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.

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.

This Datasets contains the Kitti Object Detection Benchmark, created by Andreas Geiger, Philip Lenz and Raquel Urtasun in the Proceedings of 2012 CVPR ," Are we ready for Autonomous Driving? The KITTI Vision Benchmark Suite". This Kernel contains the object detection part of their different Datasets published for Autonomous Driving. It contains a set of images with their bounding box labels and velodyne point clouds. For more information visit the Website they published the data on (http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=2d).

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.

These light detection and ranging (lidar) point clouds (LPCs) were generated from lidar data collected during multiple field campaigns in three study areas near Winter Park, Colorado. Small, uncrewed aircraft systems (sUAS) collected lidar datasets to represent snow-covered and snow-free periods. More information regarding the sUAS used and data collection methods can be found in the Supplemental Information and process step sections of each study area metadata file.

The LIDAR point cloud is an archive of hundreds of millions, or sometimes billions of highly accurate 3-dimensional x,y,z points and component attributes produced by the Environment Agency.

The environment agecy site specific LIDAR DSM and DTM Time Stamped Tiles gridded raster products are derived from the point cloud. The component attributes a point cloud contains can provide valuable additional information to supplement elevation and can enable the user to make bespoke raster products such as canopy height models or intensity rasters.

Site specific LIDAR surveys have been carried out across England since 1998, with certain areas, such as the coastal zone, being surveyed multiple times. The point cloud is available for surveys going back to 2006. Although the DSM and DTM Tile Stamped Tiles products are derived from the point cloud data there may not necessarily be a matching point cloud for each surface model due to historic data archiving processes.

During processing the point cloud classifies the laser returns in the 'ground' and 'surface objects'. Further manual editing undertkaen on the derived digital terrain model (DTM) means the classifed ground points in the point cloud data will not match the final derived DTM.

Data is available in 5km download zip files for each year of survey. Within each downloaded zip file are LAZ files aligned to the Ordinance Survey grid. The size of each tile is dependent upon the spatial resolution of the data.

Please refere to the coverage metadata files for the start and end date flown of a survey as well as additional component information the point cloud contains such as the average point density.

In support of U.S. Geological Survey (USGS) Southwest Biological Science Center researchers, and in coordination with the Bureau of Land Management (BLM) and National Ecological Observatory Network (NEON), the USGS National Uncrewed Systems Office (NUSO) conducted uncrewed aircraft systems (UAS) remote sensing flights over two BLM Assessment, Inventory, and Monitoring (AIM) plots at the NEON Moab site in Utah for multi-scale carbon sequestration research on public lands. The UAS data collected include natural color, multispectral, and hyperspectral imagery, and lidar to capture diverse information about vegetation and soils on drylands. The first site (“site 1”) features intact sagebrush and was mapped on May 3, 2023. The second site (“site 7”) is located on a grazed rangeland environment and was mapped on May 5, 2023. These UAS surveys were conducted in early May 2023 to coincide spatially and temporally with ground-based BLM AIM sampling and airplane-based remote sensing surveys by NEON. This portion of the data release presents discrete lidar point clouds from low-altitude UAS flights at two dryland sites approximately 40 km south of Moab, Utah. A YellowScan Vx20-100 scanner (laser wavelength 905 nm) was flown at an altitude of 31 meters above ground level on a DJI Matrice 600 Pro UAS with approved government edition firmware. The lidar point clouds were post-processed kinematic (PPK) corrected to a concurrently operating Trimble R8s GNSS base station and each point was assigned Red, Gren, Blue (RGB) image values using corresponding natural color orthomosaics at each site. The point clouds were also point classified using a bare-ground classification scheme (0-Created, never classified; 2-Ground) and exported in .las format.

This .las file contains sample LiDAR point cloud data collected by National Ecological Observatory Network's Airborne Observation Platform. The .las file format is a commonly used file format to store LIDAR point cloud data.This teaching data set is used for several tutorials on the NEON website (neonscience.org). The dataset is for educational purposes, data for research purposes can be obtained from the NEON Data Portal (data.neonscience.org).

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.

