Semantic-assisted CityGML model consistency checking method

The inconsistency of model geometry, topology and semantics of CityGML data caused by the modeling method, model optimization and data conversion are widespread, which affects its further application. A rule set for CityGML building models was proposed and constructed in this paper which takes semantic constraints into account. Relevant algorithms for automatic detection and restoring of CityGML LOD2/LOD3/LOD4 multi-level-of-detail building model data are designed. Open data downloaded from OGC website was used to verify the rules and algorithms. Experimental results demonstrate that the constructed consistency rule set was complete and self-consistent, and proposed corresponding algorithms can detect most of the topology inconsistencies in CityGML building model data, and can automatically repair some of the topological and geometric errors