Get familiar with the ArcGIS Pro 3D environment and learn a variety of techniques to create and enhance 3D scenes.Goals Link 3D scenes and 2D maps to enable side-by-side visualization. Extrude 2D features based on an attribute. Apply photorealistic symbology, light, and shadow. Share a 3D scene as a map layout.

Scene Layer Package used on Website. Has data from assessor table in it. This is used in our scene layers. It is the entire City's buildings based off the LiDAR.This is the official layer that was created using Local Government 3D modeling software from ArcGIS Pro.

A style containing 34 assorted 3D people models for use in large-scale visualizations, providing vertical context.To Match Layer Symbology to Style in ArcGIS Pro, populate a person_type text field to match the values shown below. Next, copy these values to a table, then join the height value(s) to the people points for use in pop-ups or charts. person_type name height_m height_feet height_inches

Man 1 Gerald 1.7899 5 10.47

Man 2 Ethan 1.8879 6 2.33

Man 3 Cliff 1.7015 5 6.99

Man 4 Dustin 1.7965 5 10.73

Man 5 Jorge 1.8787 6 1.96

Man 6 Phillip 1.6752 5 5.95

Man 7 Dmitri 1.71 5 7.32

Man 8 Luke 1.793 5 10.59

Man 9 Carlos 1.7028 5 7.04

Man 10 Jimmy 1.7625 5 9.39

Man 11 Helmut 1.8331 6 0.17

Man 12 Guy 1.812 5 11.34

Man 13 Leon 1.8219 5 11.73

Man 14 Matthias 1.753 5 9.02

Man 15 Kendrick 1.8787 6 1.96

Man 16 Seth 1.8272 5 11.94

Man 17 Gomer 1.8982 6 2.73

Man 18 Robert 1.7853 5 10.29

Man 19 Jack 1.779 5 10.04

Man 20 Andy 1.8794 6 1.99

Man 21 Hamish 1.67 5 5.75

Man 22 Felix 1.86 6 1.23

Man 23 Adrian 1.75 5 8.90

Woman 1 Greta 1.5371 5 0.52

Woman 2 Simone 1.6366 5 4.43

Woman 3 Alison 1.679 5 6.10

Woman 4 Felicia 1.7433 5 8.63

Woman 5 Jessica 1.7322 5 8.20

Woman 6 Claire 1.6405 5 4.59

Woman 7 Maude 1.7795 5 10.06

Woman 8 Jenny 1.659 5 5.31

Woman 9 Diane 1.67 5 5.75

Woman 10 Carla 1.75 5 8.90

Woman 11 Lauren 1.69 5 6.54

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.

The TopoBathy 3D layer provides a global seamless topography (land elevation) and bathymetry (water depths) surface to use as a ground 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 LayersClick Browse layersand 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 3D In 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 basemap Dataset CoverageTo see the coverage and sources of various datasets comprising this elevation layer, view the World Elevation Coverage Map. Additionally, this layer contains data from Vantor’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.

