Many research fields analysing urban space depend on 3D city models. However, 3D city models still are often of a low geometric quality. Due to topo- logical errors it is not possible to compute volumetric information for many buildings in real world datasets using analytical approaches. Since this volumetric information is important for many applications we present a method to approximate the volume of building models overcoming topological errors. The method is based on a voxelisation and a generalisation of the point-in-polygon test to three dimensions. We show in extensive tests that the method produces accurate results and is able to cope with different types of errors. Beyond the computation of volumes, the proposed approach potentially has a high impact for numerous applications like healing of building models, indoor routing or model transformation.     «

Many research fields analysing urban space depend on 3D city models. However, 3D city models still are often of a low geometric quality. Due to topo- logical errors it is not possible to compute volumetric information for many buildings in real world datasets using analytical approaches. Since this volumetric information is important for many applications we present a method to approximate the volume of building models overcoming topological errors. The method is based on a voxelisation and a ge...     »