This 3d scene contains 3D buildings over the Populated Urban Area of San Bernardino County.

This scene is used as the City of Aspen 3D Basemap derived from 2016 and 2020 Lidar data. Displays realistic buildings and trees in the mountain town of Aspen, Colorado. Aspen is located in a remote area of the Rocky Mountains at an elevation just below 8,000 feet. Surrounded by the White River National Forest along the Roaring Fork River, Aspen is a popular destination for year-round outdoor recreation. For more interactive maps from the City of Aspen, visit Map Aspen, the City of Aspen's open data site.

The TopoBathy 3D layer provides a global seamless topography (land elevation) and bathymetry (water depths) surface to use in ArcGIS 3D applications.What can you do with this layer?This layer is meant to be used as a ground in ArcGIS Online Web Scenes, ArcGIS Earth, and ArcGIS Pro to help visualize your maps and data in 3D.How do I use this layer?In the ArcGIS Online Web Scene Viewer:Sign-in with ArcGIS Online accountOn the Designer toolbar, click Add Layers Click Browse layers and choose Living Atlas.Search for TopoBathy 3DAdd TopoBathy 3D (Elevation Layer)The TopoBathy 3D will get added under Ground. Change basemap to OceansOptionally, add any other operational layers to visualize in 3DIn ArcGIS Pro:Ensure you are logged in with an ArcGIS Online accountOpen a Global SceneOn the Map tab, click Add Data > Elevation Source LayerUnder Portal, click Living Atlas and search for TopoBathy 3DSelect TopoBathy 3D (Elevation Layer) and click OKThe TopoBathy 3D will get added under GroundOptionally, remove other elevation layers from ground and choose the desired basemapDataset Coverage To see the coverage and sources of various datasets comprising this elevation layer, view the Elevation Coverage Map. Additionally, this layer uses data from Maxar’s Precision 3D Digital Terrain Models for parts of the globe.

This 3D basemap presents OpenStreetMap (OSM) data and other data sources and is hosted by Esri using the OpenStreetMap style.Esri created the Places and Labels, Trees, and OpenStreetMap layers from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new scene available to the OSM, GIS, and Developer communities.The Buildings layer (beta) presents open buildings data that has been processed and hosted by Esri. Esri created this buildings scene layer using data from the Overture Maps Foundation (OMF) which is supported by Meta, Microsoft, Amazon, TomTom, Esri and other members. Overture includes data from many sources, including OpenStreetMap (OSM). The 3D buildings layer will be updated each month with the latest version of Overture data, which includes the latest updates from OSM, Esri Community Maps, and other sources.Overture Maps is a collaborative project to create reliable, easy-to-use, and interoperable open map data. Member companies work to bring together the best available open datasets, and the resulting data can be downloaded from Microsoft Azure or Amazon S3. Esri is a member of the OMF project and is excited to make this 3D web scene available to the ArcGIS user community.

This 3D basemap presents OpenStreetMap (OSM) and other data sources and is hosted by Esri using the Topographic style.The Buildings layer references the Esri 3D Buildings scene layer, which includes commercial 3D buildings data acquired from TomTom and Maxar, in addition to Esri Community Maps and Overture Maps Foundation data. The Esri 3D Buildings scene layer is an alternative to the OpenStreetMap (OSM) 3D Buildings scene layer, particularly for areas where the OSM data is missing accurate 3D attributes.Esri created the Places and Labels, Trees, and Topographic layers from the Daylight map distribution of OSM data, which was supported by Meta and supplemented with additional data from Microsoft. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new scene available to the OSM, GIS, and Developer communities.

The Terrain 3D layer provides global elevation surface to use in ArcGIS 3D applicationsWhat can you do with this layer?Use this layer to visualize your maps and layers in 3D using applications like the Scene Viewer in ArcGIS Online and ArcGIS Pro. Show me how1) Working with Scenes in ArcGIS Pro or ArcGIS Online Scene Viewer2) Select an appropriate basemap or use your own3) Add your unique 2D and 3D data layers to the scene. Your data are simply added on the elevation. If your data have defined elevation (z coordinates) this information will be honored in the scene4) Share your work as a Web Scene with others in your organization or the publicDataset Coverage To see the coverage and sources of various datasets comprising this elevation layer, view the Elevation Coverage Map. Additionally, this layer uses data from Maxar’s Precision 3D Digital Terrain Models for parts of the globe.This layer is part of a larger collection of elevation layers. For more information, see the Elevation Layers group on ArcGIS Online.

