3D spatial data are widely used to simulate various urbanistic phenomena, thanks to their valuable semantic, geometric, and topologic information. CityGML is a highly adopted data standard for semantic 3D city models, providing a standardized description of the cityscape that enables interoperability across different stakeholders. When future scenarios for urban development are simulated, the simulation results can be visualized and further analyzed in synthetically generated 3D city models. However, land use and constructability regulations are often overlooked when generating synthetic 3D city models for simulation purposes, despite some regulatory urban constraints having a direct impact on simulation results. For instance, the roof shape is highly correlated with building solar energy potential, while the zoning maximum allowed number of apartments directly influences the buildings' urban density estimation. Therefore, integrating such constructability knowledge within 3D city models is crucial. This paper proposes a framework for mapping urban planning rules defined in the German XPlanung standard onto 3D city models structured in compliance with CityGML to ensure legislative validity and real-life applicability. We review related work, discuss the structure of CityGML and the main elements concerned by urbanistic laws, explain the main concepts of XPlanung, and investigate the mapping of regulatory information with CityGML entities.
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3D spatial data are widely used to simulate various urbanistic phenomena, thanks to their valuable semantic, geometric, and topologic information. CityGML is a highly adopted data standard for semantic 3D city models, providing a standardized description of the cityscape that enables interoperability across different stakeholders. When future scenarios for urban development are simulated, the simulation results can be visualized and further analyzed in synthetically generated 3D city models. How...
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