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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
2,003 datasets
River condition in Victoria is assessed every 5 years using the Index of Stream Condition. The Department of Environment and Primary Industries developed this 2010-13 state-wide mapping project using 15cm aerial photography and LiDAR to derive bare ground metrics. This table provides statistical summaries for the bare ground metric at 100-meter river sections, designed to join with river centerline data.
Channel Transects are line features created every 25 meters along Victorian rivers to assess cross-sectional statistics like area and volume. The Department of Environment and Primary Industries developed this dataset using remote sensing data, specifically 15cm aerial photography and multi-pulse LiDAR, between 2010 and 2013. It supports the Index of Stream Condition, a five-year assessment of river health focusing on physical form and riparian vegetation metrics.
Victoria, Australia's river condition was assessed using the 2010 Index of Stream Condition (ISC). The dataset contains river centre line features divided into 100-meter sections, with metric statistics for physical form and riparian vegetation derived from LiDAR and aerial photography. It was created by the Department of Environment and Primary Industries (DEPI) from a mapping project conducted between 2010 and 2013.
A statistical summary table for the Fragmentation Metric at the 100-meter section level, part of the 2010 Index of Stream Condition assessment for Victoria, Australia. The table is designed to join to a river centerline feature class. It was created by the Department of Environment and Primary Industries using remote sensing data, including 15cm aerial photography and LiDAR, collected between 2010 and 2013.
A statistical summary table for the Bare Ground metric at the river reach level, part of Victoria's 2010 Index of Stream Condition assessment. The Department of Environment and Primary Industries developed the data using remote sensing from 15cm aerial photography and multi-pulse LiDAR collected between 2010 and 2013. This table is designed to join to a river centerlines feature class for spatial analysis.
The ISC2010_RIVER_CENTRELINE_R dataset contains line features representing the center of river reaches assessed in the 2010 Index of Stream Condition for Victoria. The Department of Environment and Primary Industries (DEPI) developed this data using remote sensing from 15cm aerial photography and LiDAR collected between 2010 and 2013. It serves as a spatial key to join with other tables containing physical form and riparian vegetation metric statistics.
The 2010 Index of Stream Condition dataset provides statistical summaries of vertical vegetation layering within a 40-meter riparian zone for rivers in Victoria, Australia. It was created by the Department of Environment and Primary Industries using remote sensing data, specifically 15cm aerial photography and multi-pulse LiDAR, collected during a state-wide mapping project from 2010 to 2013. The table is designed to join with river centerline feature classes for spatial analysis.
Structure1 represents vegetation cover for shrubs (1.5m-5m) and trees (>5m) along Victorian rivers. The Department of Environment and Primary Industries developed this data using 15cm aerial photography and multi-pulse LiDAR collected between 2010 and 2013. This statistical summary table is designed to join to river centerline feature classes for assessing the Index of Stream Condition.
ÍNDICE DE INFORMACIÓN CLASIFICADA Y RESERVADA ACUAVALLE S.A. E.S.P. is an inventory of public information generated, obtained, acquired, or controlled by the obligated entity that has been classified as confidential or reserved. The index is maintained according to Law 1712 of 2014 (Transparency Law) and must be updated whenever information is classified or declassified. The dataset is published by www.datos.gov.co and was last updated on 2026-05-18.
A Spanish-language audio dataset for controlling a robotic arm, containing recordings from 20 speakers. It includes 30 WAV files per speaker, each labeled with speaker ID, gender, emotion (angry, neutral, sad), and one of 10 specific movement commands. The dataset was created by Teth Azrael Cortes Aguilar and last updated on 2026-05-06.
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.
A benchmark dataset for studying camera-based perception in autonomous driving under varying sensor configurations. It is created using the CARLA simulator to model real-world fleet variations in camera placement, orientation, field of view, and count. The dataset was authored by timb2001 and last updated on 2026-06-25.
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.
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.
Wuhan University researchers led by Yun He produced lidar temperature data for atmospheric refraction correction. The data is intended for use in millimeter-level precision lunar laser ranging experiments. The dataset is available under an Open Access license.
Miguel Sanchez Gomez from the University of Colorado Boulder provides data to recreate lidar figures from a Wind Energy Science article. The data likely contains point cloud measurements of wind flow. It is shared under an Open Access license to support reproducible research in wind energy.
EgoDyn-Bench is a physics-grounded visual question answering benchmark for evaluating Vision-Language Models on trajectory-based dynamics reasoning in autonomous driving. The dataset artifacts are hosted by TUM-AVS, with a last update recorded on 2026-07-09. A portion of the data is derived from the nuScenes dataset.
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.
MolmoAct2-BimanualYAM is a large-scale collection of bimanual robot manipulation demonstrations created using LeRobot. The dataset contains more than 720 hours of training demonstrations for diverse tabletop manipulation tasks. It was created by AllenAI and was last updated on the platform in June 2026.