This 3D basemap presents OpenStreetMap (OSM) and other data sources and is hosted by Esri using the Dark Gray Canvas style.The Buildings layer references the Esri 3D Buildings scene layer, which includes commercial 3D buildings data acquired from TomTom and Maxar, in addition to Esri Community Maps and Overture Maps Foundation data. The Esri 3D Buildings scene layer is an alternative to the OpenStreetMap (OSM) 3D Buildings scene layer, particularly for areas where the OSM data is missing accurate 3D attributes.Esri created the Places and Labels, and Dark Gray Canvas layers from the Daylight map distribution of OSM data, which is supported by Facebook and supplemented with additional data from Microsoft. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new vector basemap available available to the OSM, GIS, and Developer communities.

This 3D basemap presents OpenStreetMap (OSM) and other data sources and is hosted by Esri using the Streets (Dark) style.The Buildings layer references the Esri 3D Buildings scene layer, which includes commercial 3D buildings data acquired from TomTom and Maxar, in addition to Esri Community Maps and Overture Maps Foundation data. The Esri 3D Buildings scene layer is an alternative to the OpenStreetMap (OSM) 3D Buildings scene layer, particularly for areas where the OSM data is missing accurate 3D attributes.Esri created the Places and Labels, and Streets Dark layers from the Daylight map distribution of OSM data, which was supported by Meta and supplemented with additional data from Microsoft. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new scene available to the OSM, GIS, and Developer communities.

This 3D basemap presents OpenStreetMap (OSM) and other data sources and is hosted by Esri using the Light Gray Canvas style.The Buildings layer references the Esri 3D Buildings scene layer, which includes commercial 3D buildings data acquired from TomTom and Maxar, in addition to Esri Community Maps and Overture Maps Foundation data. The Esri 3D Buildings scene layer is an alternative to the OpenStreetMap (OSM) 3D Buildings scene layer, particularly for areas where the OSM data is missing accurate 3D attributes.Esri created the Places and Labels, and Light Gray Canvas layers from the Daylight map distribution of OSM data, which was supported by Meta and supplemented with additional data from Microsoft. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project and is excited to make this new scene available to the OSM, GIS, and Developer communities.

v1 for geo-point

This layer portrays elevation as an artistic hillshade. The map is designed to be used as a backdrop for topographical, soil, hydro, landcover or other outdoor recreational maps. It’s a default relief background in various basemaps such as Topographic, Terrain with Labels.The map is compiled from a variety of data sources from commercial, community maps and many authoritative organizations across the globe. The basemap has global coverage down to a scale of ~1:72k. In the United States, parts of Europe, Asia and Africa coverage goes down to ~1:9k. To see the coverage and sources of various datasets comprising this map layer, view the Elevation Coverage Map. Additionally, this layer uses data from Maxar’s Precision 3D Digital Terrain Models for parts of the globe.The map is based on the Multi-directional hillshade algorithm.Precise Tile RegistrationThe World Hillshade map uses the improved tiling scheme “WGS84 Geographic, Version 2” to ensure proper tile positioning at higher resolutions (neighborhood level and beyond). The new tiling scheme is much more precise than tiling schemes of the legacy basemaps Esri released years ago. We recommend that you start using this new basemap for any new web maps in WGS84 that you plan to author. Due to the number of differences between the old and new tiling schemes, some web clients will not be able to overlay tile layers in the old and new tiling schemes in one web map.

