Visualisation and Generalisation of 3D City Models
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Visualisation and Generalisation of 3D City Models Bo Mao August 2010 TRITA SoM 2010-08 ISSN 1653-6126 ISRN KTH/SoM/-10/08/-SE ISBN 978-91-7415-715-4 © Bo Mao 2010 Licentiate Thesis Geoinformatics Division Department of Urban Planning and Environment Royal Institute of Technology (KTH) SE-100 44 STOCKHOLM, Sweden ii Abstract 3D city models have been widely used in different applications such as urban planning, traffic control, disaster management etc. Effective visualisation of 3D city models in various scales is one of the pivotal techniques to implement these applications. In this thesis, a framework is proposed to visualise the 3D city models both online and offline using City Geography Makeup Language (CityGML) and Extensible 3D (X3D) to represent and present the models. Then, generalisation methods are studied and tailored to create 3D city scenes in multi- scale dynamically. Finally, the quality of generalised 3D city models is evaluated by measuring the visual similarity from the original models. In the proposed visualisation framework, 3D city models are stored in CityGML format which supports both geometric and semantic information. These CityGML files are parsed to create 3D scenes and be visualised with existing 3D standard. Because the input and output in the framework are all standardised, it is possible to integrate city models from different sources and visualise them through the different viewers. Considering the complexity of the city objects, generalisation methods are studied to simplify the city models and increase the visualisation efficiency. In this thesis, the aggregation and typification methods are improved to simplify the 3D city models. Multiple representation data structures are required to store the generalisation information for dynamic visualisation. One of these is the CityTree, a novel structure to represent building group, which is tested for building aggregation. Meanwhile, Minimum Spanning Tree (MST) is employed to detect the linear building group structures in the city models and they are typified with different strategies. According to the experiments results, by using the CityTree, the generalised 3D city model creation time is reduced by more than 50%. Different generalisation strategies lead to different outcomes. It is important to evaluate the quality of the generalised models. In this thesis a new evaluation method is proposed: visual features of the 3D city models are represented by Attributed Relation Graph (ARG) and their similarity distances are calculated with Nested Earth Mover’s Distance (NEMD) algorithm. The calculation results and user survey show that the ARG and NEMD methods can reflect the visual similarity between generalised city models and the original ones. Keywords : 3D city models, Visualisation, CityGML, X3D, Generalisation, Aggregation, Typification, Quality evaluation iii Acknowledgements I am grateful to my supervisors, Professor Yifang Ban, KTH and Associate Professor Lars Harrie, Lund University, for their constant support, instruction, guidance, facilitation and encouragement during the research and daily life throughout the duration of my study in Sweden. Thanks all the staff and PhD students at Geoinformatics Division, KTH. The united international team gives me inspiration and feelings of home. I am also grateful to Helen Rost from Blom AB and Peter Axelsson from Digpro AB for the 3D data in the research. Erik Olsson and Hongchao Fan also assisted in this thesis research. I would like to thank China Scholarship Council and School of Architecture and Built Environment at KTH for providing the scholarship (2008-2012). I also thank the school of Computer Science and Engineering, Southeast University, China for the chance to study abroad. This Work has been carried out as part of a ViSuCity research project funded by the Knowledge Foundation, Swedish Foundation for Strategic Research, Vinnova, The Swedish Foundation for Health Care Sciences and Allergy Research, and Invest in Sweden. Finally, I would like to thank my family and my friends for their support all along. Bo Mao Stockholm, August 2010 iv Table of Contents 1. Introduction .......................................................................................................1 1.1 Background ..................................................................................................1 1.1.1 Use of 3D city model.............................................................................1 1.1.2 Related technologies of 3D city model .................................................2 1.1.3 The current research status of 3D city models......................................4 1.2 Research objectives......................................................................................7 1.3 Organisation of the thesis ............................................................................8 2. Literature review .............................................................................................11 2.1 Representation of 3D city models – CityGML..........................................11 2.1.1 CityGML overview .............................................................................11 2.1.2 CityGML module and levels of detail.................................................13 2.1.3 CityGML resources .............................................................................14 2.1.4 Other related standards........................................................................15 2.2 Visualisation of 3D city models.................................................................17 2.2.1 Introduction .........................................................................................17 2.2.2 X3D .....................................................................................................18 2.2.3 KML and other standards....................................................................19 2.2.4 Future development.............................................................................20 2.3 Generalisation of 3D city models ..............................................................22 2.3.1 Generalisation algorithm.....................................................................22 2.3.2 Generalisation evaluation....................................................................24 3 Related methodologies .....................................................................................25 3.1 Visualisation frameworks ..........................................................................25 3.1.1 Direct visualisation..............................................................................25 3.1.2 Visualisation using 3D standards ........................................................25 3.1.3 Visualisation of CityGML...................................................................28 3.2 Dynamic generalisation and visualisation .................................................31 3.2.1 Aggregation .........................................................................................31 3.2.2 Dynamic typification...........................................................................34 v 3.2.3 Multiple representation data structure.................................................37 3.3 Generalisation evaluation ..........................................................................38 4 Results and Discussions ...................................................................................41 4.1 Introduction................................................................................................41 4.2 Visualisation framework............................................................................41 4.3 Multiple representation data structure .......................................................43 4.4 Generalisation results evaluation...............................................................45 4.5 Typification based on MST .......................................................................46 5 Conclusions and future research ......................................................................49 5.1 Conclusions................................................................................................49 5.2 Future research...........................................................................................50 References ...........................................................................................................51 vi List of Figures Figure 2.1 The five levels of detail (LODs) defined by CityGML (source: IGG Uni Bonn) .....................................................................................14 Figure 2.2 Relationship among VDI 3805, IFC and CityGML .........................16 Figure 3.1 A topographic map (source: Eran et al., 2005).................................27 Figure 3.2 Workflow scheme of X3D model generation...................................27 Figure 3.3 The architecture of a web 3D service (source: Reitz et al., 2009)....28 Figure 3.4 The system architecture of the virtual 3D city model of Berlin (source: Döllner et al., 2006)...............................................................................29 Figure 3.6 Direct merge (Source: Bundy et al., 1995).......................................31 Figure 3.7 Snap merge (source: Bundy et al., 1995)..........................................32 Figure 3.8 2D building projections (source: Anders, 2005) ..............................33 Figure 3.9 Aggregation of 3D buildings (source: Anders, 2005) ......................33 Figure 3.10 Aggregation