Digital Twins are increasingly used as analytical frameworks in urban planning, supporting spatially explicit assessments of climate, energy and environmental risks. Based on interoperable 3D city models (e.g. CityGML/CityJSON) and shared geodata infrastructures, they enable scenario-based evaluations across multiple planning domains. This paper examines how Digital Twin workflows can support planning-oriented simulation tasks, with a particular focus on the interplay between open-source and proprietary tools. Using the city of Landsberg am Lech as an applied case study, four thematic applications are investigated: solar framework planning in a protected historic ensemble, urban heat screening, pluvial flood risk assessment, and environmental noise scenarios. The workflows combine open data – most notably LOD2 building models and digital terrain models – with a hybrid toolchain including QGIS, GRASS GIS, Honeybee, ICETools, H-Risk, as well as proprietary environments such as Rhino/Grasshopper and ArcGIS Pro. The results demonstrate that Digital Twins function most effectively as shared spatial reference systems for planning-oriented screening and orientation analyses, rather than as fully integrated simulation platforms. While physically based models such as PALM-4U represent the state of the art in urban climate modelling, simplified tools proved suitable for early-stage planning and comparative scenario evaluation. Overall, the study shows that hybrid workflows combining open and proprietary tools currently represent best practice, balancing transparency, methodological robustness, and planning relevance.
Zeile et al. (Thu,) studied this question.