IDENTIFICATION OF SOLAR POTENTIALS IN URBAN BUILDING STOCK THROUGH ANALYSIS OF URBAN STRUCTURE TYPES BASED ON A SEMANTIC 3D CITY MODEL

Abstract

This article concerns methods for identifying solar-energy potential across urban building stock by analysing urban structure types with a semantic 3D city model. Three-dimensional building information can represent roof geometry, orientation, surrounding structures, and other spatial characteristics relevant to solar exposure. When combined with semantic classifications of urban form, these models can support systematic comparisons between buildings and neighbourhoods. The approach can help planners and energy specialists move from isolated building assessments toward city-scale analysis, making it easier to identify promising areas and understand how urban morphology influences potential generation. The quality of results depends on model accuracy, appropriate assumptions, and the availability of relevant building and environmental data. Spatial analysis can also help communicate findings to municipalities, property owners, and energy planners. The topic sits at the intersection of geoinformatics, 3D city modelling, renewable energy, and sustainable urban development. This abstract is generated from the title and should not be treated as the authors’ original abstract.