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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,662 datasets
Polygon data delineates Water Framework Directive River Water Body Catchments and associated coastal catchments for areas draining directly to coastal waters. The dataset provides attribution for the 2022 classification cycle results and other relevant information for each water body. It was created by the UK Environment Agency using hydrological models based on EA LiDAR data and the Detailed River Network.
A seamless 2-meter resolution raster model of the UK inter-tidal zone, produced by the Environment Agency in 2014. It was created using LIDAR and multibeam SONAR bathymetry to assess coastal changes following the 2013/2014 winter storms. The data is provided as 5km x 5km GeoTiff tiles and an ESRI Image Service.
2017 LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering areas of England at 50cm spatial resolution. Produced by the Environment Agency, it is derived from a merged and re-sampled archive, using the newest, best resolution data from repeat surveys. The data has a vertical accuracy of +/-15cm RMSE and is available in 2km grids.
Environment Agency's LIDAR Composite DSM 2017 is a raster elevation model covering areas of England at 25cm spatial resolution. The dataset is derived from an archive of airborne LIDAR surveys, merged and re-sampled to provide the best possible coverage, with newer, higher-resolution data used where available. Data is presented in metres, referenced to Ordinance Survey Newlyn, with a stated vertical accuracy of +/-15cm RMSE.
2017 LIDAR Composite Digital Surface Model for England at 50cm spatial resolution, produced by the Environment Agency. The dataset is derived from a merged and re-sampled archive, using the newest and best resolution data from repeat surveys, and is updated annually. Data is available as ASCII files in 5km grids, with heights in meters and a vertical accuracy of +/-15cm RMSE.
PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios is a large-scale synthetic video dataset of autonomous-driving scenes generated with NVIDIA's internal Omniverse simulation platform. Each clip is a temporally consistent multi-camera surround capture of one ego vehicle and surrounding traffic participants, paired with per-camera VLM captions. The dataset was created by NVIDIA and was last updated on the platform in May 2026.
Airborne in situ measurements of atmospheric carbon dioxide were collected over California and Nevada on February 10-11, 2016. The data were taken onboard a DC-8 aircraft using NASA's AVOCET instrument to validate the performance of an experimental CO2 Sounder LiDAR. The dataset includes aircraft navigation and flight meteorological data, provided in ICARTT and CSV formats.
CALIPSO's CALIOP instrument provides monthly mean vertical profiles of aerosol optical properties on a uniform spatial grid, focusing on altitudes below 12 km. This Level 3 'All Sky' product, derived from quality-screened Level 2 data, reports aerosol extinction coefficients at 532 nm and aerosol optical depth (AOD). The dataset, part of the A-Train constellation since CALIPSO's 2006 launch, includes profiles for all aerosols and specifically for mineral dust, with data categorized by sky conditions.
Ontario's managed forest zone is covered by airborne single photon LiDAR data captured under leaf-on conditions, with a minimum point density of 25 points per square meter. The Government of Ontario provides this data to support Forest Resources Inventory (FRI) development, including information on tree species, density, heights, and distribution. The dataset was last updated in March 2026.
Procurement processes from the Regional Autonomous Corporation of Guavio, published in detail within Colombia's SECOP I and II systems. The dataset includes columns for contract details, parties involved, guarantees, and physical progress. It is hosted on the Colombian open data portal, www.datos.gov.co, and was last updated on 2026-05-18.
October 2004 to March 2008 data provides global estimates of forest canopy height derived from the GLAS LiDAR instrument aboard NASA's ICESat satellite. The dataset contains canopy height metrics for 18,578 statistically selected forested sites worldwide, processed from over 12 million GLAS waveform observations. It is produced by the ORNL_CLOUD organization and includes country-level summaries.
Late June and July 2008 LiDAR surveys provide point clouds and digital terrain models over the Tapajos National Forest in Para, Brazil. The data covers areas around K67 and K83 eddy flux towers and a deforestation chronosequence, collected to analyze forest canopy structure and the impact of selective logging on biomass and carbon balance. The dataset is associated with the Large-Scale Biosphere-Atmosphere Experiment in Amazonia.
LiDAR point clouds and digital terrain models capture forest canopy structure across three research sites near Manaus, Brazil. Data was collected in June 2008 to monitor the effects of selective logging on forest biomass and carbon balance. The dataset is associated with the Large-scale Biosphere-Atmosphere Experiment in Amazonia and other Brazilian research programs.
Global sea surface salinity data from the NASA Soil Moisture Active Passive (SMAP) satellite, processed by Remote Sensing Systems. The Level 3 product provides gridded, 8-day running mean averages at a 0.25-degree resolution, with data collection ongoing since April 1, 2015. It includes both 40KM and 70KM resolution salinity variables, with the 70KM data recommended for open ocean applications due to lower noise.
Two Saildrone uncrewed surface vehicles, SD-1057 and SD-1058, collected a 76-day multivariate dataset in the Bering and Chukchi Seas from 6 July to 20 September 2021. The mission's primary objective was to understand air-sea covariance scales and validate satellite sea-surface temperature measurements near the sea ice edge. Each vehicle was equipped with instruments measuring atmospheric conditions, ocean temperature, salinity, chlorophyll fluorescence, dissolved oxygen, waves, and near-surface currents via a 300 kHz ADCP.
Crown-BERT dataset contains UAV LiDAR and hyperspectral data from ten sample plots at Maoershan Forest Farm. The data is structured in HDF5 files with crown-level inputs, masks, positional encodings, and one-hot encoded labels for individual tree species classification. Xinbo Wang published this resource in April 2026.
Experimental data from a manuscript on drone routing with hybrid charging and fuzzy time windows. The dataset is 31.6 KB in size and was authored by Yuan Fang. It was last updated on 2026-05-12.
Experimental or simulation data for a Square Hollow Section (SHS) T-joint subjected to slamming loads. The dataset is 352.0 KB in size and was authored by Yongyi Jiang, last updated on May 26, 2026. It is shared under a CC-BY-4.0 license on the figshare platform.
Southern Quebec's terrain slope is classified into 7 categories derived from a 10-meter resolution digital terrain model. The dataset covers the entire Southern Quebec Ecoforest Inventory territory and was created to support Forest Management Investment Program applications. The minimum polygon area is 0.2 hectares.
Quebec's provincial LiDAR acquisition project produced vector layers mapping potential water flow beds based on topography. The data is distributed by water drainage unit (UDH) in Geodatabase or GeoPackage format and is used to support forest operations. It is a preliminary product from the Ministry of Natural Resources and Forests and the Ministry of the Environment.