This data collection of the 3D Elevation Program (3DEP) consists of Lidar Point Cloud (LPC) projects as provided to the USGS. These point cloud files contain all the original lidar points collected, with the original spatial reference and units preserved. These data may have been used as the source of updates to the 1/3-arcsecond, 1-arcsecond, and 2-arcsecond seamless 3DEP Digital Elevation Models (DEMs). The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Lidar (Light detection and ranging) discrete-return point cloud data are available in LAZ format. The LAZ format is a lossless compressed version of the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. Point Cloud data can be converted from LAZ to LAS or LAS to LAZ without the loss of any information. Either format stores 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of geo-referenced x, y coordinates and z (elevation), as well as other attributes for each point. Additonal information about the las file format can be found here: https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities. All 3DEP products are public domain.

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.DEFRA Data Services Platform Metadata URLDefra Network WMS server provided by the Environment Agency

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.

The goal of the USGS 3D Elevation Program (3DEP) is to collect elevation data in the form of light detection and ranging (LiDAR) data over the conterminous United States, Hawaii, and the U.S. territories, with data acquired over an 8-year period. This dataset provides two realizations of the 3DEP point cloud data. The first resource is a public access organization provided in Entwine Point Tiles format, which a lossless, full-density, streamable octree based on LASzip (LAZ) encoding. The second resource is a Requester Pays of the original, Raw LAZ (Compressed LAS) 1.4 3DEP format, and more complete in coverage, as sources with incomplete or missing CRS, will not have an ETP tile generated. Resource names in both buckets correspond to the USGS project names.

This data set is comprised of lidar point cloud data. This project required lidar data to be acquired over Horry County, South Carolina. The total area of the Horry County Elevation Data and Imagery AOI is approximately 1092 square miles. Lidar data was collected and processed to meet the requirements of the project task order. The lidar collection was a collaborative effort between two data acquisition firms. While Woolpert was responsible for collection of the majority of the county, the coastal portion of the data was collected by Quantum Geospatial and is detailed in the processing steps of the metadata. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, four (4) foot pixel raster DEMs of the bare-earth surface in ERDAS IMG Format. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Ground conditions: Water at normal levels; no unusual inundation; no snow. The bare earth DEMs along the coast may have a variance in the water heights due to temporal differences during the lidar data acquisition and will be represented in DEM as a seam-like anomaly. One coastal elevation was applied to entire project area. Due to differing acquisition dates and thus differing tide levels there will be areas in the DEM exhibiting what appears to be "digging" water features. Sometimes as much as approximately 2.5 feet. This was done to ensure that no coastal hydro feature was "floating" above ground surface. This coastal elevation will also affect connected river features wherein a sudden increase in flow will be observed in the DEM to accommodate the coastal elevation value. During Hydrologic breakline collection, Woolpert excluded obvious above-water piers or pier-like structures from the breakline placement. Some features extend beyond the apparent coastline and are constructed in a manner that can be considered an extension of the ground. These features were treated as ground during classification and subsequent hydrologic delineation. In all cases, professional practice was applied to delineate what appeared to be the coast based on data from multiple sources; Due to the many substructures and the complexity of the urban environment, interpolation and apparent "divots" (caused by tinning) may be evident in the surface of the bare earth DEM. In all cases, professional practice was applied to best represent the topography. The data received by the NOAA OCM are topographic data in LAS 1.2 format, classified as unclassified (1), ground (2), all noise (7), water (9), ignored ground (10), overlap unclassified (17), and overlap ground (18). Digital Elevation Models (DEMs) and breakline data are also available. The DEM data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/DEMs/ The breakline data are available at: ftp://coast.noaa.gov/pub/DigitalCoast/lidar1_z/geoid18/data/4814/breaklines Any conclusions drawn from the analysis of this information are not the responsibility of NOAA, the Office of Coastal Management (OCM)or its partners. Original contact information: Contact Org: Woolpert Phone: (937) 461-5660

