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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,663 datasets
Field data collected in 2017 and 2018 from Nadaleen Mountain in Yukon provides new insight into the Cambrian–Devonian Bouvette Formation. The dataset includes measured stratigraphic sections, biostratigraphy, and imagery from UAVs to test hypotheses about platform margin reef preservation. These observations contribute to early Paleozoic depositional history and identify a location to study carbonate platform–margin environments.
604 permanent Forest Inventory and Analysis plots in the Penobscot Experimental Forest, Maine, provide the ground truth for these 2012 aboveground biomass estimates. NASA's Goddard Space Flight Center modeled the biomass using LiDAR data from the G-LiHT airborne imager and a novel approach to correct for temporal misalignment between field and remote sensing data. This dataset represents a specific fusion of intensive field inventory and advanced remote sensing for ecological research.
11 high-resolution GeoTIFF maps estimate aboveground biomass for four forested sites in the US for the nominal year 2011. The data, at 20-50 meter resolution, combine field inventory and LiDAR data with modeling approaches. Uncertainty estimates are provided for the Maryland site using two different methodologies.
LiDAR point cloud data from 2005 and 2011 was used to create a 30-meter resolution map of vegetation canopy structure for the Great Smoky Mountains National Park. The dataset, produced by NASA, classifies vegetation types by grouping areas with similar three-dimensional canopy characteristics. The resulting map has been validated against existing vegetation maps for the park.
Giacomo Zanetti provides 3.3 MB of data supporting a paper on CO2 sensing using a symmetrical three-wavelength differential absorption lidar (DIAL) technique. The data, last updated on 2026-05-28, compares this method to a traditional two-wavelength approach.
Gridded 30-meter estimates of aboveground biomass, forest canopy height, and canopy coverage for Maryland, Pennsylvania, and Delaware in 2011. The dataset was produced by NASA using a model-based stratification of leaf-off LiDAR and agricultural imagery to select 848 field sampling sites, with random forest regression models relating field data to LiDAR metrics across three physiographic regions. Pixel-level spatial error estimates and validation against FIA plots and national maps were performed.
Olympic Mountains Experiment (OLYMPEX) campaign data contains vertical profiles of cloud and aerosol properties measured by a multi-wavelength lidar aboard the NASA ER-2 aircraft. The dataset includes extinction profiles, layer optical depth, lidar ratio, and aircraft parameters from November 9 to December 15, 2015. It is produced by NASA as part of the Global Precipitation Mission (GPM) ground validation effort.
Over 1,500 atmospheric profiles were collected during the CPEX-AW field campaign from August 24 to September 28, 2021. This dataset contains measurements of pressure, temperature, humidity, wind speed, and wind direction from DFM-09 radiosondes. It was produced by a joint NASA and ESA effort to calibrate and validate the ADM-Aeolus satellite wind lidar.
Canopy height and elevation data products derived from airborne LiDAR collected over 90 sites on Borneo in late 2014. The dataset covers approximately 100,000 hectares of forested land in Kalimantan, Indonesia. It was produced by NASA as part of an effort to improve Indonesia's national forest monitoring system.
NASA's dataset provides high-resolution canopy height estimates for mangrove forests in the Zambezi Delta, Mozambique. The data were derived from three separate canopy height models using airborne Lidar, stereophotogrammetry with WorldView 1 imagery, and In-SAR techniques with TanDEM-X imagery. Estimates cover the period from October 2011 to May 2014.
NASA's dataset provides high-resolution LiDAR point cloud data collected over mangrove forests in Mozambique's Zambezi River Delta in May 2014. The data is organized into 144 individual 1-by-1-kilometer tiles. This collection supports detailed analysis of coastal vegetation structure and terrain.
Iran, Islamic Republic of data from the World Bank's portal, aiming to shed light on the country's technology base. The dataset includes indicators on research and development, scientific publications, high-technology exports, royalty fees, and patents. It was last updated on 2026-04-28 and is sourced from organizations including UNESCO, the U.S. National Science Board, and the World Intellectual Property Organization.
World Bank Group data aggregates indicators on private markets and trade for Iran. The dataset likely contains metrics on private infrastructure investment, enterprise conditions, business regulations, and international trade flows. It was last updated on 2026-04-28 and is provided under a CC-BY-4.0 license.
World Bank Group data on public sector performance for Iran, Islamic Republic. The dataset likely contains staff assessments of economic management, structural policies, social inclusion, and public sector institutions, along with IMF government finance statistics and tax policy indicators. It was last updated on 2026-04-28 03:53:41.408899.
Iran, Islamic Rep. external debt data from the World Bank's Quarterly External Debt Statistics and Quarterly Public Sector Debt databases. The dataset provides a detailed picture of debt stocks and flows for developing countries, with data gathered from national statistical organizations, central banks, and multilateral institutions. It was last updated on 2026-04-28.
World Bank Group trade data for Iran, Islamic Republic, last updated on 2026-04-28. The dataset is part of the Transparency in Trade Initiative, which aims to provide free access to data on country-specific trade policies to support development goals. It is available in CSV format under a CC-BY-4.0 license.
Alana Lutz created a dataset of 3,972 highwall segments from surface coal mining in Central Appalachia. The data was generated using a LiDAR-based remote sensing workflow on USGS 3D Elevation Program data across 55 counties in Kentucky, West Virginia, and Virginia. It includes polygon geometries and attributes for estimating reclamation costs and was last updated in May 2026.
Column-weighted carbon dioxide concentration data retrieved by the Atmospheric Environmental Monitoring Satellite (AEMS/DQ-1). The dataset includes high-precision XCO2 measurements from the ACDL lidar payload, with validation involving 170 overpasses for DQ-1 and 91 for OCO-2. The data was last updated on 2026-05-12.
January 1 through February 26, 2020 data contains Doppler velocity and backscatter intensity measurements collected by the Stony Brook University Doppler LiDAR. This dataset was produced for the multi-year Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign, which studied snowstorm formation and evolution along the U.S. Atlantic Coast from 2020 to 2023. It is provided by the National Aeronautics and Space Administration in netCDF-4 format.
The Bagmati–Nakkhu confluence area in Lalitpur Metropolitan City, Nepal, is the focus of this dataset. It contains a 0.5 m resolution UAV-derived Digital Elevation Model and RTK-surveyed flood mark points from a 2024 flood event. The data was generated by Rishav Khatiwada for a study submitted to the ISPRS International Journal of Geo-Information.