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Computer Graphics & Simulation

3D models, rendered datasets, physics simulation, digital twins, synthetic data generation, game engine data

1,403 datasets

ACT Canopy Cover 2020: Vegetation Statistics for Urban Blocks and Divisions

April 2020 LiDAR-derived canopy coverage statistics for the Australian Capital Territory. The dataset provides estimated percentage coverage of vegetation above 3 meters for urban blocks, divisions, and road polygons, with a total tree canopy cover estimate for Canberra of 22.5%. It was produced by the ACT Government from LiDAR data captured in April 2020 and processed with ArcGIS.

TabularTime SeriesGeospatialPoint CloudZIPCSVTreeGdc0b1360dfClimate ChangeCanopyClimateUrban ForestSustainabilityCanopy coverAct CanberraCanberraUrban CoolingCoverConnectivityUrban ForestryActUrban HabitatEnvironmentLiving InfrastructureUrban CanopyEnvironmental Sustainability+1

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Computer Graphics & Simulation

ACT Road Canopy Cover 2020: Vegetation Statistics for Canberra

Canberra's 2020 tree canopy coverage statistics for blocks, divisions, and road polygons, derived from LiDAR data. The dataset provides estimated percentage coverage of vegetation above 3 meters, with a total urban canopy cover estimate of 22.5% for Canberra. It was produced by the ACT Government from LiDAR captured in April 2020 and is updated every five years.

TabularTime SeriesGeospatialPoint CloudZIPCSVTreeGdc0b1360dfClimate ChangeEnvironmental monitoringCanopyClimateUrban ForestSustainabilityCanopy coverCanberraUrban CoolingCoverConnectivityUrban ForestryActUrban HabitatEnvironmentLiving Infrastructure+1

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Computer Graphics & Simulation

ACT Canopy Cover 2020: Urban Vegetation Statistics for Canberra

ACT Canopy Estimate Statistics 2020 provides the estimated percentage coverage of vegetation above 3 meters for blocks, divisions, and road polygons in the Australian Capital Territory. The dataset is derived from LiDAR data captured in April 2020 and was completed by a collaboration between CED and TCCS, ACT Government. The total tree canopy cover estimate for Canberra's urban divisions in 2020 is 22.5%.

Time SeriesGeospatialPoint CloudZIPCSVTreeGdc0b1360dfTree CanopyClimate ChangeCanopyClimateUrban ForestSustainabilityCanberraUrban CoolingCoverConnectivityActUrban HabitatEnvironmentLiving Infrastructure+1

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Computer Graphics & Simulation

Coral Sea Sentinel 2 Marine Satellite Composite Imagery, 2015-2021

Composite satellite images for the Coral Sea region based on 10 m resolution Sentinel 2 imagery from 2015 to 2021. This draft version from the Australian Ocean Data Network was prepared from approximately 60% of the available imagery and contains 31 tiles with 5 different enhancement styles each. The collection is intended to allow mapping of reef and island features.

ImageGeospatialCoral ReefMarine EcologySatellite ImageryComputer Vision+1

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Computer Graphics & Simulation

ACT Canopy Cover 2020: Urban Tree Canopy Percentage for Canberra

ACTGOV 2020 Canopy Cover provides estimated percentage coverage of vegetation above 3 meters for blocks, divisions, and road polygons in Canberra. The dataset is derived from LiDAR data captured in April 2020 by Aerometrex and the ACT Government, processed to a 1-meter resolution. The total tree canopy cover estimate for Canberra's urban divisions in 2020 is 22.5%.

Time SeriesGeospatialPoint CloudTreeGdc0b1360dfTree CanopyClimate ChangeCanopyClimateUrban ForestSustainabilityCanberraUrban CoolingCoverConnectivityActUrban HabitatEnvironmentLiving Infrastructure+1

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Computer Graphics & Simulation

City of Melbourne 3D Point Cloud with RGB Attributes, 2018

A 3D point cloud representing physical features like buildings, trees, and terrain across the City of Melbourne. The data was captured in May 2018 with a 7.5cm ground sample distance and is provided by City of Melbourne Open Data. It is encoded in .las files containing geospatial coordinates and RGB color values for each point.