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 vary by project. Some projects 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 SizesLEAP 2009 - 22.9 GBOMAFRA Lidar 2016-18 - Cochrane - 442 GBOMAFRA Lidar 2016-18 - Lake Erie - 1.22 TBOMAFRA Lidar 2016-18 - Peterborough - 443 GBGTA 2014 - 57.6 GBGTA 2015 - 63.4 GBBrampton 2015 - 5.9 GBPeel 2016 - 49.2 GBMilton 2017 - 15.3 GBHalton 2018 - 73 GBCLOCA 2018 - 36.2 GBSouth Nation 2018-19 - 72.4 GBYork Region-Lake Simcoe Watershed 2019 - 75 GBOttawa River 2019-20 - 836 GBLake Nipissing 2020 - 700 GBOttawa-Gatineau 2019-20 - 551 GBHamilton-Niagara 2021 - 660 GBOMAFRA Lidar 2022 - Lake Huron - 204 GBOMAFRA Lidar 2022 - Lake Simcoe - 154 GBBelleville 2022 - 1.09 TBEastern Ontario 2021-22 - 1.5 TBHuron Shores 2021 - 35.5 GBMuskoka 2018 - 72.1 GBMuskoka 2021 - 74.2 GBMuskoka 2023 - 532 GBDigital Elevation Data to Support Flood Mapping 2022-26:Huron-Georgian Bay 2022 - 1.37 TBHuron-Georgian Bay 2023 - 257 GBHuron-Georgian Bay 2023 Bruce - 95.2 GBKawartha Lakes 2023 - 385 GBSault Ste Marie 2023-24 - 1.15 TBSudbury 2023-24 - 741 GBThunder Bay 2023-24 - 654 GBTimmins 2024 - 318 GBCataraqui 2024 - 50.5 GBGTA 2023 - 985 GBStatusOn going: Data is continually being updated Maintenance and Update FrequencyAs needed: Data is updated as deemed necessary ContactOntario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

The High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

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.

Elevation datasets in New Jersey have been collected over several years as several discrete projects. Each project covers a geographic area, which is a subsection of the entire state, and has differing specifications based on the available technology at the time and project budget. The geographic extent of one project may overlap that of a neighboring project. Each of the 18 projects contains deliverable products such as LAS (Lidar point cloud) files, unclassified/classified, tiled to cover project area; relevant metadata records or documents, most adhering to the Federal Geographic Data Committee’s (FGDC) Content Standard for Digital Geospatial Metadata (CSDGM); tiling index feature class or shapefile; flights lines feature class or shapefile; Digital Elevation Model in image format or Esri grid format; other derivative data products such as contour lines feature class or shapefile.

During the Fall of 2016 AGRC and the Utah Geological Survey acquired ~205 square miles of 8 points per meter Quality Level 1 LiDAR of The Frontier Observatory for Research in Geothermal Energy (FORGE) area around Milford, Utah in Beaver and Millard Counties in western Utah. The 0.5 meter resolution bare earth DEMs and first-return/highest-hit DSMs in .img format have a 10.0cm vertical RMSE accuracy and are available for download. The LAS classified point clouds are also available by request Rick Kelson from AGRC at RKelson@utah.gov or The National Map. This elevation data was collected between October 26 and November 3, 2016 and has a UTM NAD83 (2011) zone 12 north meter NAVD88(GEOID12) projection.

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 point cloud is structured into non-overlapping 1 km by 1 km tiles in LAZ format. The following classification codes are applied to the data: * unclassified * ground * water * high noise * low noise This dataset is a compilation of lidar data from multiple acquisition projects, so specifications, parameters, accuracy and sensors may vary by project. This data is for geospatial tech specialists, and is used by government, municipalities, conservation authorities and the private sector for land use planning and environmental analysis. Related data: 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).

Lidar data for the United States portion of the Missisquoi Watershed in Northern Vermont. Data were collected during leaf-off conditions in 2008 and in 2009 while no snow was on the ground and rivers were at or below normal levels. The Lidar data were acquired at a nominal post spacing of 1.4 meters. Points were classified as ground (LAS class 2) using a combination of automated and manual techniques. The data were acquired by Photoscience and subsequently reviewed by the USGS and The University of Vermont. The data are made available on OpenTopography through a grant from AmericaView.

MD/PA Sandy Supplemental Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00397 Woolpert Order No. 74333 CONTRACTOR: Woolpert, Inc. This task is for a high resolution data set of lidar covering approximately 1,845 square miles. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. Coastal tiles 18SVH065720 and 8SVH095690 contain no lidar points as they exist completely in water. A DEM IMG was generated for these two tiles as the digitized hydro breakline assumed the data extent in the area. As such only 2568 LAS and Intensity files will be delivered along with 2570 DEM IMG's.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://mdgeodata.md.gov/lidar/rest/services/BaltimoreCity/MD_baltimorecity_dem_ft/ImageServer

