Urban dynamics modelling using system dynamic approaches aims to provide an understanding of the major internal forces controlling the balance of urban factors such as population, housing and industry within an urban area. It supports decision and policy making in order to improve the quality of life of the citizens. Urban systems are strongly related to the urban space. Since today, the state of the urban space is well described by geospatial data, the connection of system dynamics (SD) and geospatial data is advantageous, both for feeding spatial information into system dynamics models and for further spatial analyses and for visualizing the results of system dynamics models in the geographic context. While the use of two-dimensional geodata in combination with SD models is already described in the literature, there are currently no publications on coupling SD models with semantic 3D city models. In this paper an approach is described to combine an urban dynamics model with a semantic 3D city model structured according to the CityGML standard for a use case regarding urban densification. Our approach shows that a bidirectional data exchange between a semantic 3D city models and an SD model is possible and predictions generated by the SD model are improved using information derived from the city model. Furthermore, we show that automatic modification of the semantic 3D city model by the output of the SD model allows for 3D visualization of future scenarios and for further impact analysis, which can support decision making and public participation. Since semantic 3D city models and SD models have complex data structures and since the models have evolved in very different domains, integrating the models is a complex task. In order to facilitate the integration process, the approach described in this paper develops a conceptual model. The conceptual model formally describes the data structures of the semantic 3D city model and of the SD model as well as the bidirectional relations between the models using the concept of model weaving. The approach was tested using the system dynamics tool Vensim and a CityGML data set that covers an area of the inner city of Munich which is affected by land scarcity, requiring vertical growth of building structures. The bidirectional data exchange between these models is achieved using spatial extract transform load (ETL) proceses, implemented in the Feature Manipulation Engine (FME) software package.     «

Urban dynamics modelling using system dynamic approaches aims to provide an understanding of the major internal forces controlling the balance of urban factors such as population, housing and industry within an urban area. It supports decision and policy making in order to improve the quality of life of the citizens. Urban systems are strongly related to the urban space. Since today, the state of the urban space is well described by geospatial data, the connection of system dynamics (SD) and geo...     »