This New Zealand Point Cloud Classification Deep Learning Package will classify point clouds into building and background classes. This model is optimized to work with New Zealand aerial LiDAR data.The classification of point cloud datasets to identify Building is useful in applications such as high-quality 3D basemap creation, urban planning, and planning climate change response.Building could have a complex irregular geometrical structure that is hard to capture using traditional means. Deep learning models are highly capable of learning these complex structures and giving superior results.This model is designed to extract Building in both urban and rural area in New Zealand.The Training/Testing/Validation dataset are taken within New Zealand resulting of a high reliability to recognize the pattern of NZ common building architecture.Licensing requirementsArcGIS Desktop - ArcGIS 3D Analyst extension for ArcGIS ProUsing the modelThe model can be used in ArcGIS Pro's Classify Point Cloud Using Trained Model tool. Before using this model, ensure that the supported deep learning frameworks libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.Note: Deep learning is computationally intensive, and a powerful GPU is recommended to process large datasets.The model is trained with classified LiDAR that follows the The model was trained using a training dataset with the full set of points. Therefore, it is important to make the full set of points available to the neural network while predicting - allowing it to better discriminate points of 'class of interest' versus background points. It is recommended to use 'selective/target classification' and 'class preservation' functionalities during prediction to have better control over the classification and scenarios with false positives.The model was trained on airborne lidar datasets and is expected to perform best with similar datasets. Classification of terrestrial point cloud datasets may work but has not been validated. For such cases, this pre-trained model may be fine-tuned to save on cost, time, and compute resources while improving accuracy. Another example where fine-tuning this model can be useful is when the object of interest is tram wires, railway wires, etc. which are geometrically similar to electricity wires. When fine-tuning this model, the target training data characteristics such as class structure, maximum number of points per block and extra attributes should match those of the data originally used for training this model (see Training data section below).OutputThe model will classify the point cloud into the following classes with their meaning as defined by the American Society for Photogrammetry and Remote Sensing (ASPRS) described below: 0 Background 6 BuildingApplicable geographiesThe model is expected to work well in the New Zealand. It's seen to produce favorable results as shown in many regions. However, results can vary for datasets that are statistically dissimilar to training data.Training dataset - Auckland, Christchurch, Kapiti, Wellington Testing dataset - Auckland, WellingtonValidation/Evaluation dataset - Hutt City Dataset City Training Auckland, Christchurch, Kapiti, Wellington Testing Auckland, Wellington Validating HuttModel architectureThis model uses the SemanticQueryNetwork model architecture implemented in ArcGIS Pro.Accuracy metricsThe table below summarizes the accuracy of the predictions on the validation dataset. - Precision Recall F1-score Never Classified 0.984921 0.975853 0.979762 Building 0.951285 0.967563 0.9584Training dataThis model is trained on classified dataset originally provided by Open TopoGraphy with < 1% of manual labelling and correction.Train-Test split percentage {Train: 75~%, Test: 25~%} Chosen this ratio based on the analysis from previous epoch statistics which appears to have a descent improvementThe training data used has the following characteristics: X, Y, and Z linear unitMeter Z range-137.74 m to 410.50 m Number of Returns1 to 5 Intensity16 to 65520 Point spacing0.2 ± 0.1 Scan angle-17 to +17 Maximum points per block8192 Block Size50 Meters Class structure[0, 6]Sample resultsModel to classify a dataset with 23pts/m density Wellington city dataset. The model's performance are directly proportional to the dataset point density and noise exlcuded point clouds.To learn how to use this model, see this story

Dataset estimates location and size of trees in the District of Columbia that are not managed by the Urban Forestry Division (https://opendata.dc.gov/datasets/urban-forestry-street-trees/explore). Trees are modeled using an automated feature extraction process applied to 2022 LiDAR data. All data is an estimate, and intended for general representation purposes.

DC 2022 LiDAR was used and processed using the “Extract Trees using Cluster Analysis” script which is included as part of Esri’s 3D Basemap solution. All LiDAR-derived trees within 2 meters of a Urban Forestry Division tree were removed as being duplicates.

Tree diameter (DBH, in inches) was estimated for the LiDAR-derived trees from calculated tree height (in feet) based on the equation: DBH = 0.4003*height - 1.9557. This equation was derived from a statistical analysis of a detailed park inventory tree data set and has an R^2 = 0.7418.

Extreme outliers were also modified, with any DBH larger than 80 inches being converted to a DBH of 80 inches.

ArcGIS Solutionsの「3D basemaps」を利用したデジタルツインのデモアプリです。アメリカ合衆国バーモント州https://www.arcgis.com/home/webscene/viewer.html?webscene=cfc5b68d98d14c1d9d1ed94756492c30詳細はこちらhttps://doc.arcgis.com/en/arcgis-solutions/10.9.1/reference/use-3d-basemaps.htm

These footprint extents are collapsed from an earlier 3D building model provided by Pictometry of 2010, and have been refined from a version of building masses publicly available on the open data portal for over two years.The building masses were manually split with reference to parcel lines, but using vertices from the building mass wherever possible.These split footprints correspond closely to individual structures even where there are common walls; the goal of the splitting process was to divide the building mass wherever there was likely to be a firewall.

An arbitrary identifier was assigned based on a descending sort of building area for 177,023 footprints. The centroid of each footprint was used to join a property identifier from a draft of the San Francisco Enterprise GIS Program's cartographic base, which provides continuous coverage with distinct right-of-way areas as well as selected nearby parcels from adjacent counties. See accompanying document SF_BldgFoot_2017-05_description.pdf for more on methodology and motivation https://data.sfgov.org/d/72ai-zege/about

To get this data as a File Geodatabase, go to https://data.sfgov.org/d/asx6-3trm

This resource contains Lidar-DEM collection status shapefiles from the Texas Natural Resources Information System (TNRIS) [http://tnris.org]. November 2023 updates: this year, TNRIS changed its name to Texas Geographic Information Office (TxGIO). The domain name hasn't changed yet, but the data hub is continually evolving. See [1], [2] for current downloadable data.