The Terrain 3D layer provides global elevation surface to use as a ground in ArcGIS 3D applications.What 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 CoverageTo see the coverage and sources of various datasets comprising this elevation layer, view the World Elevation Coverage Map. Additionally, this layer contains data from Vantor’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 dataset contains 50-ft contours for the Hot Springs shallowest unit of the Ouachita Mountains aquifer system potentiometric-surface map. The potentiometric-surface shows altitude at which the water level would have risen in tightly-cased wells and represents synoptic conditions during the summer of 2017. Contours were constructed from 59 water-level measurements measured in selected wells (locations in the well point dataset). Major streams and creeks were selected in the study area from the USGS National Hydrography Dataset (U.S. Geological Survey, 2017), and the spring point dataset with 18 spring altitudes calculated from 10-meter digital elevation model (DEM) data (U.S. Geological Survey, 2015; U.S. Geological Survey, 2016). After collecting, processing, and plotting the data, a potentiometric surface was generated using the interpolation method Topo to Raster in ArcMap 10.5 (Esri, 2017a). This tool is specifically designed for the creation of digital elevation models and imposes constraints that ensure a connected drainage structure and a correct representation of the surface from the provided contour data (Esri, 2017a). Once the raster surface was created, 50-ft contour interval were generated using Contour (Spatial Analyst), a spatial analyst tool (available through ArcGIS 3D Analyst toolbox) that creates a line-feature class of contours (isolines) from the raster surface (Esri, 2017b). The Topo to Raster and contouring done by ArcMap 10.5 is a rapid way to interpolate data, but computer programs do not account for hydrologic connections between groundwater and surface water. For this reason, some contours were manually adjusted based on topographical influence, a comparison with the potentiometric surface of Kresse and Hays (2009), and data-point water-level altitudes to more accurately represent the potentiometric surface. Select References: Esri, 2017a, How Topo to Raster works—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/how-topo-to-raster-works.htm. Esri, 2017b, Contour—Help | ArcGIS Desktop, accessed December 5, 2017, at ArcGIS Pro Raster Surface toolset at http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/contour.htm. Kresse, T.M., and Hays, P.D., 2009, Geochemistry, Comparative Analysis, and Physical and Chemical Characteristics of the Thermal Waters East of Hot Springs National Park, Arkansas, 2006-09: U.S. Geological Survey 2009–5263, 48 p., accessed November 28, 2017, at https://pubs.usgs.gov/sir/2009/5263/. U.S. Geological Survey, 2015, USGS NED 1 arc-second n35w094 1 x 1 degree ArcGrid 2015, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html. U.S. Geological Survey, 2016, USGS NED 1 arc-second n35w093 1 x 1 degree ArcGrid 2016, accessed December 5, 2017, at The National Map: Elevation at https://nationalmap.gov/elevation.html.

Discover how to display and symbolize both 2D and 3D data. Search, access, and create new map symbols. Learn to specify and configure text symbols for your map. Complete your map by creating an effective layout to display and distribute your work.

The Terrain 3D layer provides global elevation for your work in 3D.What 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 of various datasets comprising this service, click here.This layer is part of a larger collection of elevation layers. For more information, see the Elevation Layers group on ArcGIS Online.

This 3D model of Cape Cod structures and street trees was created with planimetrics from 2014. Using a combination of CityEngine, ArcGIS Pro and purchased collada models, the Cape Cod Commission generated this 3D scene to enhance visualization scenarios.

Mature Support Notice: This item is in mature support as of December 2024. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. See blog for more information.This 3D scene layer presents OpenStreetMap (OSM) trees 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.

This deep learning model is used to detect trees in low-resolution drone or aerial imagery. Tree detection can be used for applications such as vegetation management, forestry, urban planning, etc. High resolution aerial and drone imagery can be used for tree detection due to its high spatio-temporal coverage.

This deep learning model is based on MaskRCNN and has been trained on data from the DM Dataset preprocessed and collected by the IST Team.

There is no need of high-resolution imagery you can perform all your analysis on low resolution imagery by detecting the trees with the accuracy of 75% and finetune the model to increase your performance and train on your own data.

Licensing requirements ArcGIS Desktop – ArcGIS Image Analyst and ArcGIS 3D Analyst extensions for ArcGIS Pro ArcGIS Enterprise – ArcGIS Image Server with raster analytics configured ArcGIS Online – ArcGIS Image for ArcGIS Online

Using the model Follow the guide to use the model. Before using this model, ensure that the supported deep learning 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.

Input 3-band low-resolution (70 cm) satellite imagery.

Output Feature class containing detected trees

Applicable geographies The model is expected to work well in the U.A.E.

Model architecture This model is based upon the MaskRCNN python package and uses the Resnet-152 model architecture implemented in pytorch.

Training data This model has been trained on the Satellite Imagery created and Labelled by the team and validated on the different locations with more diverse locations.

Accuracy metrics This model has an average precision score of 0.45.

Sample results Here are a few results from the model.

