IDENTIFICATION OF SOLAR POTENTIALS IN URBAN BUILDING STOCK THROUGH ANALYSIS OF URBAN STRUCTURE TYPES BASED ON A SEMANTIC 3D CITY MODEL; [IDENTIFIKATION VON SOLARPOTENZIALEN IM URBANEN GEBÄUDEBESTAND DURCH ANALYSE STADTTYPOLOGISCHER STRUKTUREN ANHAND EINES SEMANTISCHEN 3D-STADTMODELLS]

Abstract

This article investigates how solar energy potential can be identified within existing urban building stock by analysing urban structure types through a semantic 3D city model. Cities contain a wide variety of buildings, roof forms, orientations, heights, and surrounding structures, all of which influence the suitability of surfaces for solar energy generation. A semantic three-dimensional city model provides a structured representation that can connect building geometry with additional information about the urban environment. The article considers how such models can be used to distinguish different urban structure types and evaluate their relevance for solar potential analysis. Spatial analysis can help identify suitable roof areas, consider the influence of neighbouring buildings, and support comparisons between different parts of a city. The approach demonstrates the value of combining three-dimensional urban information with renewable-energy planning. Instead of evaluating individual buildings in isolation, urban structure analysis can provide a broader view of how building arrangements influence available solar resources. Such information can support municipalities, planners, energy providers, and property owners when considering future photovoltaic installations. The quality of the results depends on the completeness and accuracy of the underlying 3D model as well as the assumptions used in the analysis. Nevertheless, semantic city models provide a useful basis for connecting urban planning and energy questions. The study illustrates how geospatial data and 3D modelling can contribute to more informed decisions about renewable energy in densely developed urban environments. The approach therefore demonstrates how semantic 3D city models can connect detailed urban information with practical energy questions and help cities identify realistic opportunities for renewable generation.