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 ...

This dataset consists of point cloud data collected in 2016 and 2017 of the lower and upper Scenic Drive landslide locations in La Honda, California. Point cloud data were collected in 2016 to establish baseline for movement detection of past landslides. Point cloud data were collected in 2017 adjacent and upslope of 2016 data to document a newly formed landslide. The data were collected with a Riegl VZ400 Terrestrial Laser Scanner and georeferenced using a Leica Viva GS15 survey grade GPS. The data are delivered as georeferenced (NAD83 UTM zone 10N ellipsoid) classified point clouds, 5 cm resolution digital elevation models, and a text file of surveyed GPS control points.
The included files are:
LH2017_Jan.laz LH2016_Jan.laz LH2017_5cm_DEM_be_tin.tif LH2017_5cm_DEM_bebldg_tin.tif LH2017_5cm_DEM_be_idp.tif LH2016_5cm_DEM_be_tin.tif LH2016_5cm_DEM_bebldg_tin.tif LH2016_5cm_DEM_be_idp.tif LH_GPS_control_points_NAD83_UTM_z10N_ell.txt

Unclassified three-dimensional point cloud by flightline and classified point cloud by 1 km tile, provided in LAZ format. Classifications follow standard ASPRS definitions. All point coordinates are provided in meters. Horizontal coordinates are referenced in the appropriate UTM zone and the ITRF00 datum. Elevations are referenced to Geoid12A.

LiDAR data obtained from the USGS National Map: https://apps.nationalmap.gov/downloader/. Point cloud resolution is approximately 0.7m NPS. Data was collected January and February of 2020.Elevation is in International Feet.

Elevation Point Cloud data is available from various sources. Visit the links below or contact Reed Burgette (reed.burgette@dogami.oregon.gov) at Department of Geology and Mineral Industries (DOGAMI) for more information. Resources: https://gis.dogami.oregon.gov/maps/lidarviewer/ ftp://lidar.engr.oregonstate.edu/ https://coast.noaa.gov/digitalcoast/ https://www.usgs.gov/programs/national-geospatial-program/national-map

This data release consists of three child items distinguishing the following types of data: light detection and ranging (lidar) point clouds (LPCs), digital elevation models (DEMs), and snow depth raster maps. These three data types are all derived from lidar data collected on small, uncrewed aircraft systems (sUAS) at study areas in the Upper Colorado River Basin, Colorado, from 2020 to 2022. These data were collected and generated as part of the U.S. Geological Survey's (USGS) Next Generation Water Observing Systems (NGWOS) Upper Colorado River Basin project.

The DFG Priority Program 1803 “EarthShape” (www.earthshape.net) investigates Earth surface shaping by biota. As part of this project, we present Light Detection and Ranging (LiDAR) data of land surface areas for the four core research sites of the project. The research sites are located along a latitudinal gradient between ~26 °S and ~38 °S in the Chilean Coastal Cordillera. From north to south, the names of these sites are: National Park Pan de Azúcar; Private Reserve Santa Gracia; National Park La Campana; and National Park Nahuelbuta. The three datasets contain raw 3D point cloud data captured from an airborne LiDAR system, and the following derivative products: a) digital terrain models (DTM, sometimes also referred to as DEM [digital elevation model]) which are (2.5D) raster datasets created by rendering only the LiDAR returns which are assumed to be ground/bare-earth returns and b) digital surface models (DSM) which are also 2.5D raster datasets produced by rendering all the returns from the top of the Earth’s surface, including all objects and structures (e.g. buildings and vegetation). The LiDAR data were acquired in 2008 (southernmost Nahuelbuta [NAB] catchment), 2016 (central La Campana [LC] catchment) and 2020 (central Santa Gracia [SGA] catchment). Except for Nahuelbuta (data already was available from the data provider from a previous project), the flights were carried out as part of the "EarthShape" project. The LiDAR raw data (point cloud/ *.las files) were compressed, merged (as *.laz files) and projected using UTM 19 S (UTM 18 S for the southernmost Nahuelbuta catchment, respectively) and WGS84 as coordinate reference system. A complementary fourth dataset for the northernmost site in the National Park Pan de Azúcar, derived from Uncrewed Aerial Vehicle (UAV) flights and Structure from Motion (SfM) photogrammetry, is expected to be obtained during the first half of 2022 and will be added to the above data set.

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 feature service is available through CT ECO, a partnership between UConn CLEAR and CT DEEP. The tile grid service is as an index for accessing aerial imagery and lidar elevation data files for Connecticut and is used in the Download Tool.

This web map allows for the download of KyFromAbove LiDAR data by 5k tile in LAZ format. This point cloud data was acquired during the typical leaf-off acquisition period (winter-spring) over a period of several years and may be provided as LAS version 1.1, 1.2, or 1.4 depending upon the acquisition period. Users will need to download the LAZIP.exe in order to decompress each tile. LiDAR data specifications adopted by the KyFromAbove Technical Advisory Committee can be found here. This is the source data used to create the Commonwealth's 5 foot digital elevation model (DEM) and its associated derivatives. More information regarding this data resource can be found on the KyGeoPortal.

