Precise and comprehensive knowledge about 3D urban space, critical infrastructures, and below ground features is required for simulation and analysis in the fields of urban and environmental planning, city administration and disaster management. In order to facilitate these applications, geo-information about functional, semantic, and topographic aspects of urban features, their mutual dependencies and relations are needed. Substantial work has been done in the modeling and representation of above ground features in the context of 3D city modelling by means of CityGML. However, the below ground part of the real world, of which utility networks form a big part, is often neglected in 3D city models. At the same time, several existing utility network data models exist. These are, however, commonly tailored to a specific domain and not suitable for the integrated modeling and representation of utility networks and city objects in 3D urban space

This research proposes a 3D data modeling approach for integrated management of below ground utility networks features (viz. electricity and sewer) and related above ground city objects (viz. streetlights and manhole covers). The data modeling approach is successfully examined by implementing relationships between 1) the below ground electricity network and above ground streetlights and 2) between the sewer network and the above ground manhole covers.

Having existing utility network data and city objects as input, a file in CityGML Utility Network ADE format is created. The manipulation of the data structure and content, according the proposed data modeling approach, is completed in FME. The output CityGML dataset allows interoperability but may become very large and objects may be arbitrarily nested leading to complex data structures. Therefore carefully optimized database schemas are required that enables efficient storage, management and data access of the CityGML data. The object-oriented CityGML data model, including the Utility Network ADE, is mapped to a relational database by means of the 3DCityDB. Subsequently, the CityGML data is inserted into the derived relational database. Several relevant (network) analyses are performed by querying the designed relational database. It shows the possibility to simulate what network features are affected by e.g. a utility strike by means of pgRouting and visualization in a GIS.

This research made one of the first attempts to thoroughly model existing utility network data and city objects according the CityGML Utility Network ADE. Following are further research that could optimize the proposed data modeling approach for better decision making in the field of asset management:

- Modeling multiple different utility networks and city objects
- Modeling in a higher LoD
- Detailing the CityGML Utility Network ADE classes and use
- Better investigating on more types of analyses
- Implementing larger datasets
- Implementing datasets with a different accuracy
- Exporting a CityGML file from the relational database
- Better investigating on visualization of the data
- Investigating on how to model different types of relationships