This paper presents a process to develop a CityGML-based 3D city model that, together with results from a flood simulation, can be used to investigate direct and indirect effects of floods on a city, its inhabitants and its critical infrastructure, and to quantify such effects by means of a Flood Resilience Score. In addition, the model can be used as a spatial planning support tool for urban planners to prioritise the redevelopment of certain areas and to test new spatial design decisions. First, a semantic 3D city model is prepared and enriched with additional building and infrastructure information. Then a Flood Resilience Score (FReSco) is defined and computed by quantifying the direct and indirect impacts of flooding on buildings, households, and critical infrastructure points using information from both the 3D city model and the flood simulation results. Lastly, a prototype of a spatial planning support tool is proposed to evaluate the flood resilience of a new environmental plan. As a case study, the neighbourhood of “Nieuw Kralingen” in Rotterdam was chosen. Overall, the outcomes of this work are meant to help cities better understand the impacts of flooding and adjust their urban planning activities accordingly. At the same time, the developed methodology also tests the strengths and limits of CityGML-based 3D city models in combination with openly available data and software.@en

Urban areas face increasing pressure due to densification, presenting numerous challenges involving various stakeholders. The impact of densification on human well-being in existing urban areas can be both positive and negative, which requires a comprehensive understanding of its consequences. Computational Urban Design (CUD) emerges as a valuable tool in this context, offering rapid generation and evaluation of design solutions, although it currently lacks consideration for human perception in urban areas. This research addresses the challenge of incorporating human perception into computational urban design in the context of urban densification, and therefore demonstrates a complete process. Using Place Pulse 2.0 data and multinomial logit models, the study first quantifies the relationship between volumetric built elements and human perception (beauty, liveliness, and safety). The findings are then integrated into a Grasshopper-based CUD tool, enabling the optimization of parametric designs based on human perception criteria. The results show the potential of this approach. Finally, future research and development ideas are suggested based on the experiences and insights derived from this study.@en