This is a bathymetry-only view of the World Topographic Basemap. Sometimes you just need the bathymetry and don't want the not-thymetry. Where can you use it? Pretty much anywhere you might want a bathymetric layer. This vector tile layer can be used in an ArcGIS Online web map or scene, 2D or 3D ArcGIS Pro map, or any application using the ArcGIS API for Javascript. It's just like, a layer. If you are interested in learning how to isolate layers in vector basemaps yourself, here is a YouTube video with all the glorious details. The underlying data is untouched and unmoved, but his creates a custom "view" of the source basemap. Here it is all by itself in ArcGIS Online... ...and with an imagery basemap. Here it is in an ArcGIS Pro 3D map... Happy mapping, basemap surgeons! John Nelson

The National Hydrography Dataset Plus High Resolution (NHDplus High Resolution) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US Geological Survey, NHDPlus High Resolution provides mean annual flow and velocity estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses.For more information on the NHDPlus High Resolution dataset see the User’s Guide for the National Hydrography Dataset Plus (NHDPlus) High Resolution.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territoriesGeographic Extent: The Contiguous United States, Hawaii, portions of Alaska, Puerto Rico, Guam, US Virgin Islands, Northern Marianas Islands, and American SamoaProjection: Web Mercator Auxiliary Sphere Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Source: USGSUpdate Frequency: AnnualPublication Date: July 2022This layer was symbolized in the ArcGIS Map Viewer and while the features will draw in the Classic Map Viewer the advanced symbology will not. Prior to publication, the network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original dataset. No data values -9999 and -9998 were converted to Null values.What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute.Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map.Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

Renowned for its natural and man-made beauty, the historic city of Venice spans a series of islands in a shallow lagoon. Venice’s unique geography has a downside, however. Tidal patterns mix with low elevation to cause acqua alta (high water), a periodic flooding that, although not dangerous to human life, impedes transportation and endangers Venice’s priceless architecture.This layer package includes three layers. The Structures layer contains building footprint data. The Canals layer contains Venice's canals. The Landmarks layer contains famous landmarks throughout the city. The data was acquired from Comune di Venezia - Portale dei servizi in 2014.This project package contains the default ArcGIS Pro project for the tutorial Map Venice in 3D. If users did not complete the previous tutorial in the series, they can use this project package.

This New Zealand Point Cloud Classification Deep Learning Package will classify point clouds into tree and background classes. This model is optimized to work with New Zealand aerial LiDAR data.The classification of point cloud datasets to identify Trees is useful in applications such as high-quality 3D basemap creation, urban planning, forestry workflows, and planning climate change response.Trees 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 Tree 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.InputThe model is trained with classified LiDAR that follows the LINZ base specification. The input data should be similar to this specification.Note: The model is dependent on additional attributes such as Intensity, Number of Returns, etc, similar to the LINZ base specification. This model is trained to work on classified and unclassified point clouds that are in a projected coordinate system, in which the units of X, Y and Z are based on the metric system of measurement. If the dataset is in degrees or feet, it needs to be re-projected accordingly. 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 5 Trees / High-vegetationApplicable 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 - Wellington CityTesting dataset - Tawa CityValidation/Evaluation dataset - Christchurch City Dataset City Training Wellington Testing Tawa Validating ChristchurchModel architectureThis model uses the PointCNN model architecture implemented in ArcGIS API for Python.Accuracy metricsThe table below summarizes the accuracy of the predictions on the validation dataset. - Precision Recall F1-score Never Classified 0.991200 0.975404 0.983239 High Vegetation 0.933569 0.975559 0.954102Training dataThis model is trained on classified dataset originally provided by Open TopoGraphy with < 1% of manual labelling and correction.Train-Test split percentage {Train: 80%, Test: 20%} 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-121.69 m to 26.84 m Number of Returns1 to 5 Intensity16 to 65520 Point spacing0.2 ± 0.1 Scan angle-15 to +15 Maximum points per block8192 Block Size20 Meters Class structure[0, 5]Sample resultsModel to classify a dataset with 5pts/m density Christchurch 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

ArcGIS Pro ist eine professionelle Desktop-GIS-Anwendung von Esri mit vollem Funktionsumfang. Mit ArcGIS Pro können Sie Daten erkunden, visualisieren und analysieren, 2D-Karten und 3D-Szenen erstellen sowie Ihre Arbeit im ArcGIS Online- oder ArcGIS Enterprise-Portal freigeben. In den folgenden Abschnitten werden der Anmeldevorgang, die Startseite, ArcGIS Pro-Projekte und die Bedienoberfläche vorgestellt. https://pro.arcgis.com/de/pro-app/latest/get-started/get-started.htm

