Abstract
Abstract. Urban digital twins have been increasingly adopted by cities worldwide. Digital twins, especially semantic 3D city models as key components, have quickly become a crucial platform for urban monitoring, planning, analyses and visualization. However, as the massive influx of data collected from cities accumulates quickly over time, one major problem arises as how to handle different temporal versions of a virtual city model. Many current city modelling deployments lack the capability for automatic and efficient change detection and often replace older city models completely with newer ones. Another crucial task is then to make sense of the detected changes to provide a deep understanding of the progresses made in the cities. Therefore, this research aims to provide a conceptual framework to better assist change detection and interpretation in virtual city models. Firstly, a detailed hierarchical model of all potential changes in semantic 3D city models is proposed. This includes appearance, semantic, geometric, topological, structural, Level of Detail (LoD), auxiliary and scoped changes. In addition, a conceptual approach to modelling most relevant stakeholders in smart cities is presented. Then, a model - reality graph is used to represent both the different groups of stakeholders and types of changes based on their relative interest and relevance. Finally, the study introduces two mathematical methods to represent the relevance relations between stakeholders and changes, namely the relevance graph and the relevance matrix.
Highlights
Urban modelling and digitalization is gaining traction globally
The number of transformative urban digital twin and city modelling deployments is expected to grow from a handful of early implementations in 2019 to exceed 500 by 2025 (ABI Research, 2019)
This research aims to provide a conceptual framework to better interpret changes in semantic 3D city models encoded in CityGML
Summary
Urban modelling and digitalization is gaining traction globally. The number of transformative urban digital twin and city modelling deployments is expected to grow from a handful of early implementations in 2019 to exceed 500 by 2025 (ABI Research, 2019). Digital twins, especially their virtual city models, have quickly become a crucial platform for storing, visualizing and monitoring urban objects, and for urban interpretation, simulation and analyses in general This involves many types of transformation on the virtual city models, such as refinement, generalization, derivation and enrichment (see Figure 1b). In contrast to virtual reality (VR) models that focus exclusively on the geometrical and graphical aspects, CityGML represents city objects in classes and relations with respect to their semantic, geometric, topolo- This research aims to provide a conceptual framework to better interpret changes in semantic 3D city models encoded in CityGML This includes a more refined model of changes and stakeholders as well as mathematical methods to represent the relevance relations between different groups of stakeholders and different types of changes.
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