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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.
All 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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| 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. |
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.
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: 2008-09-02