This two-part video tutorial provides a comprehensive, step-by-step guide to creating and georeferencing a 3D textured model of a historic building using Reality Capture. It covers the entire process, from photo alignment and importing GPS data from a text file to identifying and using ground control points (GCPs) to improve the alignment of model components and accurately georeference the point cloud. The tutorial also demonstrates model creation, cleaning, simplification, and texturing. In the final steps, the model is exported and imported into ArcGIS Pro for geographic analysis and visualization.

New to 3D GIS with @esri and @ArcGISPro?I’ve put together a printable 2-page cheat-sheet of the concepts and terms you need to get started! 😊First, take a quick anatomy lesson to learn about the elements that make up a 3D scene. Not every scene has every element, but you need to know your options.Perhaps most importantly, think about HOW you intend to share your 3D map BEFORE you spend hours (or days) making it. - Tip: If it’s an image or a video, you can spend more time on areas you know the camera will visit, and less on the rest. 3D also has this nasty habit of showing continuous scales (aka levels-of-detail / LODs) throughout the view… You WILL need to think about how scales change off into the distance, as well as choosing the “just-right” LOD for the features you’re showing.Got data with no Z’s? No problem – give them a place to draw by creating an elevation surface. While ‘Ground’ is the most famous, you can also model surfaces: underground; in the air; and based on thematic values.“Paint” your surfaces by draping them with imagery and cartographic content… but don’t forget about the whole continuous-scale thing.Vector content are the “pretty boys” of your 3D map. They give the scene depth and things for people to click on. They can also be high maintenance, both in creation time and performance impact. Use them wisely, and consistently, to avoid a scene that tries to do too much.Vector objects come in all shapes and sizes. Think about how even a simple shape – rotated and resized into place – can communicate information to the user. Everything does NOT* have to look “real”!* (Full Disclosure: sometimes it does).Much like the Ground surface, the exterior shell of vector objects can also be “painted”. The source could be oblique imagery… or procedurally-placed windows and bricks… or even “material” properties that can make a surface appear to be iron or glass or wood. Text in a 3D view can label locations and reinforce the direction a feature is oriented. Make it 3D (where you can) and only drape it on the ground as a last resort… or when you have full camera control (eg: video).Once you’ve symbolized all your layers, you still have more to do – you must also think about the scene as a whole! A scene’s light direction can change the mood, exaggeration can make flat land interesting, and the background color might be critical for the intended use of an exported image.And, finally, if you’re sharing an interactive 3D view, please have a little EMPATHY for your audience. Some of them will be new to 3D and – let’s be honest - navigating around can be hard.If you give them ‘safe places’ (bookmarks / slides) to zoom to if they get lost, they will love your work even more.Hope this helps – good luck with your 3D!-Nathan.

Web-palvelu, joka julkaisee DMR 4G -dataa, joka on suunniteltu näyttämään yksityiskohtainen korkeusmalli verkkoympäristössä 3D: ssä, S-JTSK-koordinaattijärjestelmässä Křovákin näkökulmasta. Palvelun tarjoamat tiedot ovat erikoistuneessa muodossa LERC (https://github.com/Esri/lerc), mikä mahdollistaa tehokkaan pakkaamisen nopeaan tiedonsiirtoon ja renderointiin 3D-sovelluksissa. Palvelun lähdetiedot sijaitsevat koordinaattijärjestelmässä S-JTSK/Krovak East North (EPSG 5514). Olemassa olevia Esri-sovelluksia, kuten Scene Viewer (https://www.esri.com/software/scene-viewer), ArcGIS Pro (http://www.esri.com/en/software/arcgis-pro) tai ArcGIS Earth (http://www.esri.com/en/software/arcgis-pro), voidaan käyttää korkeusmallin näyttämiseen 3D-muodossa omissa verkkosovelluksissasi käyttämällä ArcGIS API JavaScript 4.x -kirjastoa tai natiivisovelluksia ArcGIS Runtime SDK: n avulla.