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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
2,016 datasets
Fifteen-minute averaged 3-D wind profiles and cloud data were collected by the University of Alabama in Huntsville Mobile Integrated Profiling System during the CAMEX-4 campaign. The dataset includes backscatter power and up to three cloud base heights measured by a lidar ceilometer. It is hosted by the GHRC DAAC and was last updated in March 2026.
nuReasoning is a reasoning-centric multimodal dataset for evaluating and training end-to-end driving systems. It is designed to help models connect perception, map context, actor motion, ego state, route intent, and safety constraints to interpretable driving decisions. The dataset was created by qixuewei and was last updated on May 7, 2026.
NOAA's 2021 bathymetric lidar dataset for Sleeping Bear Dunes National Lakeshore, Michigan, provides a classified point cloud in LAS v.1.4 format. The data was acquired on August 31 and September 3, 2021, using a Leica HawkEye4X sensor by contractors Woolpert, Inc. and NV5, with a vertical accuracy of less than or equal to 15 cm RMSE for bathymetric points. It includes classifications for ground, water surface, bathymetric points, and submerged objects.
A bare earth digital elevation model (DEM) derived from high-resolution LiDAR data collected for four 'Sentinel Sites' within the Great Bay National Estuarine Research Reserve in New Hampshire. The data was collected by Air Shark for NOAA's Office for Coastal Management between May 1 and May 9, 2019, with Quantum Spatial as the contractor. The DEM represents the earth's surface with vegetation and human-made features removed, with some areas of interpolated elevation data.
2015 airborne lidar data covering approximately 500 square miles in Lowndes County, Georgia, collected by Woolpert, Inc. under a NOAA contract. The dataset includes classified LAS point clouds, four-foot pixel raster digital elevation models (DEMs), hydrologic breaklines, and flightline vectors. Deliverables also encompass survey control data, processing reports, and FGDC metadata files.
A 2-meter resolution Digital Elevation Model (DEM) derived from classified topo-bathy lidar point clouds collected over Sleeping Bear Dunes National Lakeshore in August and September 2021. Woolpert, Inc., contracted NV5 to acquire the data using a Leica HawkEye 4X sensor, aiming for a vertical accuracy of less than or equal to 15 cm RMSE for bathymetric measurements. The dataset is intended to support new benthic mapping products using the Coastal and Marine Ecological Classification Standard (CMECS).
NOAA Coastal Services Center contracted Woolpert, Inc. to collect high-resolution LiDAR elevation data for Burke, Richmond, Lincoln, and Columbia counties in Georgia in 2011. The data includes classified LAS point clouds and hydrologically flattened raster DEMs with a nominal pulse spacing of 1.0 meter and a 4-foot pixel resolution. Final products were delivered in ESRI Floating Point Grid and later converted to GeoTIFF format with vertical units in feet.
Florida's coastal region from Miami to the Marquesas Keys is covered by this 1-meter resolution topobathymetric digital elevation model (DEM). The data were collected by Quantum Spatial, Inc. for NOAA across 85 missions between November 2018 and March 2019, covering approximately 1,381,270 acres. The final dataset consists of 300 tiled DEMs derived from classified LiDAR points for ground, bathymetric bottom, and submerged objects.
The Hayabusa spacecraft's LIDAR altimeter measured the range between the spacecraft and asteroid Itokawa. This dataset includes Experiment Data Records (EDRs) and Calibrated Data Records (CDRs) from the mission. Version 2.0 features a new CDR optimized by minimizing offsets between the LIDAR data and a high-resolution shape model.
A multi-modal driving dataset focused on extreme, critical, and adverse-condition driving scenarios. It was released by the Intelligent Chassis Team at Tsinghua University's School of Vehicle and Mobility. The dataset includes human driving data as well as autonomous driving data, last updated on the platform in April 2026.
Natural hazard statistics for the Islamic Republic of Iran aggregated by year and disaster subtype, produced by the Centre for Research on the Epidemiology of Disasters (CRED). The records track human impact and economic damage from events occurring within the country, with updates maintained through March 2026.
OCHA Field Information Services Section (FISS) provides geospatial boundaries for Iran at two administrative levels. The dataset contains 31 provinces (Admin 1) and 429 districts (Admin 2). It was last reviewed for accuracy in October 2024 and is part of the global subnational administrative boundaries collection.
A dataset from the Autonomous Space Robotics Laboratory (ASRL) for developing aquatic autonomous navigation algorithms. It includes synchronized data from a 360-degree radar, a 128-beam lidar, a stereo camera, imaging sonar, motor inputs, and GNSS, collected on lakes and reservoirs in Ontario, Canada. The data is hosted on AWS Open Data and released under a CC-BY-4.0 license.
Latency and transmission evaluation records for the EE8204 V2X image-captioning project. The dataset likely contains performance metrics for vehicle-to-everything communication systems. Its author, organization, and specific temporal or geographic scope are unknown.
Arabic speech data comprising 7,168 hours of validated audio across approximately 3,957,670 segments from 1,229 books. The dataset, created by AlgoRythmetic, was last updated on April 21, 2026. Audio is provided in 16 kHz mono FLAC format and is organized into 2,639 parquet shards.
Anti-Drone RF UAV Signals Clean Balanced 12GB is a dataset of radio frequency signals related to unmanned aerial vehicles, published on Kaggle. The dataset title suggests it contains processed and balanced data for anti-drone applications. Its specific origin, collection method, and temporal coverage are not detailed in the available metadata.
St. Croix, U.S. Virgin Islands, was the location for this radiosonde dataset collected during the Convective Processes Experiment – Aerosols & Winds (CPEX-AW) field campaign from August 19 to September 14, 2021. It provides vertical profiles of atmospheric pressure, temperature, relative humidity, wind speed, and wind direction from DFM-09 instruments. The primary purpose was the post-launch calibration and validation of the European Space Agency's ADM-Aeolus wind Lidar satellite.
Building outlines representing roof areas for the City of Greater Geelong, derived from LiDAR and photogrammetry. The dataset includes attributes for approximate building height in metres and year of construction. It is published and maintained by the City of Greater Geelong, with a last recorded update in April 2026.
Roof area outlines for buildings were identified and measured using LiDAR analysis and photogrammetry. The dataset includes attributes for approximate building height in meters and the year of construction. It is produced and maintained by the City of Greater Geelong, with a recent update in April 2026.
Data from the NASA Cold Land Processes Experiment (CLPX) includes color infrared orthophotography at 6-inch pixel resolution, raw and filtered lidar elevation returns, and 0.5-meter elevation and 0.1-meter snow depth contours. The dataset is produced by the National Snow and Ice Data Center (NSIDC) and was last updated on the platform in March 2026. It supports research into snowpack properties and terrain modeling.