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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,663 datasets
A land evaluation for commercial peach palm (chontaduro) cultivation in Colombia's Guaviare department, developed under agreement 3045449 of 2021 between UPRA and the Guaviare Governor's Office. The dataset likely contains categorical land suitability ratings and area statistics derived from soil, climate, and land-use information at a 1:100,000 scale. The data was last updated on 2026-05-18.
Guaviare Department in Colombia is the focus of this land evaluation dataset for pineapple (Ananas comosus L.) cultivation. The data was produced through a 2021 agreement between UPRA and the Guaviare Governor's Office, applying a 1:100,000 scale agricultural land suitability methodology. It contains polygon-level classifications of land aptitude, likely derived from soil studies, land cover maps, and climate data.
Ontario, Canada hosts this dataset from the GPM Cold-season Precipitation Experiment (GCPEx), collected from January 14 to February 29, 2012. It contains measurements from the ADMIRARI scanning radiometer, which records brightness temperature at three frequencies and two polarizations, alongside co-located radar reflectivity profiles and cloud lidar data. The dataset was produced by NASA for validating satellite precipitation retrievals.
261 peer-reviewed publications from 2010 to 2025 form the curated corpus for this bibliometric analysis. Wei Sheng Chong compiled this dataset to support a manuscript on the evolution of UAV remote sensing applications in coastal environments. The raw data tracks temporal trends, collaborative patterns, and technical system details to ensure transparency and serve as a baseline for future meta-analyses.
Cudal, Australia is covered by a 3D LiDAR mesh scene layer package with a 50mm resolution, published in November 2022. The dataset is hosted by Spatial Services (DCS) on the data.gov.au platform and is accessible via an ESRI SceneServer API. Its spatial reference systems include GDA94, GDA2020, and WGS84.
NASA's Synergistic TEMPO Air Quality Science (STAQS) mission collected a multi-instrument dataset to validate and enhance observations from the TEMPO satellite. The dataset includes measurements from aircraft, drones, sondes, and ground stations targeting urban areas like Los Angeles, New York City, and Chicago during summer 2023. It provides repeated high-resolution mapping of pollutants including nitrogen dioxide (NO2), formaldehyde (HCHO), ozone, and aerosols.
40-meter riparian zone polygons represent areas where vegetation cover is less than 20% over at least a 10x10 meter gap. The Department of Environment and Primary Industries derived this data from 15cm aerial photography and LiDAR for a state-wide mapping project between 2010 and 2013. It supports the assessment of river condition in Victoria, Australia.
A 2026 study by Madhusudhan Adhikari compared three UAV-based weed detection methods against a ground-based camera system. The dataset likely contains performance metrics such as prediction accuracy (MAE, RMSE, R²), omission rates, and Bland-Altman analysis results from three mapping dates in a summer fallow field. The data supports research into the operational feasibility of UAV-derived weed maps for site-specific management.
Between September 1995 and July 1996, this dataset provides ~100-meter resolution Synthetic Aperture Radar (SAR) image mosaics of South America, specifically covering the Amazon River Basin during low and high flood seasons. It constitutes the first-ever high-resolution, single-season coverage of the entire basin, enabled by the cloud-penetrating properties of radar. The data are provided as 66 GeoTIFF files, mosaicked from approximately 50 JERS-1 scenes per tile into 34 tiles for each season.
ITD-UAV is a 3.5 GB dataset of aerial images for maglev track intrusion detection, released by Jiajing Xu. It is the first publicly available dataset for this specific task. The annotations and supplementary information are organized in the COCO format.
Northern Ireland's entire coastline is covered by this natural colour orthophotography dataset, extending approximately 200 meters landward from the high water mark and including the intertidal zone. The imagery was captured in 2021 as part of a 3D coastal survey and has been ortho-rectified to remove geometric distortion, providing a uniform 10cm ground resolution. This dataset offers a detailed, geometrically accurate visual baseline for coastal analysis.
24.6 MB of simulation and experimental data for an ultrasonically-actuating amphibious robot. The dataset, authored by Zhaochun Ding, includes results for designing terrestrial and aquatic transducers, terrestrial and aquatic locomotion experiments, and vibration velocity distributions. It was last updated on May 29, 2026.
NASA's dataset provides high-resolution estimates of above-ground woody biomass for Sonoma County, California, USA, for the nominal year 2013. Biomass density in megagrams per hectare was modeled at 30-meter resolution using airborne LiDAR data and field plot measurements. The dataset includes uncertainty estimates derived from 1,000 model iterations per pixel.
March 1998 and March 2005 LiDAR surveys provide 100-meter resolution GeoTIFFs of land-use, canopy height, and aboveground carbon estimates for La Selva Biological Station in Costa Rica. A supplementary look-up table relates modeled height changes to stand characteristics like age and carbon content. NASA produced this dataset to test the scale-dependency and accuracy of the Ecosystem Demography (ED) model for predicting vegetation dynamics and carbon flux.
ANUGA 2D depth-integrated hydrodynamic model outputs and run-scripts for the Atchafalaya basin in Louisiana's Mississippi River Delta. The dataset contains over a month of simulation results from three field campaigns in fall 2016, spring 2021, and fall 2021. NASA produced this resource, which was calibrated using in-situ gauges and remote sensing data.
2021 data provides an updated multisource digital elevation model for the Atchafalaya and Terrebonne river basins in coastal Louisiana. It integrates sonar, bathymetric, and LiDAR data from the Delta-X and Pre-Delta-X campaigns, CPRA SWAMP, NOAA, and USGS. The dataset includes elevation values, a water/land mask, source flags, and weighting factor layers in cloud-optimized GeoTIFF format.
NASA provides 1 km resolution maps of woody vegetation cover and biomass for Sub-Saharan Africa from 2000 to 2004. The dataset integrates field measurements, Google Earth imagery, MODIS optical data, Q-SCAT microwave measurements, and spaceborne lidar. It was created using canopy cover observations, predicted woody cover, canopy height estimates, and tree allometry equations.
Fall 2016 lidar data from NASA's Pre-Delta-X campaign provides water surface elevation profiles for river channels between Wax Lake and the Gulf of Mexico. The dataset offers time-specific water levels in meters, calibrated with in-situ field measurements and referenced to NAVD 88 and WGS 84 geoids. It was produced by NASA using an Airborne Snow Observatory (ASO) lidar instrument.
NASA's 1992 TRACE-A campaign deployed a DC-8 aircraft equipped with 19 instruments, including a Differential Absorption Lidar (DIAL), to investigate high ozone concentrations over the South Atlantic. The dataset likely contains merged in-situ and remotely sensed measurements of ozone, aerosols, CO, CH4, N2O, CO2, and atmospheric pressure from both aircraft and dropped ozonesondes. This data collection was part of NASA's Global Tropospheric Experiment (GTE), conducted in partnership with the Brazilian Space Agency (INPE).
2021 airborne LiDAR data provides a precise and accurate Digital Surface Model of the Northern Ireland coastline. The survey captured the intertidal zone and extended approximately 200 meters landward of the high-water mark. This dataset represents the topographic surface, including buildings and vegetation, for the NI 3D Coastal Survey.