Precise and comprehensive knowledge about 3D urban space 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 is needed. Substantial work has been done in the modelling and representation of above-ground features in the context of 3D city modelling. However, the belowground part of the real world, of which utility networks form a big part, is often neglected. Existing data models for utility networks are generally very domain-specific and, therefore, not suitable either. This paper describes a 3D data modelling approach for integrated management of below-ground utility networks and related above-ground city objects. This approach consists of manipulating first the structure of existing utility data in the commonly used Feature Manipulation Engine ETL software in order to make the data compliant to the CityGML Utility Network ADE data model. Subsequently, workspaces are created that take care of storing the CityGML data into the free and open-source 3D City Database, which has been extended in order to manage utility network data, too. Moreover, the research shows the suitability of the extended 3DCityDB to perform graph-based topological operations by means of the PostgreSQL pgRouting extension. Lastly, the results are visualized in typical GIS applications, e.g. QGIS and ArcGIS.@en

Availability of 3D underground information models is key to designing and managing urban infrastructure construction projects. Buried utilities information is often registered by using different types of location data with different uncertainties. These data variances are, however, not considered in many existing visualization approaches. This study, therefore, aims to enable 3D-representation of uncertainties in underground utility data. To this end, the research team identified four different location parameters (unknown, standard, estimated, surveyed location), and explored how these could be integrated into models that visualize utilities in 3D. As proof of concept, we developed a first 3D uncertainty model for an urban road intersection and implemented this in a handheld augmented reality application. As a next step, we designed an improved 3D visualization model that incorporates standard, estimated, and surveyed location data to estimate utility locations, and to generate cylinder shapes that represent the uncertainty buffer around a visualized utility. The presented approach eventually allows city engineers to better estimate design and construction workspaces. We conclude the paper by elaborating both the contributions and consecutive research steps.@en