Aero-Metric, Inc., was contracted by the U.S. Geological Survey (USGS) to collect and process these data. The lidar data were collected at a nominal pulse spacing (NPS) of 1.0 meter (m). The horizontal projection and datum of the data are Universe Transverse Mercator, zones 15N and 16N, North American Datum 1983 (UTM Zone 15N or 16N NAD83), meters. The vertical datum is North American Vertical Datum 1988, Geoid 2012 (NAVD88, GEOID12), meters. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

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 Management. A separate but related task order was issued by the USGS National Geospatial Technical Operations Center (NGTOC), under their Geospatial Products and Services Contract (GPSC), to leverage the same resources committed to the NOAA LiDAR project for the acquisition of LiDAR data in the southern 1/3 portion of Oahu. The combined task orders yielded one study area covering the entire island of Oahu. The data collected for the island of Oahu will exhibit Hydro Flattened DEMs for inclusion into the NED. The purpose of the data is for use in coastal management decision making, including applications such as flood plain mapping and water rights management. The point density for this data set was specified in the SOW at 1.15 pts/m2. The NOAA Office for Coastal Management tested the NPS (nominal pulse spacing) for this data set in April 2015. The NPS was determined to be 0.84 m. The data used in the NPS determination were the first returns of classes 1,2,9, and 10.

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.

Note: The shapefile download may fail when downloading the entire dataset. If this happens, download the file geodatabase instead.Feature class contains 2-foot interval contours of the area surrounding and including the Eugene urban growth boundary. Contours have been derived by LCOG from 2009 LiDAR data. The LiDAR data was prepared by Watershed Science for DOGAMI. General processing includes (1) joining Junction City, Coburg, Eugene East and Eugene West bare-earth quads into one mosaic, (2) smoothing the mosaic with a focal mean (3 x 3 rectangle), (3) contouring the smoothed bare-earth mosaic, and (4) quality-checking along the edges of the quads to insure matching contours. (DISCLAIMER: The maps and data available for access from the City of Eugene are provided "as is" without warranty or any representation of accuracy, timeliness or completeness. The burden for determining accuracy, completeness, timeliness, merchantability and fitness for or the appropriateness for use rests solely on the user accessing this information. The City of Eugene makes no warranties, expressed or implied, as to the use of the maps and data available for access at this website. There are no implied warranties of merchantability or fitness for a particular purpose. The user acknowledges and accepts all inherent limitations of the maps and data, including the fact that the maps and data are dynamic and in a constant state of maintenance, correction and revision. Any maps and associated data for access do not represent a survey. No liability is assumed for the accuracy of the data delineated on any map, either expressed or implied.)

Note: The files can be downloaded from the Attachments section below. Please note that the total size is 180GB, so the download may take some time depending on your system’s capabilities and configuration.

Topographic and bathymetric LiDAR data was collected for New York City in 2017. Topographic data was collected for the entire city, plus an additional 100 meter buffer, using a Leica ALS80 sensor equipped to capture at least 8 pulse/m². Dates of capture for topographic data were between 05/03/2017 and 05/17/2017 during 50% leaf-off conditions. Bathymetric data was collected in select areas of the city (where bathymetric data capture was expected) using a Riegl VQ-880-G sensor equipped to capture approximately 15 pulses/m² (1.5 Secchi depths). Dates of capture for bathymetric were between 07/04/2017 - 07/26/2017. LiDAR data was tidally-coordinated and captured between mean lower low water (+30% of mean tide) ranges.

The horizontal datum for all datasets is NAD83, the vertical datum is NAVD88, Geoid 12B, and the data is projected in New York State Plane - Long Island. Units are in US Survey Feet. To learn more about these datasets, visit the interactive “Understanding the 2017 New York City LiDAR Capture” Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LiDAR_Summary.md

Many Ontario lidar point cloud datasets have been made available for direct download by the Government of Canada through the federal Open Government Portal under the LiDAR Point Clouds – CanElevation Series record. Instructions for bulk data download are available in the Download Instructions document linked from that page. To download individual tiles, zoom in on the map in GeoHub and click a tile for a pop-up containing a download link.

See the LIO Support - Large Data Ordering Instructions to obtain a copy of data for projects that are not yet available for direct download. 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

Web map displaying Wisconsin DNR-produced Digital Elevation Model (DEM) and Hillshade image services, along with their index layer, in formats that are clickable and can be symbolized and filtered. This map can also be used as a starting point to create a new map. To open the web map from DNR's GIS Open Data Portal, click the View Metadata: link to the right of the description, then click Open in Map Viewer.

The Light Detection and Ranging (LiDAR) data set is a survey of Alameda County in Northern California. The entire survey covers approximately 868.382 square miles. The Nominal Point Density of this dataset is approximately 1.66 meters for unobscured areas. The LiDAR discrete-return point cloud data were originally available in the American Society for Photogrammetry and Remote Sensing (ASPRS) L...

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) High Resolution Elevation Enterprise Program and the Iowa Department of Agriculture and Land Stewardship Iowa Flood Plain Program, in addition to the 3DEP mission. The data contained within this particular release are comprised of conventional survey (i.e. total station and GNSS) and ground based lidar data.

