Reconstruction by components for automated updating of 3D city models

3D city models are of interest for various reasons like urban planning, environmental simulations of urban climate and noise pollution, disaster simulations, virtual tourism, virtual-heritage conservation, etc. To create and update large-scale 3D city models efficiently, automated approaches to 3D reconstruction are in great demand. Aside from efficiency, reliability and flexibility are of crucial importance. The derived reconstruction results should be reliable in that they correspond to the observed buildings in both their geometry and their structural topology. Flexibility should ensure the derivation of 3D reconstructions for the most common urban building structures without being limited in descriptive power to only some specific building types. To ensure efficiency, reliability, and flexibility of automated 3D building reconstruction, we propose an approach that combines two paradigms. First, we employ the fusion of information derived from different sensors and map data from a geographic information system. Second, we employ a semantic and component-based approach to model and reconstruct complex buildings. The derived geometrical and semantic building description is utilized within a spatial information system to support spatial and semantic queries for the maintenance and updating of the derived 3D city models.