GeospatialPoint CloudCSVJSONCity PlanningBuildingHEIGHTSModelCloudPlanningUrban 3d ModelingPoint+1

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Computer Graphics & Simulation

City of Melbourne 3D Textured Mesh with 7.5cm Ground Sample Distance, 2018

A 3D textured mesh representing physical features like buildings, trees, and terrain across the City of Melbourne municipality. The dataset is provided in tiled .obj files with accompanying .mtl and .jpg texture files, captured in May 2018 with a 7.5cm ground sample distance. Data is provided by City of Melbourne Open Data and includes multiple levels of detail from L13 to L20.

ImageGeospatialPoint CloudMultimodalCSVJSONUrban ModellingCity PlanningTerrainModelMeshPhotogrammetryAnalysisDsmComputer VisionBuildingsVegetationPlanningEnvironmentModelling3d Mesh+1

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Computer Graphics & Simulation

Northern Ireland North Coast Post-Storm LiDAR Recovery Survey

Fugro undertook two topographic LiDAR surveys of soft sedimentary coastlines in Northern Ireland in 2022, following successive storms Dudley, Eunice, and Franklin. The March survey assessed damage to beaches from Curran Strand to Magilligan, while the September survey measured recovery, with data collected from the intertidal zone to 10 meters inland at 0.5-meter resolution. This data, provided in the same format as a 2021 baseline survey, enables precise change detection for coastal management.

GeospatialPoint CloudJSONBenchmarkStorm ImpactCoastal Monitoring+1

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Computer Graphics & Simulation

eReefs Basemap: GIS Layers for the Great Barrier Reef and Coral Sea

A collection of GIS layers for creating printed maps of the Great Barrier Reef and Coral Sea. The collection includes datasets for countries, 21 cities along the Queensland coast, drainage basins, rivers, and reef boundaries, derived from sources like Natural Earth Data and Geoscience Australia. The data is simplified for low-detail map rendering and is hosted by the Australian Ocean Data Network.

Geospatial🇦🇺 AustraliaCoral reefsRiver BasinsCoastal GeographyGis Layers+1

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Computer Graphics & Simulation

City of Melbourne 3D Textured Mesh with 2cm Ground Sample Distance

May 2020 capture of a high-resolution 3D textured mesh representing all physical features across the City of Melbourne municipality. The data, provided by City of Melbourne Open Data, is delivered in ESRI SLPK and Wavefront OBJ formats, split into geo-referenced tiles. It features a 2cm ground sample distance and estimated spatial accuracies of 0.05m (X), 0.6m (Y), and 0.04m (Z).

ImageGeospatialPoint CloudMultimodalCSVJSONUrban ModellingCity PlanningTerrainModelMeshPhotogrammetryAnalysisDsmComputer VisionBuildingsVegetationPlanningEnvironmentModelling3d Mesh+1

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Computer Graphics & Simulation

Probabilistic airborne electromagnetic inversion of 20 km AusAEM data, North East Queensla

35,000 line kilometers of airborne electromagnetic (AEM) data from the 2024 Northeast Queensland AusAEM survey were inverted using the open-source HiQGA code. The dataset provides probabilistic inversion products, including the 10th, 50th, 90th, and mean percentiles of log10 conductivity, released under the Resourcing Australia's Prosperity initiative. Products are available in multiple formats including VTK structured grids, ASCII point clouds, ASEG-GDF2 files, and GOCAD S-grids.

GeospatialPoint Cloud🇦🇺 AustraliaZIPGeophysical InversionProbabilistic ModelingAirborne ElectromagneticGeoscience+1

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Computer Graphics & Simulation

Diverse Topologies for Evaluation of Geometric Similarity Metrics: 7 Datasets of 3D Shapes

A collection of 7 datasets containing 3D shapes with varying topological complexity, created by Nivesh Dommaraju at the Technical University of Munich. The datasets include surface mesh and point cloud files and were used to compare metrics of geometric dissimilarity in a related journal article. Two of the datasets contain topologically complex shapes resembling designs from topology optimization.

Point CloudEngineering DesignBenchmarkTopology OptimizationGeometric Similarity3D shapesSynthetic+1

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Computer Graphics & Simulation

Ultraliser: 3D Neuronal, Astrocytic, and Vascular Morphology Meshes

Supplementary Data 1 contains input and output surface meshes for a reconstructed tissue block from an EPFL-KAUST collaboration. The collection includes 25 neuronal morphologies, 25 synthetic astroglial morphologies, and a vascular morphology, all with corresponding watertight meshes generated by the Ultraliser framework. Neuronal, astrocytic, and vascular data are stored in SWC, H5, and VMV file formats respectively, with surface meshes provided as Wavefront OBJ and STL files.

