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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
2,016 datasets
A 2015-2016 habitat model for Limber Pine was developed under contract for Alberta Forestry and Parks. It incorporates variables like elevation, aspect, slope, landscape mesotopography, and LiDAR-derived canopy height, with a 1m² pixel resolution where LiDAR coverage existed. Accuracy was assessed against field observations, with detailed township-level reports available.
VisDrone-V2 is a dataset hosted on Kaggle. Its title suggests it is a second version of a dataset focused on visual data captured by drones, likely for computer vision tasks. The dataset's specific contents, scale, and origin require verification after download due to minimal provided metadata.
Dekadal Normalized Difference Vegetation Index (NDVI) indicators for Iran are provided here at sub-national administrative levels by the World Food Programme. The data utilizes NASA MODIS Collection 6.1 imagery from Aqua and Terra satellites to monitor vegetation health and anomalies over 10-day intervals.
The DEVOTE project conducted eleven science flights in September and October 2011 to collect aerosol and cloud measurements. NASA scientists used High Spectral Resolution Lidar (HSRL) on a UC-12 aircraft to validate and improve retrieval algorithms for the CALIPSO and ACE satellite missions. Data collection is complete.
July 1982 to January 1984 data from NASA Langley Airborne Lidar flights conducted after the El Chichon volcanic eruption. The dataset, provided by the National Aeronautics and Space Administration, contains atmospheric measurements in ASCII format.
A dataset of LiDAR point clouds for autonomous driving research, published on Kaggle. The title suggests it is likely derived from the KITTI Vision Benchmark Suite, which is a standard resource for computer vision in robotics. Specific details on size, collection dates, and annotations require verification from the dataset files.
A catalog of 216 primary sources ingested into the Islamic Historical Corpus, created by IslamStories. The manifest lists authentication tiers and chunk counts for each source but does not include copyrighted translation text. The dataset page was last updated on April 19, —.
Humanitarian funding flows and financial requirements for Iran are documented in this OCHA Financial Tracking Service (FTS) resource. It captures donor-to-recipient transactions and maps them against specific humanitarian response plan requirements. The data is provided as a UTF-8 encoded CSV and reflects ongoing financial tracking as of March 2026.
Reboot Hub DJI Drone Specs and Used Price Index aggregates price data for DJI aircraft models. The dataset summarizes 251 catalog configurations into 43 model-level aggregates. It was sourced from the Kaggle platform, but the author, organization, and last update date are unknown.
VisDrone2019-DET Pseudo-Depth Maps is a dataset likely derived from the VisDrone2019 object detection benchmark. The dataset appears to contain depth information, possibly estimated or generated, corresponding to aerial images captured by drones. It is hosted on Kaggle, but specific details about its size, creation method, and exact content are not provided in the available metadata.
Lidar data from Sao Jose dos Campos, Brazil, collected from 1972 to the present day. The dataset includes aerosol backscatter ratios from 15-30 km altitude, sodium densities from 75-105 km, and atmospheric density and temperature profiles from 35-70 km. Data was gathered by the CEOS_EXTRA organization using lidar systems at 589.0 nm and 593.0 nm wavelengths.
Arctic Ocean sea ice and Alaskan coastal snow cover are measured by this dataset. It contains airborne lidar point cloud data collected by the Airborne Topographic Mapper instrument on a P3 aircraft over the Chukchi and Beaufort Seas. The data likely includes surface elevation and roughness measurements for studying cryospheric changes.
Riseholme Vineyard UAV RGB Segmentation Dataset consists of RGB images captured by an unmanned aerial vehicle. The images are labeled for posts, vines, and rows, likely for agricultural monitoring and computer vision tasks. The dataset's author, organization, and specific scale are not provided in the input.
A 2021 airborne LiDAR survey captured the Northern Ireland coastline, including the intertidal area and extending approximately 200 meters landward of the high-water mark. This dataset is the Digital Surface Model derived from that survey, providing data on coastal morphology. The data is provided by OpenDataNI under the OGL-UK-3.0 license and was last updated in March 2026.
2019 - 2020 NOAA NGS Topobathy Lidar DEM: Hurricane Michael is a topobathymetric digital elevation model covering approximately 2,120,060 acres of the Florida Panhandle. The data were collected by contractors including NV5 and Dewberry using a Leica Chiroptera 4X system between November 2019 and July 2020. It is provided in geoTIFF format at a 1-meter horizontal resolution.
VisDrone dataset v2 is a collection of drone-captured images and video sequences. It is hosted on Kaggle and its platform tags suggest a focus on computer vision tasks like object detection. The dataset's specific scale, collection method, and temporal coverage are not detailed in the available metadata.
Drone Vehicle Detection Dataset is a collection of images for object detection tasks, published on Kaggle. The dataset likely contains aerial imagery for identifying vehicles from a drone's perspective. Specific details on size, annotation format, and collection methodology are not provided in the available metadata.
A dataset derived from the KITTI Vision Benchmark Suite, a standard resource for autonomous driving research. The dataset is published on Kaggle. Its specific version is labeled as v1.4, but detailed metadata such as column descriptions, sample data, and file formats are not provided.
DPT KITTI Epoch 1 Handoff v1.4 is a dataset published on Kaggle. The title and platform tags suggest it contains computer vision data, likely related to autonomous driving and the KITTI benchmark. The dataset's specific content, size, and origin are not detailed in the available metadata.
DPT T-KITTI Checkpoint Handoff is a dataset hosted on Kaggle. The title suggests a connection to the KITTI vision benchmark suite, likely containing sensor data for autonomous driving tasks. The dataset's specific content, size, and creation details are not provided in the available metadata.