Loading...
Loading...
Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,663 datasets
NASA's dataset provides aboveground biomass estimates for mangrove forests in Mozambique's Zambezi River Delta. Estimates derive from field plot measurements taken in 2012-2013 and high-resolution airborne LiDAR canopy surveys from 2014. The dataset includes plot-level biomass and a canopy height model for the delta region.
NASA's dataset provides geospatial estimates of forest aboveground biomass (AGB) for the Atchafalaya and Terrebonne Basins in Louisiana. The data were generated by applying a machine learning regression model, trained on in-situ plot data from 2015 and 2021, to airborne AVIRIS-NG hyperspectral and UAVSAR radar mosaics. The final product consists of cloud-optimized GeoTIFF maps derived from these combined remote sensing sources.
Approximately 0.8963 million kilometers of roads in Iran are mapped, with AI-derived estimates classifying 16.1911% as paved and 7.6254% as unpaved. The dataset, created by the Heidelberg Institute for Geoinformation Technology (HeiGIT), combines OpenStreetMap data with deep learning predictions from Mapillary imagery and urban classification layers. It was last updated on March 17, 2026.
FLUID is a dataset of fine-grained trajectories with a focus on dense traffic conflicts at typical urban signalized intersections. It contains approximately 5 hours of drone-captured data covering over 20,000 traffic participants across three distinct intersection types. The dataset was authored by Yiyang Chen and last updated on 2026-05-02.
9.5 KB of analytical results for a multi-user UAV-assisted non-orthogonal multiple access system operating over Rician fading channels. The data, authored by Sk Thaherbasha and last updated in May 2026, includes derived closed-form expressions for outage probability, incorporating hardware impairments, imperfect channel state information, and non-ideal successive interference cancellation.
The CAMEX-4 MIPS Microwave Profiling Radiometer dataset from the University of Alabama in Huntsville provides mobile atmospheric profiles. It includes vertical profiles of temperature, water vapor, and liquid water from the surface to 10 km altitude, measured approximately every 15 minutes. The data was collected by NASA during the CAMEX-4 field campaign.
Eight days of mission reports from the NASA DC-8 aircraft during the CPEX-AW field campaign. These documents detail daily objectives, flight times, and instrument performance for the joint NASA-ESA campaign to validate the ADM-Aeolus wind Lidar satellite. Data covers the period from August 20 to August 27, 2021.
Fourteen flights between August 15 and September 12, 2006 collected atmospheric profiles during the NASA African Monsoon Multidisciplinary Analyses campaign. The dataset contains Differential Absorption Lidar measurements of water vapor mixing ratio and aerosol scattering ratio from the NASA DC-8 aircraft, along with derived parameters like relative humidity and aerosol optical thickness.
Yukon drone lidar surveys provide 30 cm resolution bare-earth Digital Terrain Models over segments of the Eastern Denali fault. The Yukon Geological Survey and Kluane First Nation collected the data to evaluate geothermal energy potential near Burwash Landing. The data reveals dextral offsets between 5 and 75 meters and vertical separation up to 20 meters.
Colauntangle Post-cutoff dataset contains 300 synthesized tangled commits collected from open-source Java and C# projects. The benchmark is constructed by combining pairs of atomic commits using git cherry-pick, following the methodology of the original Flexeme benchmark. Each data point contains a tangled commit and its corresponding atomic commits, which serve as ground-truth decomposition answers.
Hui Wu published judgment matrices on figshare in May 2026. The dataset supports research on selecting optimal multi-sensor fusion schemes for unmanned aerial vehicle (UAV) monitoring of highway geohazards. It applies an improved AHP-TOPSIS method to evaluate sensor combinations for rural and urban highway areas.
Hui Wu's dataset provides an improved Analytic Hierarchy Process (AHP) evaluation metric weights table for sensor fusion screening. The 9.5 KB XLS file, last updated in May 2026, supports research into optimizing unmanned aerial vehicle (UAV) sensor combinations for monitoring highway geohazards in rural and urban areas.
The Ministry of Natural Resources and Forests produced vector layers of riparian ecotones starting in 2020. These layers delineate transition zones between aquatic and forest environments using a canopy height model and topographic humidity index derived from aerial LiDAR, integrated with southern Quebec's ecoforest map data. The methodology was developed in collaboration with Laval University's forest hydrology laboratory.
185.8 MB of semantically structured urban data integrated into a machine-readable knowledge graph. The Autonomous Vehicle Knowledge Graph (AVKG) is organized into five subgraphs covering road networks, incidents, activities, points of interest, and operators, stored in a GraphDB triple store. Author Huihai Wang published the dataset on figshare in April 2026 under a CC-BY-4.0 license.
776 publicly available autonomous vehicle collision reports from the California Department of Motor Vehicles, analyzed by Liu Yang. The dataset, last updated in April 2026, categorizes risk factors into vehicle information, collision details, and road/environmental characteristics. It employs statistical and Bayesian network analysis to explore causal chains and collision severity.
DTM Flow Monitoring by IOM Afghanistan tracks mobility patterns at border points with Iran and Pakistan. The data covers ten crossing points, including four on Afghanistan's National Highway, from January 2024 to May 2026. It counts total movements, not unique individuals, meaning a person leaving and returning counts as two separate flows.
NASA's SMAP satellite provides global sea surface salinity data starting April 1, 2015, with an 8-day moving average to reduce noise. Version 5.0 introduces formal uncertainty estimates and improved sea-ice edge detection using direct AMSR-2 brightness temperature measurements. The primary product is a gridded map at 0.25-degree resolution, offering a 70km smoothed field recommended over a noisier 40km alternative.
CALIPSO, a joint NASA-CNES satellite launched in 2006, provides vertical profiles of clouds and aerosols to study their impact on Earth's climate. The Level 2 data product contains 5 km aerosol layer observations from the CALIOP lidar instrument. This data is part of the international A-Train satellite constellation for coincident Earth observations.
Building footprints for the territory of Laval, Quebec, produced by the City of Laval. The dataset includes fields for building type, name, release date, and the digitization method used for each structure. Data is provided in multiple geospatial formats including SHP, GEOJSON, and KML.
Five forested areas in Paragominas, Para, Brazil, are covered by this dataset, which provides raw LiDAR point cloud data and derived Digital Terrain Models (DTMs). Data collection spans the years 2012, 2013, and 2014 across specific sites, including Fazenda Cauaxi and Fazenda Andiroba. The dataset is provided by the National Aeronautics and Space Administration (NASA) and includes shapefiles delineating the LiDAR coverage areas.