Visualisation and Generalisation of 3D City Models

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.