Buildings are the foundation of any 3D city; they create a realistic visual context for understanding the built environment. This rule can help you quickly create 3D buildings using your existing 2D building footprint polygons. Create buildings for your whole city or specific areas of interest. Use the buildings for context surrounding higher-detail buildings or proposed future developments. Already have existing 3D buildings? Check out the Textured Buildings from Mass by Building Type rule.What you getA Rule Package file named Building_FromFootprint_Textured_ByBuildingType.rpk Rule works with a polygon layerGet startedIn ArcGIS Pro Use this rule to create Procedural Symbols, which are 3D symbols drawn on 2D features Create 3D objects (Multipatch layer) for sharing on the webShare on the web via a Scene LayerIn CityEngineCityEngine File Navigator HelpParametersBuilding Type: Eave_Height: Height from the ground to the eave, units controlled by the Units parameterFloor_Height: Height of each floor, units controlled by the Units parameterRoof_Form: Style of the building roof (Gable, Hip, Flat, Green)Roof_Height: Height from the eave to the top of the roof, units controlled by the Units parameterType: Use activity within the building, this helps in assigning appropriate building texturesDisplay:Color_Override: Setting this to True will allow you to define a specific color using the Override_Color parameter, and will disable photo-texturing.Override_Color: Allows you to specify a building color using the color palette. Note: you must change the Color_Override parameter from False to True for this parameter to take effect.Transparency: Sets the amount of transparency of the feature Units:Units: Controls the measurement units in the rule: Meters | FeetImportant Note: You can hook up the rule parameters to attributes in your data by clicking on the database icon to the right of each rule parameter. The database icon will change to blue when the rule parameter is mapped to an attribute field. The rule will automatically connect when field names match rule parameter names. Use layer files to preserve rule configurations unique to your data.For those who want to know moreThis rule is part of a the 3D Rule Library available in the Living Atlas. Discover more 3D rules to help you perform your work.Learn more about ArcGIS Pro in the Getting to Know ArcGIS Pro lesson

3D buildings. This dataset is a 3D building multipatch created using lidar point cloud bare earth points and building points to create a normalized data surface. Some areas have limited data. The lidar dataset redaction was conducted under the guidance of the United States Secret Service. All data returns were removed from the dataset within the United States Secret Service redaction boundary except for classified ground points and classified water points.The scene layer complies with the Indexed 3D Scene layer (I3S) format. The I3S format is an open 3D content delivery format used to disseminate 3D GIS data to mobile, web, and desktop clients.

Buildings within Montgomery County. Building ruins, buildings under construction, and parking garages are also included. Overhead rooftops, or canopies, are shown with a separate feature code and features running under are not clipped out. Each feature is attributed with height in feet and roof type of either gable or flat. This data was captured for use in general mapping at a scale of 1:1200.This dataset contains two types of 2023 building layers:Buildings: 2D polygon features that represent the horizontal area a building covers on the ground. Does not contain building heights or elevation.Buildings_3D: these are created by splitting 2D building footprints to show added building details such as mechanical equipment (like HVAC systems, generators, and water tanks), towers, then adding vertical (height) and horizontal (elevation) dimensions derived from LiDAR. Used in 3D modeling but can be used as 2D footprints as well. Countywide data updated Spring 2023.For more information, contact: GIS Manager Information Technology & Innovation (ITI) Montgomery County Planning Department, MNCPPC T: 301-650-5620.

