Son H. Nguyen and Felix Olbrich from the Chair of Geoinformatics have contributed two new webinars to the CUT Academy in October 2024, which focus on the new features in CityGML 3.0 and its graph-based applications. In the “Connected Urban Twins” (CUT) project, Urban Digital Twins (UDT) are being jointly developed for integrated urban development. The CUT Academy serves as a platform for the exchange and discussion of knowledge - both between the partners of the CUT project and with the public, for example through webinars.
Video 1: New Features in CityGML 3.0
Video 2: Graph-based Applications of CityGML
Video 1: New Features in CityGML 3.0
CityGML 3.0 is an official international OGC standard since 2023. This video summarizes the most important new features of the new version.
A brief overview:
- New and revised modules: In addition to revised modules such as CityGML Core, Generics, Building and Transportation, CityGML 3.0 also has new modules such as Dynamizer, Versioning, PointCloud and Construction.
- New concepts for spaces and space boundaries: All city objects are now based on the concept of Space and SpaceBoundary; all geometries are bound to it.
- Interior modelling without LOD4: CityGML 3.0 enables interior modeling in any LOD. This eliminates the need for LOD4.
- Modelling of changes: Fast, dynamic changes are handled by the Dynamizer module, while slow changes are handled by the Versioning module.
- Improved representation of transportation infrastructure: CityGML 3.0 allows for a detailed representation of street space as part of a standardized and consistent semantic 3D city model.
Further resources:
- Kutzner, T., Chaturvedi, K. & Kolbe, T.H. CityGML 3.0: New Functions Open Up New Applications. PFG 88, 43–61 (2020). https://doi.org/10.1007/s41064-020-00095-z
- Official OGC page of CityGML
- Online Demos for CityGML 3.0
Video 2: Graph-based Applications of CityGML
City objects, especially those encoded in CityGML, are structured like graphs. This video presents two applications that use graph representations of CityGML datasets: (1) Identification and interpretation of changes to a city, and (2) Multimodal navigation using detailed street space modelling of a city.
A brief overview:
- Graph structure of CityGML: CityGML objects are structured like graphs. Graph-based methods and algorithms can therefore be applied.
- The Neo4j graph database: In the applications presented, graph representations of city objects are stored in the Neo4j graph database. Neo4j is currently one of the most popular graph databases worldwide.
- Identification and interpretation of changes: Graphs can be used to compare CityGML datasets with each other to detect changes. These changes are then interpreted to identify meaningful patterns for specific stakeholders.
- Multimodal navigation: Graph representations of street spaces in CityGML 3.0 can also be used to enable multimodal navigation.
- Interactive Neo4j tutorials: This video is accompanied by interactive tutorials for Neo4j and its query language Cypher.
Further resources:
- GitHub repository for identification and interpretation of changes in CityGML graphs
- GitHub repository for the construction of knowledge graphs from semantic 3D city models
- GitHub repository for multimodal navigation in CityGML 3.0