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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,664 datasets
October 4 to November 1, 2016, data collected by Leading Edge Geomatics using a Leica Chiroptera II sensor. The dataset contains 7,030 tiles covering 234 square miles around Marthas Vineyard and Nantucket Islands, Massachusetts. Data is in LAS 1.2 format with classifications for ground, water, bathymetric bottom, and noise points.
1,224 500 m x 500 m lidar tiles covering approximately 85 square miles along the shores of Tarpon Springs, Florida. The data was collected by the National Oceanic and Atmospheric Administration using a Riegl VQ880G sensor from February 11, 2016 through February 14, 2016. It includes topobathy data in LAS 1.2 format with classifications for ground, water surface, bathymetric bottom, and noise.
195 square miles of combined topographic and bathymetric lidar data collected along five Virginia rivers from October 2023 to November 2024. The National Oceanic and Atmospheric Administration commissioned this survey, which resulted in 9,548 individual 500-meter tiles. Data points are classified into categories including ground, water surface, bathymetric bottom, and submerged objects.
G-LiHT Metrics V001 provides over 80 raster layers of lidar-derived height, density, and return statistics for forest analysis. The data product is generated from the NASA Goddard LiDAR, Hyperspectral, and Thermal Imager airborne system. It covers forest communities across the Conterminous United States, Alaska, Puerto Rico, and Mexico.
The Scottish Public Sector LiDAR (Phase 5) dataset is a point cloud captured by Fugro for Scottish Power Energy Networks from 2020 to 2021. The Scottish Government procured the dataset for public use in 2021. It has a specified point density of 4 points per square metre.
Fugro captured this LiDAR data for Scottish Power Energy Networks from 2021 to 2022 to monitor overhead power cables. The Scottish Government procured the dataset for public use in 2022. It consists of a Digital Surface Model derived from the original point cloud data.
Scottish Public Sector LiDAR (Phase 5) is a Digital Surface Model (DSM) derived from point cloud data. The Scottish Government procured this dataset for public use in 2021. The data was initially captured by Fugro for Scottish Power Energy Networks from 2020 to 2021 to monitor overhead power cables.
Fugro captured this Scottish Public Sector LiDAR data in 2022 for Scottish Power Energy Networks to monitor overhead power cables. The Scottish Government, with a contribution from SEPA, procured the dataset for public use the same year. This release is the Digital Terrain Model derived from the original point cloud.
LiDAR point cloud data captured for Scottish Power Energy Networks from 2021 to 2022. The Scottish Government procured the dataset for public use in 2022. The data has a density of 4 points per square metre and was collected to monitor overhead power cables.
November 13 to December 7, 1991, this dataset contains Volume Imaging Lidar (VIL) images of cirrus cloud scans with a 120 km extent, collected during the FIRE Cirrus 2 field experiment in Coffeyville, Kansas. The data was created by the National Aeronautics and Space Administration (NASA) to improve cloud and radiation models. It is part of the First ISCCP Regional Experiments designed to study cloud life cycles and interactions with satellite data.
The First ISCCP Regional Experiment (FIRE) Marine Stratocumulus NASA ER-2 Cloud Lidar System Data contains cloud top and ground height calculations from a 1987 airborne campaign. Data includes time, position, and plane height parameters, with undetected values signified by -9.9. This dataset was produced by the National Aeronautics and Space Administration to improve cloud and radiation models.
Altitude vs. time images of cirrus clouds collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign in Coffeyville, Kansas. The data were gathered by the Volume Imaging Lidar (VIL) and sampled at 5 km intervals in cross-wind scans. NASA produced this dataset as part of a series of intensive field observations designed to improve cloud and radiation models.
UNDP Human Development Reports Office (HDRO) provides human development indicators for Iran, including the Human Development Index (HDI) and the 2019 Global Multidimensional Poverty Index (MPI). The HDI measures average achievement in health, education, and standard of living, while the MPI assesses poverty across multiple dimensions. The dataset was last updated on 2026-03-04.
Population statistics for Iran at the country, province (ostΔn), and district (baxΕ‘) administrative levels for the reference year 2016. The data is provided by OCHA Middle East and North Africa (ROMENA) and is structured for linkage with corresponding geographic boundary layers. It was last updated on the platform in March 2026.
Surface roughness data for Arctic sea ice is derived from NASA Operation IceBridge Airborne Topographic Mapper (ATM) lidar elevation surveys. The dataset contains statistical distributions of roughness for 10 km flight segments, collected during annual low-altitude campaigns between March and May from 2009 to 2018. It is produced by NASA and hosted by the National Oceanic and Atmospheric Administration.
AMSRIce06 Airborne Topographic Mapper (ATM) Lidar Data, Version 1 contains point cloud measurements collected by a P3 aircraft. The data capture sea ice conditions in the Chukchi and Beaufort Seas and snow cover off the northern coast of Alaska. Documentation and support for this dataset are noted as limited, as they were provided solely by the Principal Investigator(s) and not further reviewed by NSIDC.
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 1mΒ² pixel resolution where LiDAR coverage existed. Accuracy was assessed against field observations, with detailed township-level reports available.
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.