For purposes of Hurricane Harvey studies, the 1-m DEM for Harris County (2008) has also been uploaded here as a set of 4 zipfiles containing the DEM in tiff files. See [1] for a link to the current elevation status map and downloadable DEMs.
Project name: H-GAC 2008 1m Datasets: 1m Point Cloud, 1M Hydro-Enforced DEM, 3D Breaklines, 1ft and 5ft Contours Points per sq meter: 1 Total area: 3678.56 sq miles Source: Houston-Galveston Area Council (H-GAC) Acquired by: Merrick, QA/QC: Merrick Catalog: houston-galveston-area-council-h-gac-2008-lidar

References: [1] TNRIS/TxGIO StratMap elevation data [https://tnris.org/stratmap/elevation-lidar/] [2] TNRIS/TxGIO DataHub [https://data.tnris.org/]

DC 2022 LiDAR was used and processed using the “Extract Trees using Cluster Analysis” script which is included as part of Esri’s 3D Basemap solution. All LiDAR-derived trees within 2 meters of a Urban Forestry Division tree were removed as being duplicates.Tree diameter (DBH, in inches) was estimated for the LiDAR-derived trees from calculated tree height (in feet) based on the equation: DBH = 0.4003*height - 1.9557. This equation was derived from a statistical analysis of a detailed park inventory tree data set and has an R^2 = 0.7418.Extreme outliers were also modified, with any DBH larger than 80 inches being converted to a DBH of 80 inches.The combined data set was processed using the USDA Forest Service i-Tree eco software, where structure and environmental benefits were estimated.

CartoSat-1 (also known as IRS-P5) archive products are available as PAN-Aft (backward), PAN-Fore (forward) and Stereo (PAN-Aft and PAN-Fore). - Sensor: PAN - Products: PAN-Aft (backward), PAN-Fore (forward), Stereo (PAN-Aft+PAN-Fore) - Type: Panchromatic - Resolution (m): 2.5 - Coverage (km x km): 27 x 27 - System or radiometrically corrected - Ortho corrected (DN) - Neustralitz archive: 2007 - 2016 - Global archive: 2005 - 2019 Note: - Resolution 2.5 m. - Coverage 27 km x 27 km. - System or radiometrically corrected. For Ortho corrected products: If unavailable, user has to supply ground control information and DEM in suitable quality, - For Stereo ortho corrected: only one of the datasets will be ortho corrected. Euro-Maps 3D is a homogeneous, 5 m spaced digital surface model (DSM) semi-automatically derived from 2.5 m in-flight stereo data provided by IRS-P5 CartoSat-1 and developed in cooperation with the German Aerospace Center, DLR. The very detailed and accurate representation of the surface is achieved by using a sophisticated and well adapted algorithm implemented on the basis of the Semi-Global Matching approach. In addition, the final product includes detailed flanking information consisting of several pixel-based quality and traceability layers also including an ortho layer. Product Overview: - Post spacing: 5m - Spatial reference system: DD, UTM or other projections on WGS84 - Height reference system: EGM96 - Absolute vertical accuracy: LE90 5-10 m - Absolute Horizontal Accuracy: CE90 5-10 m - Relative vertical accuracy: LE90 2.5 m - File format: GeoTIFF, 16 bit - Tiling: 0.5° x 0.5° - Ortho Layer Pixel Size: 2.5 m The CartoSat-1 products and Euro-Maps 3D are available as part of the GAF Imagery products from the Indian missions: IRS-1C, IRS-1D, CartoSat-1 (IRS-P5), ResourceSat-1 (IRS-P6) and ResourceSat-2 (IRS-R2) missions. ‘Cartosat-1 archive’ collection has worldwide coverage: for data acquired over Neustrelitz footprint, the users can browse the EOWEB GeoPortal catalogue (http://www.euromap.de/products/serv_003.html) to search archived products; worldwide data (out the Neustrelitz footprint) as well as Euro-Maps 3D DSM products can be requested by contacting GAF user support to check the readiness since no catalogue is available. All details about the data provision, data access conditions and quota assignment procedure are described into the Terms of Applicability available in Resources section.

Important Note: This item is in mature support as of December 2024. See blog for more information.This 3D scene layer presents OpenStreetMap (OSM) buildings data hosted by Esri. Esri created buildings and trees scene layers from the OSM Daylight map distribution, which is supported by Facebook and others. The Daylight map distribution has been sunsetted and data updates supporting this layer are no longer available. You can visit openstreetmap.maps.arcgis.com to explore a collection of maps, scenes, and layers featuring OpenStreetMap data in ArcGIS. You can review the 3D Scene Layers Documentation to learn more about how the building and tree features in OSM are modeled and rendered in the 3D scene layers, and see tagging recommendations to get the best results.OpenStreetMap is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap site: www.OpenStreetMap.org. Esri is a supporter of the OSM project.Note: This layer is supported in Scene Viewer and ArcGIS Pro 3.0 or higher.

DC 2022 LiDAR was used and processed using the “Extract Trees using Cluster Analysis” script which is included as part of Esri’s 3D Basemap solution. The extracted tree data set was merged with the UFA tree inventory data, with preference given to the UFA tree inventory data. All LiDAR-derived trees within 2 meters of a UFA tree were removed as being duplicates.