Volume IV-4/W7 | Copyright
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-4/W7, 43-50, 2018
https://doi.org/10.5194/isprs-annals-IV-4-W7-43-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Sep 2018

20 Sep 2018

MODELLING BELOW- AND ABOVE-GROUND UTILITY NETWORK FEATURES WITH THE CITYGML UTILITY NETWORK ADE: EXPERIENCES FROM ROTTERDAM

X. den Duijn1, G. Agugiaro2, and S. Zlatanova3 X. den Duijn et al.
  • 1TU Delft, Faculty of Architecture and the Built Environment, The Netherlands
  • 2AIT - Austrian Institute of Technology, Center for Energy, Smart and Resilient Cities Unit, Austria
  • 3University of New South Wales, Faculty of the Built Environment, Australia

Keywords: Utility networks, CityGML, Utility Network ADE, 3D City Database, PgRouting

Abstract. 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.

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