Semantic 3D City Modeling and BIM

Kolbe, Thomas H.; Donaubauer, Andreas

doi:10.1007/978-981-15-8983-6_34

Cited by 26 publications

(17 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Digital 3D city models are commonly used for a variety of applications (Biljecki et al, 2015). One of the main advantage of these models is the consistent integration of geometric, semantic and topological information (Kolbe and Donaubauer, 2021). The international OGC standard CityGML is widely used for modelling semantic 3D city models.…”

Section: Potential Of Coupling Point Clouds With Semantic 3d City Modelsmentioning

confidence: 99%

Integration of 3d Point Clouds With Semantic 3d City Models – Providing Semantic Information Beyond Classification

Beil

Kutzner

Schwab

et al. 2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Abstract. A range of different and increasingly accessible acquisition methods, the possibility for frequent data updates of large areas, and a simple data structure are some of the reasons for the popularity of three-dimensional (3D) point cloud data. While there are multiple techniques for segmenting and classifying point clouds, capabilities of common data formats such as LAS for providing semantic information are mostly limited to assigning points to a certain category (classification). However, several fields of application, such as digital urban twins used for simulations and analyses, require more detailed semantic knowledge. This can be provided by semantic 3D city models containing hierarchically structured semantic and spatial information. Although semantic models are often reconstructed from point clouds, they are usually geometrically less accurate due to generalization processes. First, point cloud data structures / formats are discussed with respect to their semantic capabilities. Then, a new approach for integrating point clouds with semantic 3D city models is presented, consequently combining respective advantages of both data types. In addition to elaborate (and established) semantic concepts for several thematic areas, the new version 3.0 of the international Open Geospatial Consortium (OGC) standard CityGML also provides a PointCloud module. In this paper a scheme is shown, how CityGML 3.0 can be used to provide semantic structures for point clouds (directly or stored in a separate LAS file). Methods and metrics to automatically assign points to corresponding Level of Detail (LoD)2 or LoD3 models are presented. Subsequently, dataset examples implementing these concepts are provided for download.

show abstract

Section: Potential Of Coupling Point Clouds With Semantic 3d City Modelsmentioning

confidence: 99%

Integration of 3d Point Clouds With Semantic 3d City Models – Providing Semantic Information Beyond Classification

Beil

Kutzner

Schwab

et al. 2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

show abstract

“…This is typically observed in the composition and aggregation relations. Finally, objects are structured according to their logical criteria and interrelationships (Kolbe and Donaubauer, 2021). City objects are represented using a set of predefined classes such as Building, Bridge, Tunnel, etc.…”

Section: Semantic Changesmentioning

confidence: 99%

“…CityGML defines a common information model and data exchange format for most urban and rural objects such as buildings, bridges, tunnels, transportation, vegetation, etc. 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-gical and appearance properties (Kolbe and Donaubauer, 2021). Moreover, CityGML allows modelling objects in five different Level of Details (LoD 0 -4).…”

Section: Introductionmentioning

confidence: 99%

Modelling Changes, Stakeholders and Their Relations in Semantic 3d City Models

Nguyen

Kolbe

2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

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.

show abstract

“…Integrating information models from the domains Building Information Modeling (BIM) and Urban Information Modeling (UIM) aims to bridge information silos caused by the heterogeneous character of these information models [1][2][3][4][5][6]. A significant reason for the heterogeneous character of information models from the domains BIM and UIM is the diversity of their underlying perspectives and purposes [3][4][5]7,8].…”

Section: Introductionmentioning

confidence: 99%

Analyzing Contextual Linking of Heterogeneous Information Models from the Domains BIM and UIM

Beck

Abualdenien

Hijazi

et al. 2021

IJGI

Self Cite

View full text Add to dashboard Cite

Information models from the domains Building Information Modeling (BIM) and Urban Information Modeling (UIM) are generally considered as information silos due to their heterogeneous character. These information silos can be bridged through linking where corresponding objects are identified and linked subsequently. However, whether two objects are considered as corresponding might depend on the scenario for which the links are created. The dependency of the link creation and the scenario refers to the term contextual linking and is analyzed in this paper with respect to building and city models. Therefore, different situational aspects influencing the link creation are discussed. Afterwards, the issue of contextual linking is demonstrated based on three different integration scenarios. In summary, this paper has three major outcomes: First, this paper introduces an application-oriented perspective on information integration and emphasize the role of the application when linking heterogeneous information models. Second, this paper shows that linking heterogeneous information models from the domains BIM and UIM at instance level depends on the scenario. Third, the results of the discourse about contextual linking serve as a framework supporting the design and development of artifacts for linking heterogeneous information models from the domains BIM and UIM.

show abstract

Semantic 3D City Modeling and BIM

Cited by 26 publications

References 27 publications

Integration of 3d Point Clouds With Semantic 3d City Models – Providing Semantic Information Beyond Classification

Integration of 3d Point Clouds With Semantic 3d City Models – Providing Semantic Information Beyond Classification

Modelling Changes, Stakeholders and Their Relations in Semantic 3d City Models

Analyzing Contextual Linking of Heterogeneous Information Models from the Domains BIM and UIM

Contact Info

Product

Resources

About