Click here to access the data directly from the Illinois State Geospatial Data Clearinghouse. These lidar data are processed Classified LAS 1.4 files, formatted to 2,117 individual 2500 ft x 2500 ft tiles; used to create Reflectance Images, 3D breaklines and hydro-flattened DEMs as necessary. Geographic Extent: Lake county, Illinois covering approximately 466 square miles. Dataset Description: WI Kenosha-Racine Counties and IL 4 County QL1 Lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a derived nominal pulse spacing (NPS) of 1 point every 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane, U.S Survey Feet and vertical datum of NAVD88 (GEOID12B), U.S. Survey Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 2,117 individual 2500 ft x 2500 ft tiles, as tiled Reflectance Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema. Ground Conditions: Lidar was collected April-May 2017, 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, Ayers established a total of 66 ground control points that were used to calibrate the lidar to known ground locations established throughout the WI Kenosha-Racine Counties and IL 4 County QL1 project area. An additional 195 independent accuracy checkpoints, 116 in Bare Earth and Urban landcovers (116 NVA points), 79 in Tall Grass and Brushland/Low Trees categories (79 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. Users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Acknowledgement of the U.S. Geological Survey would be appreciated for products derived from these data. These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.Link Source: Illinois Geospatial Data Clearinghouse

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.

Point-wise annotation was conducted on input point clouds to prepare a labeled dataset for segmenting different sorghum plant-organ. Each sorghum plant's leaf, stem, and panicle were manually labeled in 0, 1, and 2, respectively, using the segment module of the CloudCompare software.

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.

Light Detection and Ranging (LiDAR) point cloud of Fairfax County, Virginia collected in 2022. The data was colored with 2021 National Agriculture Imagery Program (NAIP) leaf-on aerial photography and filtered to show first return points, providing a high accuracy, realistic 3D view of trees and buildings. Best efforts have been made to remove noise but some artifacts may still be visible in the data. Building points have been classified as LAS class code 6 for optional removal/filtering in 3D displays.

This public data repository (https://public.spider.surfsara.nl/project/lidarac/MAMBO/) provides the LiDAR point cloud datasets which were clipped using the boundary polygons (shapefiles) of the MAMBO demonstration sites. The raw LiDAR point cloud tiles were first downloaded from the national repository in the respective country based on the approximate location of each demonstration site. The data repository uses the storage services from the Dutch IT infrastructure SURF (https://www.surf.nl/en). The code for downloading, clipping and uploading the LiDAR point cloud datasets is available on GitHub (https://github.com/Jinhu-Wang/Retile_Clip_LAZ).

LiDAR point cloud data for Washington, DC is available for anyone to use on Amazon S3. This dataset, managed by the Office of the Chief Technology Officer (OCTO), through the direction of the District of Columbia GIS program, contains tiled point cloud data for the entire District along with associated metadata.

This layer contains the Point Cloud for LiDAR data in the Hawke's Bay Region, captured between 20 September 2023 to 27 April 2024.

• The DEM is available as layer Hawke's Bay LiDAR 1m DEM (2023).

• The DSM is available as layer Hawke's Bay LiDAR 1m DSM (2023).

• The Point Cloud is also available on OpenTopography as layer Hawke's Bay LiDAR Point Cloud (2023-2024).

• The Index Tiles are available as layer Hawke's Bay LiDAR Index Tiles (2023).

LiDAR was captured for The National Institute of Water and Atmospheric Research Limited (NIWA) by Woolpert betwee 20th of September 2023 to 27 April 2024. These datasets were generated by Woolpert and their subcontractors. Data management and distribution is by 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 geolocated airborne LiDAR point cloud measurements from the Sub-Mesoscale Ocean Dynamics Experiment (S-MODE) conducted approximately 300 km offshore of San Francisco during a pilot campaign over two weeks in October 2021, and two intensive operating periods (IOPs) in Fall 2022 and Spring 2023. S-MODE aims to understand how ocean dynamics acting on short spatial scales influence the vertical exchange of physical and biological variables in the ocean. The Modular Aerial Sensing System (MASS) is an airborne instrument package that is mounted on the DHC-6 Twin Otter aircraft which flies long duration detailed surveys of the field _domain during deployments. MASS includes a high resolution LiDAR, used to characterize the properties of ocean surface topography. The sensor has a maximum pulse repetition rate of 400 kHz, with a +/- 30° cross-heading raster scan rate of 200 Hz. Level 1 LiDAR point clouds are available in .laz format.

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).

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.