Microsoft Buildings Footprints with Heights from service: https://services.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/MS_Buildings_Training_Data_with_Heights/FeatureServer (restrictions, do not use)Source: Approx. 9.8 million building footprints for portions of metro areas in 44 US States in Shapefile format.Microsoft recently released a free set of deep learning generated building footprints covering the United States of America. As part of that project Microsoft shared 8 million digitized building footprints with height information used for training the Deep Learning Algorithm. This map layer includes all buildings with height information for the original training set that can be used in scene viewer and ArcGIS pro to create simple 3D representations of buildings. Learn more about the Microsoft Project at the Announcement Blog or the raw data is available at Github.Click see Microsoft Building Layers in ArcGIS Online.Digitized building footprint by State and CityAlabamaGreater Phoenix City, Mobile, and MontgomeryArizonaTucsonArkansasLittle Rock with 5 buildings just across the river from MemphisCaliforniaBakersfield, Fresno, Modesto, Santa Barbara, Sacramento, Stockton, Calaveras County, San Fran & bay area south to San Jose and north to CloverdaleColoradoInterior of DenverConnecticutEnfield and Windsor LocksDelawareDoverFloridaTampa, Clearwater, St. Petersburg, Orlando, Daytona Beach, Jacksonville and GainesvilleGeorgiaColumbus, Atlanta, and AugustaIllinoisEast St. Louis, downtown area, Springfield, Champaign and UrbanaIndianaIndianapolis downtown and Jeffersonville downtownIowaDes MoinesKansasTopekaKentuckyLouisville downtown, Covington and NewportLouisianaShreveport, Baton Rouge and center of New OrleansMaineAugusta and PortlandMarylandBaltimoreMassachusettsBoston, South Attleboro, commercial area in Seekonk, and SpringfieldMichiganDowntown DetroitMinnesotaDowntown MinneapolisMississippiBiloxi and GulfportMissouriDowntown St. Louis, Jefferson City and SpringfieldNebraskaLincolnNevadaCarson City, Reno and Los VegasNew HampshireConcordNew JerseyCamden and downtown Jersey CityNew MexicoAlbuquerque and Santa FeNew YorkSyracuse and ManhattanNorth CarolinaGreensboro, Durham, and RaleighNorth DakotaBismarckOhioDowntown Cleveland, downtown Cincinnati, and downtown ColumbusOklahomaDowntown Tulsa and downtown Oklahoma CityOregonPortlandPennsylvaniaDowntown Pittsburgh, Harrisburg, and PhiladelphiaRhode IslandThe greater Providence areaSouth CarolinaGreensville, downtown Augsta, greater Columbia area and greater Charleston areaSouth Dakotagreater Pierre areaTennesseeMemphis and NashvilleTexasLubbock, Longview, part of Fort Worth, Austin, downtown Houston, and Corpus ChristiUtahSalt Lake City downtownVirginiaRichmondWashingtonGreater Seattle area to Tacoma to the south and Marysville to the northWisconsinGreen Bay, downtown Milwaukee and MadisonWyomingCheyenne

This layer represents 3D buildings with roof types (LOD2) for Chattanooga The data set was derived from Lidar provided by Hamilton County (2022) and attributes for building height and roof type were calculated using ArcGIS Pro. This data was created by the University of Tennessee at Chattanooga IGTLab.

swissBUILDINGS3D 3.0 Beta is a vector based dataset provided by swisstopo which describes buildings as 3D models with roof geometries and roof overhangs. The detailed roof structures are recorded in three dimensions and enhanced with additional information as attributes. The high degree of detail in all three dimensions, together with the high coverage and realistic rendering of the building volumes, make this product a valuable basic dataset for a large range of applications. swissBUILDINGS3D 3.0 is updated every six years.With the current relesase of swissBUILDINGS3D 3.0 Beta, swisstopo provides building models structred according to the federal building identifier (EGID) and containing the EGID as additional information. The data are available in the cantons AG, AI, AR, BE, BL, BS, GL, JU, SG, SZ, TG and the city of Zurich.Application examplesThis scene layer can be applied in a broad range of areas, and constitutes an ideal planning and visualization tool for planners, environmental engineers, public authorities, architects, etc. For example, this data offers the ideal background data for the following use cases:3D visualizations (e.g. tourism, marketing, information)Basis of urban and spatial planning, residential development projects, mobility, telecommunications or energyVisibility and shadow analysesCalculation of solar potentialSimulation of natural disastersAnalyses of distribution (noise, air pollutants, electromagnetic radiation)Ecology and urban climatologyAttributes with identifiers from the Swiss official commune register were added and allow filtering by municipalities, districts or cantons.Use LV95 Swiss Terrain 3D as elevation layer for best results.This scene layer is provided in CH1903+ LV95 projection (EPSG 2056).The source data can be downloaded from swisstopo's website.Data vintage: December 2024. The service is updated semiannually.