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

The LiDAR Point Clouds is a product that is part of the CanElevation Series created to support the National Elevation Data Strategy implemented by NRCan. This product contains point clouds from various airborne LiDAR acquisition projects conducted in Canada. These airborne LiDAR acquisition projects may have been conducted by NRCan or by various partners. The LiDAR point cloud data is licensed under an open government license and has been incorporated into the National Elevation Data Strategy. Point cloud files are distributed by LiDAR acquisition project without integration between projects. The point cloud files are distributed using the compressed .LAZ / Cloud Optimized Point Cloud (COPC) format. The COPC open format is an octree reorganization of the data inside a .LAZ 1.4 file. It allows efficient use and visualization rendering via HTTP calls (e.g. via the web), while offering the capabilities specific to the compressed .LAZ format which is already well established in the industry. Point cloud files are therefore both downloadable for local use and viewable via URL links from a cloud computing environment. The reference system used for all point clouds in the product is NAD83(CSRS), epoch 2010. The projection used is the UTM projection with the corresponding zone. Elevations are orthometric and expressed in reference to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013).

Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. The LAS format is a standardized binary format for storing 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 x (longitude), y (latitude) and z (elevation) points. A few older projects in this collection are in ASCII format. Please refer to http://www.asprs.org/Committee-General/LASer-LAS-File-Format-Exchange-Activities.html for additional information.

These lidar data are derived from two airborne lidar surveys: a 2016 Los Angeles Region Imagery Acquisition Consortium (LARIAC) survey, and a 2019 National Center for Airborne Laser Mapping (NCALM) survey. These data were reclassified in order to improve the classification of ground points, and to make the classification of both datasets as consistent as possible. The NCALM data had their position shifted slightly to more closely align with the LARIAC data. The data are organized into two "Child Items": Reclassified lidar point clouds from 2016 LARIAC collection near Malibu, California and Reclassified lidar point clouds from 2019 NCALM collection near Malibu, California. The point clouds are available as ~1 square kilometer tiles with 25 m buffer overlaps to avoid edge effects in further processing. The naming convention includes the name of the original data collection and some reference UTM coordinates.

These digital elevation models (DEMs) were generated from light detection and ranging (lidar) point clouds (LPCs) derived from lidar data collected during multiple field campaigns at three study areas near Winter Park, Colorado. Small, uncrewed aircraft systems (sUAS) were used to collect lidar datasets to represent snow-covered and snow-free periods.

This layer contains the Point Cloud for LiDAR data in the Northland region, captured between 18 April 2024 - 28 June 2024.

The DEM is available as layer Northland LiDAR 1m DEM (2024).

The DSM is available as layer Northland LiDAR 1m DSM (2024).

The Index Tiles are available as layer Northland LiDAR Index Tiles (2024).

LiDAR was captured for Regional Software Holdings Ltd by Landpro Ltd from 18 April to 28 June 2024. The dataset was generated by Landpro and their subcontractors. Data management and distribution is by Toitū Te Whenua Land Information New Zealand.

Data comprises:

DEM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout

DSM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout

Point cloud: las tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout

Pulse density specification is at a minimum of 8 pulses/square metre.

Vertical Accuracy Specification is +/- 0.2m (95%) Horizontal Accuracy Specification is +/- 1.0m (95%)

Vertical datum is NZVD2016.

This dataset contains Light Detection and Ranging (LiDAR) elevation data from Quarantine Bay and Neptune Pass, located in southeastern Louisiana, USA, on the east side of the lower Mississippi River. Data were collected on 6 October 2022 and 28 March 2023 to investigate landform development and vegetation dynamics associated with the expansion of Neptune Pass, the largest new distributary of the Mississippi River. The study area spans from 29.397°N to 29.272°N latitude and from -89.521°W to -89.474°W longitude. Data acquisition was performed using a DJI Matrice 300 RTK drone platform equipped with a Zenmuse L1 gimbal payload, which integrates both a LiDAR scanner and a high-resolution RGB camera. Digital elevation models (DEMs) and visible light mosaics were produced from dense 3D point clouds using DJI Terra (https://enterprise.dji.com/dji-terra) and CloudCompare (https://github.com/CloudCompare/CloudCompare/releases/). Georeferencing was achieved using real-time kinematic (RTK) GPS ground control points in QGIS to align LiDAR pulses and imagery with real-world coordinates. The final products include high-resolution DEMs and RGB orthomosaics suitable for geomorphological and ecological analysis.

Bare earth elevation surface (DTM) and actual surface (DSM) given in meters in the NAVD88 (Geoid12A realization) vertical reference frame. Horizontal coordinates referenced to appropriate UTM zone. Bare earth is created by classifying and removing vegetation and man-made structures from lidar point cloud prior to surface generation. Both the DSM and DTM are mosaicked onto a spatially uniform grid at 1 m spatial resolution in 1 km by 1 km tiles provided in a geotiff format.

This data set is derived from the original 2005 data collected over the southern San Andreas and San Jacinto fault zones in southern California, USA. These data have provided a fundamental resource for study of active faulting in southern California since they were released in 2005. However, these data were not classified in a manner that allowed for easy differentiation between bare ground surfaces and the objects and vegetation above that surface. This reprocessed (classified) dataset allows researchers easy and direct access to a "bare-earth" digital elevation data set as gridded half-meter resolution rasters (elevation and shaded relief) , "full-feature" digital elevation models as gridded one-meter resolution rasters (elevation and shaded relief) and as classified (according to ASPRS standards) point clouds in binary .laz format, and a spatial index in shapefile and Google Earth KML format.

This data set provides 3 m gridded, bare-earth elevations (excluding trees) that are used as the baseline for the Airborne Snow Observatory (ASO) snow-on products. The data were collected during snow-free conditions as part of the NASA/JPL ASO aircraft survey campaigns.