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CityGML datasets
All datasets can be downloaded freely, but may be used for evaluation, research, and education purposes only. Please note the respective copyrights. Click on a small image in order to view an enlarged version.
Most datasets are now available in CityGML version 1.0.0, version 0.4.0, and version 0.3.0. Please note that
- datasets of version 0.4.0 or higher employ the new appearance model, and
- datasets of version 1.0.0 use the new CityGML modularisation.
Within the new files all GML objects, i.e. all geometry and feature objects, have been assigned unique gml:id values. It is highly recommended to keep track of and to preserve these IDs in applications in order to be able to consistently maintain CityGML models within GIS and spatial database management systems. For the creation of ID values it is recommended to use global unique IDs (UUID).
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| The media::lab of Karlsruhe University of Applied Sciences provides CityGML datasets for several small villages. One of these small villages is Waldbruecke in the state of Baden-Wuerttemberg in Germany. It contains 606 buildings and building parts on 525 different ground patches, including transportation, waterbody and some solitary vegetation objects. Further geometry and semantic content for these objects will be added subsequently. The corresponding CityGML files of app. 6.5 Mbyte have been compiled from real data. For security reasons, the georeference has been removed in favor of a simple local coordinate system. Note, that as a particularity the CityGML file has been generated from a local database of the WB3 project. |
| A huge CityGML file (44 GB uncompressed!) is available below. The file was created from 22x22 copies of the Ettenheim dataset. Furthermore, the single LOD4 building available on this site has been added four times to each copy in order to enrich the Ettenheim city model with LOD4 data. The coordinate values of each copy are updated such that all copies are spatially arranged in a grid. Also the ID values are updated such that no two identical ID values are contained. This dataset is intended to be used to evaluate CityGML processing tools, visualization systems, and 3D spatial databases with respect to performance and their capabilities to handle really large models. |
| The files are a snapshot from an area around Leverkusen in Germany. This type of data was produced for the whole state of North-Rhine Westphalia (18 million citizens). It is being used for the computation of noise immission maps in order to implement the directive of the European Commission on Environmental Noise 2002/49/EC. The files include simple (LOD0 and LOD1) but semantically rich feature data including application specific data for noise dispersion simulation. |
| Virtual 3D city model of Ettenheim in Germany, automatically derived from an IFC dataset and manually enriched wrt. the employed CityGML feature types. This dataset contains most of the different CityGML top level feature types (Building, ReliefFeature, WaterBody, Road, CityFurniture, PlantCover, GenericCityObject) in LOD3. Please note, that it may take a few minutes to load the file into the Aristoteles Viewer. |
| Buildings (in LOD2) and true orthophoto of a small area around the 'Pariser Platz' in Berlin, Germany (including the famous 'Brandenburger Tor'). All buildings contain a number of thematic attributes including their addresses. |
| Buildings (in LODs 1 and 2) around the 'Alexanderplatz' in Berlin, Germany. These models have been converted from graphical models (in 3DS format) and do not contain semantic information. |
| This sample of building data is derived from Ordnance Survey Great Britain data and is therefore Crown copyright. All rights reserved. It may be download and used for research purposes only. Any form of commercial use is strictly prohibited. |
| Four buildings in Level-of-Detail 3, automatically generated from IFC data (Industry Foundation Classes) while preserving the object semantics like roofs, windows, walls etc. |
| Single building in Level-of-Detail 4, automatically generated from IFC data (Industry Foundation Classes) while preserving the object semantics like roofs, windows, walls. The building model also contains interior structures like rooms, interior walls, doors etc. |
| Textured model of Castle Herten (near Recklinghausen). The model was originally created for graphical presentations and therefore does not contain semantic information. Buildings, building parts and installations are equally represented as CityGML Building features. |
| Roughly textured model of the area around the Drachfelsstraße in Königswinter, Germany. The dataset contains buildings, roads, and a TIN relief in LOD1. |
Street setting in Frankfurt with 5 textured buildings in LOD 3. The models were designed as part of a larger project which shows traffic planning. The buildings are designed in-depth with the following items: window frames, dormers, balconies, chimneys, rain gutters, entrance stairs and billboards. The following feature types are represented: Building, RoofSurface, WallSurface, GroundSurface, Window, Door, BuildingInstallation, LandUse, Road, TrafficArea, AuxiliaryTrafficArea, and Address. 
More datasets can be found on the CityGML Wiki or on the CityGML webpage of the Helmholtz Research Center Karlsruhe, Institute for Applied Computer Science. The models on that website were automatically derived from IFC models. The original IFC models can be found here.
Created and maintained by Thomas H. Kolbe
Last update: 2009-11-27