Microsoft recently released a free set of deep learning generated building footprints covering the United States of America. As part of that project Microsoft shared 8 million digitized building footprints with height information used for training the Deep Learning Algorithm. This map layer includes all buildings with height information for the original training set that can be used in scene viewer and ArcGIS pro to create simple 3D representations of buildings. Learn more about the Microsoft Project at the Announcement Blog or the raw data is available at Github.Click see Microsoft Building Layers in ArcGIS Online.Digitized building footprint by State and City

Alabama Greater Phoenix City, Mobile, and Montgomery

Arizona Tucson

Arkansas Little Rock with 5 buildings just across the river from Memphis

California Bakersfield, Fresno, Modesto, Santa Barbara, Sacramento, Stockton, Calaveras County, San Fran & bay area south to San Jose and north to Cloverdale

Colorado Interior of Denver

Connecticut Enfield and Windsor Locks

Delaware Dover

Florida Tampa, Clearwater, St. Petersburg, Orlando, Daytona Beach, Jacksonville and Gainesville

Georgia Columbus, Atlanta, and Augusta

Illinois East St. Louis, downtown area, Springfield, Champaign and Urbana

Indiana Indianapolis downtown and Jeffersonville downtown

Iowa Des Moines

Kansas Topeka

Kentucky Louisville downtown, Covington and Newport

Louisiana Shreveport, Baton Rouge and center of New Orleans

Maine Augusta and Portland

Maryland Baltimore

Massachusetts Boston, South Attleboro, commercial area in Seekonk, and Springfield

Michigan Downtown Detroit

Minnesota Downtown Minneapolis

Mississippi Biloxi and Gulfport

Missouri Downtown St. Louis, Jefferson City and Springfield

Nebraska Lincoln

Nevada Carson City, Reno and Los Vegas

New Hampshire Concord

New Jersey Camden and downtown Jersey City

New Mexico Albuquerque and Santa Fe

New York Syracuse and Manhattan

North Carolina Greensboro, Durham, and Raleigh

North Dakota Bismarck

Ohio Downtown Cleveland, downtown Cincinnati, and downtown Columbus

Oklahoma Downtown Tulsa and downtown Oklahoma City

Oregon Portland

Pennsylvania Downtown Pittsburgh, Harrisburg, and Philadelphia

Rhode Island The greater Providence area

South Carolina Greensville, downtown Augsta, greater Columbia area and greater Charleston area

South Dakota greater Pierre area

Tennessee Memphis and Nashville

Texas Lubbock, Longview, part of Fort Worth, Austin, downtown Houston, and Corpus Christi

Utah Salt Lake City downtown

Virginia Richmond

Washington Greater Seattle area to Tacoma to the south and Marysville to the north

Wisconsin Green Bay, downtown Milwaukee and Madison

Wyoming Cheyenne

This web scene shows how you can visualize building floor information together with a photorealistic 3D mesh.Layers:photorealistic 3D mesh created with Sure for ArcGIS3D floor polygons generated from 2D building footprints ()Building footprints sourced from the Dutch Cadastre supplemented with floor attributes3D floor plan lines manually digitized in 3D.Water polygons rendered with water style 3D floor polygons were automatically generated from the building footprint polygon feature layer using a Python notebook. A related table contains the floor information. 3D floor polygons are extruded by height (coming from related table) and symbolized by space use, fire risk and lease end date (also coming from the related table).Questions or comments? Please send us an email.