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 2015 and 2020.

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.

This data was collected by the Geological Survey Ireland, the Department of Culture, Heritage and the Gaeltacht, the Discovery Programme, the Heritage Council, Transport Infrastructure Ireland, New York University, the Office of Public Works and Westmeath County Council. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution varies depending on survey requirements. Resolutions for each organisation are as follows:

GSI – 1m

DCHG/DP/HC - 0.13m, 0.14m, 1m

NY – 1m

TII – 2m

OPW – 2m

WMCC - 0.25m

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. The grid cell size varies depending on the organisation that collected it. GSI 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.

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.

These raster datasets are 3-meter lidar-derived images of Monroe County, West Virginia, and were created using geographic information systems (GIS) software. Lidar-derived elevation data acquired in late December of 2016 were used to create a 3-meter resolution working digital elevation model (DEM), from which a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create a 3-meter resolution lidar-derived image. The data is projected in North America Datum (NAD) 1983 UTM Zone 17.

This raster dataset contains 1-meter lidar-derived imagery of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using geographic information systems (GIS) software. Lidar-derived elevation data, acquired in 2018, were used to create a 1-meter resolution working digital elevation model (DEM). To create this imagery, a hillshade was applied and a topographic position index (TPI) raster was calculated. These two rasters were uploaded into GlobalMapper, where the TPI raster was made partially transparent and overlaid the hillshade DEM. The resulting image was exported to create these 1-meter resolution lidar-derived images. The data is projected in North America Datum (NAD) 1983 (2011) UTM Zone 19N.

In 2021, a complete airborne LiDAR survey of the Northern Ireland coastline was commissioned as part of the NI 3D Coastal Survey, providing precise and accurate data of the current coastal morphology.The survey included the intertidal area and extended approximately 200 meters landward of the high-water mark.This is the Digital Terrain Model derived from the LiDAR data collected.

A seamless hydro-flattened digital surface model (DSM) with 1 metre resolution. The DSM captures the land surface and natural and built features on the earth's surface, such as trees and buildings.The LiDAR data was captured for the Halifax Regional Municipality's coastal flood mapping project through topographic andtopo-bathymetric lidar data collection in 2017-2018 and was processed by the Applied Geomatics Research Group at NSCC.Due to limitations of the sensor used in the topography lidar data acquisition mission, the dataset excludes a significant number of buildings and other asphalt surfaces such as driveways. Users should use caution when using the data for those purposes. Metadata

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 in 2011.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 the Office of Public Works. 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. OPW data has a grid cell size of 2 meter by 2 meter. This means that each cell (pixel) represents an area of 2 meter squared.

The project vendor, Woolpert, Inc., acquired highly accurate Light Detection and Ranging (lidar) elevation data for the Arrowhead Region in Northeast Minnesota in Spring 2011. The data cover Carlton, Cook, Lake and St. Louis counties, part of Itasca County, and Voyageurs National Park in Koochiching County. Lidar data are in the UTM Zone 15 coordinate system, NAD83 96 NAVD88 Geoid09, meters. The tiling scheme is 16th USGS 1:24,000 quadrangle tiles.

The vendor delivered the data to the Minnesota Department of Natural Resources (DNR) in several formats:

1) One-meter digital elevation model
2) Edge-of-water breaklines
3) Classified LAS formatted point cloud data

DNR staff created two additional products: two-foot contours and building outlines.

This metadata record was created at the Minnesota Geospatial Information Office by combining information supplied by Woolpert and DNR.

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.This data shows the areas in Dublin for which you can download LiDAR data and contains links to download the data. This is a vector dataset. Vector data portray the world using points, lines, and polygons (areas).The LiDAR coverage is shown as polygons. Each polygon is 2000m by 2000m in size and holds information on: the location, county, data provider, owner, licence, published date, capture date, surveyor, RMS error, resolution and a link to download the LiDAR raster data in 2000m by 2000m sections.

U.S. Geological Survey (USGS) scientists conducted field data collection efforts between July 19th and 31st, 2021 over a large stretch of the McKenzie River in Oregon using high accuracy surveying technologies. The work was initiated as an effort to validate commercially acquired topobathymetric light detection and ranging (lidar) data that was collected coincidentally between July 26th and 30th, 2021 for the USGS 3D Elevation Program (3DEP). The goal was to compare and validate the airborne lidar data to topographic, bathymetric, 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 inland topobathymetric lidar mapping capabilities and their potential for use and inclusion in the USGS National Geospatial Program 3D Elevation Program. The airborne topobathymetric lidar data will be used for developing reliable hydraulic models, which can be used to model potential flood inundation and analysis for other potential hazards such as landslides. The bathymetric lidar data will also be used for characterization of endangered species aquatic habitat, including that of salmon and steelhead trout species. Furthermore, a large portion of the McKenzie River corridor that was mapped by the airborne topobathymetric lidar was impacted by the Holiday Farm Fire that burned over 170,000 acres during September of 2020 and the airborne data will be used to support post-fire geomorphic change detection.