ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W1, 13-22, 2016
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W1/13/2016/
doi:10.5194/isprs-annals-IV-2-W1-13-2016
 
05 Oct 2016
THE MOST COMMON GEOMETRIC AND SEMANTIC ERRORS IN CITYGML DATASETS
F. Biljecki1, H. Ledoux1, X. Du1, J. Stoter1, K. H. Soon2, and V. H. S. Khoo2 13D Geoinformation, Delft University of Technology, Delft, the Netherlands
2Singapore Land Authority, Singapore
Keywords: CityGML, 3D city models, Quality control, Validation, Error Abstract. To be used as input in most simulation and modelling software, 3D city models should be geometrically and topologically valid, and semantically rich. We investigate in this paper what is the quality of currently available CityGML datasets, i.e. we validate the geometry/topology of the 3D primitives (Solid and MultiSurface), and we validate whether the semantics of the boundary surfaces of buildings is correct or not. We have analysed all the CityGML datasets we could find, both from portals of cities and on different websites, plus a few that were made available to us. We have thus validated 40M surfaces in 16M 3D primitives and 3.6M buildings found in 37 CityGML datasets originating from 9 countries, and produced by several companies with diverse software and acquisition techniques. The results indicate that CityGML datasets without errors are rare, and those that are nearly valid are mostly simple LOD1 models. We report on the most common errors we have found, and analyse them. One main observation is that many of these errors could be automatically fixed or prevented with simple modifications to the modelling software. Our principal aim is to highlight the most common errors so that these are not repeated in the future. We hope that our paper and the open-source software we have developed will help raise awareness for data quality among data providers and 3D GIS software producers.
Conference paper (PDF, 5961 KB)


Citation: Biljecki, F., Ledoux, H., Du, X., Stoter, J., Soon, K. H., and Khoo, V. H. S.: THE MOST COMMON GEOMETRIC AND SEMANTIC ERRORS IN CITYGML DATASETS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W1, 13-22, doi:10.5194/isprs-annals-IV-2-W1-13-2016, 2016.

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