Enriching Urban Digital Twins with Energy-related Information from Aerial and Street View Imagery for Precise Urban Climate Modeling
Keywords: 3D City Models, Urban Digital Twins, CityJSON, Urban Climate, Python
Abstract. The country-scale 3D city model of the Netherlands, 3DBAG, has been extensively utilized across multiple disciplines. Buildings in 3DBAG include many attributes, but they lack the necessary ones required for precise urban climate modeling. This study aims to enhance the 3DBAG 3D city model by incorporating energy-related attributes and vegetation data, thereby improving visualization accuracy and realism, as well as enabling more precise urban climate simulations. Automated methods were developed to extract and integrate key features such as roof textures, façade materials, albedo values, roof slopes, and urban vegetation. Roof textures extracted from orthophotos enhance the analysis of roof geometry and facilitate material identification and solar panel detection. Meanwhile, façade materials and albedo values contribute to more accurate simulations of heat absorption, energy balance, and urban heat island effects. Furthermore, the integration of detailed urban vegetation data, including tree height and crown diameter, allows for accurate modeling of vegetation's influence on urban microclimates. Developed automated workflows significantly reduce the time and effort required for manual data preparation and integration. By enriching the urban digital twins with energy-related information, this study provides researchers with a more comprehensive and precise dataset, enabling more accurate analyses in urban climate modeling. The developed automated workflows can be applied in future releases of the 3DBAG, allowing other users in utilizing the energy-enriched 3D city model effectively. Web-based visualization of the energy-enriched 3D city model can be explored at https://bit.ly/4tuheritage.