Original Dataset Product: Processed, classified lidar point cloud data tiles in LAZ 1.4 format. Original Dataset Geographic Extent: HI_NOAAMauiOahu_1: The work unit covers approximately 446 square miles (260.7 square miles of Molokai, 140.7 square miles of Lanai, and 44.6 square miles of Kahoolawe in the state of Hawaii). HI_NOAAMauiOahu_2: The work unit covers approximately 540.86 square miles of Maui and 496.61 square miles of Oahu in the state of Hawaii. Original Dataset Description: HI_NOAAMauiOahu_1 (Kahoolawe, Lanai, Molokai) HI_NOAAMauiOahu_1_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 4 (EPSG 6634), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. Lidar data was delivered as processed LAZ 1.4 files formatted to 5,044 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. HI_NOAAMauiOahu_2 (Maui, Oahu) HI_NOAAMauiOahu_2_B20 lidar project called for the planning, acquisition, processing, and production of derivative products of QL1 lidar data to be collected an aggregate nominal pulse spacing (ANPS) of 0.35-meters and 8 points per square meter (ppsm). Project specifications were based on the National Geospatial Program Lidar Base Specification Version 2.1, and the American Society of Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0). The data was developed based on a horizontal reference system of NAD83 (PA11), UTM 4 (EPSG 6634), Meter, and a vertical reference system of NAVD88 (GEOID12B), Meter. Lidar data was delivered as processed LAZ 1.4 files formatted to 11,716 individual 500-meters x 500-meters tiles. Note: Between 2020 and 2023 multiple mobilizations were made to collect the data in the project area due to the extreme terrain and persistent low clouds. On March 31, 2023, it was decided between Woolpert and USGS to end the acquisition phase of the project and move onto processing with the data collected. The DPA and work unit has been clipped to the extent of the data collected. Areas of low point density and/or small data voids within the work unit have been identified with low confidence polygons. Original Dataset Ground Conditions: HI_NOAAMauiOahu_1 (Kahoolawe, Lanai, Molokai) Lidar was collected from August 2, 2022, through July 9, 2023 while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. HI_NOAAMauiOahu_2 (Maui, Oahu) Lidar was collected from January 11, 2023, through July 7, 2023 while rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Woolpert established ground control points that were used to calibrate the lidar to known ground locations established throughout the entire project area. An additional independent accuracy checkpoints were collected throughout the entire project area and used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data.

Many different partners and groups, and several Center-led data projects, have contributed to the lidar data collection housed and distributed by the NOAA Office for Coastal Management. The data span more than two decades and were collected using many different sensors. The collection includes data from topographic and bathymetric lidar sensors. Data are available for all of the coastal states and range from shoreline strips to full county coverage. The products have been delivered to the Center in various formats, projections, datums, and units. Once received, the data are reviewed, checked for errors, and standardized to LAZ format, geographic coordinates and ellipsoid heights in meters. Data are on a NAD83 or ITRF realization depending upon the collection specifics.

This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. PAMAP data are organized into blocks, which do not have gaps or overlaps, that represent 10,000 feet by 10,000 feet on the ground. The coordinate system for blocks in the northern half of the state is Pennsylvania State Plane North (datum:NAD83, units: feet); blocks in the sou...

This dataset is a footprint of the current available LiDAR data over for the State of Queensland compiled from numerous LiDAR projects captured on or after the year 2008.

The hillshade is a black-and-white image showing elevation changes in the landscape. It is created from a digital elevation model as if the elevation surface were illuminated by a hypothetical light source shining from the northwest.

The U.S. Geological Survey contracted with LiteWave Technologies (formerly ASTRALiTe) to fly their production topo-bathymetric lidar system (Edge) along the Colorado River near McCoy, Colorado, on September 8-9, 2021. The objective of this project was to assess the potential to map river bathymetry (i.e., river-bed topography) using lidar data collected from an uncrewed aircraft system (UAS). The Edge was mounted on a UAS owned and operated by LiteWave Technologies. This data release includes data delivered to the USGS by LiteWave Technologies on November 9, 2021. Grid coordinates are projected in Universal Transverse Mercator Zone 13 North and are represented in units of meters. The topo-bathymetric elevations, in units of meters, delivered by the contractor are believed to be relative to the height of the GRS80 ellipsoid and differ from the more commonly used orthometric height computed by the addition of the geoid height to the GRS80 ellipsoid. The data is provided as a LAS file which includes points classified as bathymetric or river bottom (code 40), created, never classified (code 0), and water surface returns (code 41). These data delivered to USGS have not been filtered or modified.

This resource was created by Esri Canada Education and Research. To browse our full collection of higher-education learning resources, please visit https://hed.esri.ca/resourcefinder/.Lidar data have become an important source for detailed 3D information for cities as well as forestry, agriculture, archaeology, and many other applications. Topographic lidar surveys, which are conducted by airplane, helicopter or drone, produce data sets that contain millions or billions of points. This can create challenges for storing, visualizing and analyzing the data. In this tutorial you will learn how to create a LAS Dataset and explore the tools available in ArcGIS Pro for visualizing lidar data.To download the tutorial and data folder, click the Open button to the top right. This will download a ZIP file containing the tutorial documents and data files.Software & Solutions Used: ArcGIS Pro Advanced 3.x. Last tested with ArcGIS Pro version 3.3. Time to Complete: 30 - 60 minsFile Size: 337 MBDate Created: August 2020Last Updated: March 2024