GraphMultimodalBiomedical SimulationMultiscale ModelingComputational neuroscience3d MeshSynthetic+1

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Computer Graphics & Simulation

Probabilistic Airborne Electromagnetic Inversion of 140,000 km AusAEM Data

Phase 2 of the AusAEM program provides probabilistic inversion products from 140,000 line kilometers of airborne electromagnetic data. The data were processed using the open-source HiQGA code as part of the Resourcing Australia's Prosperity initiative. Products include conductivity percentiles across multiple Australian survey regions.

GeospatialPoint CloudZIPGeophysicsMineral explorationProbabilistic InversionAirborne Electromagnetic+1

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Computer Graphics & Simulation

Measuring Bulk Crystallographic Texture from Ti-6Al-4V Hot-Rolled Sample Matrices using Sy

A dataset of synchrotron X-ray diffraction analysis files from Christopher Stuart Daniel at the University of Manchester. It records the refinement of crystallographic texture from 93 Ti-6Al-4V hot-rolled sample matrices, cut along three orthogonal directions. The work aimed to quantify bulk macro-texture for both the α and β phases across different processing conditions.

ImageTabularTime SeriesTexture AnalysisComputer VisionCrystallographySynchrotron XrdMaterials ScienceTitanium Alloy+1

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Computer Graphics & Simulation

eAtlas THREDDS: Environmental Data for the Great Barrier Reef

The eAtlas THREDDS service provides environmental data focused on the Great Barrier Reef, its neighboring coast, the Wet Tropics rainforests, and Torres Strait. The service delivers NetCDF data files via a THREDDS Data Server, with metadata and map layers accessible through OPeNDAP, OGC WMS, and WCS protocols. It is operated by the Australian Institute of Marine Science and co-funded by the National Environmental Science Program Tropical Water Quality Hub.

GeospatialMultimodalEnvironmental ResearchGreat Barrier ReefOcean Data+1

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Computer Graphics & Simulation

NI 3D Coastal Survey: 2021 Airborne LiDAR Point Cloud

The 2021 NI 3D Coastal Survey provides a complete airborne LiDAR point cloud of the Northern Ireland coastline. The data captures the intertidal area and extends approximately 200 meters landward of the high-water mark, offering a precise record of coastal morphology. This dataset is available on multiple open data platforms under a UK Open Government License.

GeospatialPoint CloudJSONIrelandSurveyNorthern IrelandTopographyLidar Point CloudObservatoryMarine3dNorthernCoastalCoastal SurveyLidar+1

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Computer Graphics & Simulation

ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation

ClevrTex is a synthetic benchmark of 50,000 training and 10,000 test images designed to challenge unsupervised multi-object segmentation models. Created by Laurynas Karazija at the University of Oxford using physically based rendering, it features scenes with 3-10 objects rendered with diverse textures and materials. The dataset aims to expose the limitations of current state-of-the-art models, which perform well on simpler data but fail on this textured, complex imagery.

ImageBenchmarkComputer VisionMulti Object SegmentationUnsupervised LearningSynthetic DataSynthetic+1

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Computer Graphics & Simulation

1,100 Stone Meshes and Placement Candidates for Robotic Dry Stone Construction

1,100 digitized stone meshes, including quarried boulders and concrete debris, were collected by the autonomous excavator HEAP. The dataset from ETH Zurich includes raw and cleaned 3D meshes, candidate placements for automated wall building, and hand-labeled viability scores. It supports research in robotic excavation and autonomous construction using on-site materials.

TabularPoint CloudConstruction SimulationRoboticsComputer VisionStone MeshesSynthetic+1

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Computer Graphics & Simulation

IMOS National Reference Station Zooplankton Biomass from Nine Australian Coastal Sites

Zooplankton biomass data from nine Australian coastal reference stations, sampled monthly as part of the Integrated Marine Observing Systems (IMOS) National Mooring Network. Samples are collected using a drop net and analyzed for community composition, biomass, and size spectrum. The dataset is superseded by a newer collection and made available through the Australian Ocean Data Network (AODN) portal.

TabularTime SeriesOceanographyZooplanktonBiomassMarine Biology+1

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