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

Nguyen, Son H.; Kolbe, Thomas H.

doi:10.5194/isprs-annals-viii-4-w2-2021-137-2021

Cited by 11 publications

(7 citation statements)

References 12 publications

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“…Former data and computed representation need to be prepared and distributed in a suitable manner to be accessible in the frontend where the SCDT is presented to decision makers and urban planners, and with limited capabilities to a wide public, too. Implemented interactions have to include the capability to change the point of view (R19), to select entities to access additional information (R21.i, R21.ii, R22, R26) [41], to load different models (R21.iii) [42], and to act on lighting (R20) [43]. To provide more immediate interpretation of visualized data, entities such as PINs (to indicate POI, devices, dehors, etc., on maps), shapes, paths, etc., should be represented with characteristic visualizations (R16) [44].…”

Section: R3 Logics For Data Transformationmentioning

confidence: 99%

Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution

Adreani,

Bellini,

Fanfani

et al. 2024

IEEE Access

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Digital Twins are becoming fundamental tools to monitor the status of entities, predict their future evolution and simulate alternative scenarios to understand the impact of possible changes for planning and design. More recently, Digital Twin solutions have been applied in the context of Smart Cities. Thanks to the large deployment of sensors, together with the increasing amount of information available for municipalities and governmental organizations, it is possible to build wide virtual reproductions of urban environments including structural data and real-time information that can undoubtfully help decision makers to face future challenges in urban development and improve the citizens' quality of life. In this paper, the Snap4City Smart City Digital Twin framework is presented, which can respond to the requirements identified in recent literature and by international forums. The proposed architecture provides an integrated solution for data gathering, indexing, computing, and information distribution, thus realizing a continuously updated digital twin of the urban environment at global and local scales for monitoring operation and planning. It addresses 3D building models, road networks, Internet of Things entities, points of interest, paths, as well as results from analytical processes for traffic density reconstruction, pollutant dispersion, predictions, and what-if analysis for assessing impact of changes, all integrated into a freely accessible interactive 3D web interface, enabling stakeholder and citizen participation to city decision processes. As case study, the digital twin of the city of Florence (Italy) is presented, including what-if analysis. The solution is released on top of the Snap4City platform as open-source and made available through our GitHub repository (https://github.com/disit) and as Docker compose.

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Section: R3 Logics For Data Transformationmentioning

confidence: 99%

Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution

Adreani,

Bellini,

Fanfani

et al. 2024

IEEE Access

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“…(Nguyen et al, 2017) then proposed a new approach to comparing arbitrarily large CityGML datasets using a graph database. On the other hand, (Nguyen and Kolbe, 2021) explained the importance and advantage of not only identifying but also understanding and evaluating changes with respect to different groups of stakeholders. In general, the major problems of solving change detection and interpretation in semantic 3D city models can be summarized as follows:…”

Section: Physical Physical Digital Digitalmentioning

confidence: 99%

“…The relevance relations between changes and stakeholders can then be expressed using a table. (Nguyen and Kolbe, 2021) proposed a refined model of changes as well as stakeholders in the context of urban digital twins with semantic 3D city models as one of their key components. The research further provided two mathematical ways to flexibly model the varying relevance relations between different groups of stakeholders and different types of changes, namely using the relevance matrix as well as the relevance graph.…”

Section: Related Workmentioning

confidence: 99%

“…The context information extracted and aggregated in previous layer L1 as explained in Section 3.2.1 can be forwarded to the Change Type Layer L2 to further classify changes, provide scope and therefore potentially identify local, clustered or global (systematic) changes in the dataset. Conceptual models of changes that are compatible with semantic 3D city models, such as proposed by (Nguyen and Kolbe, 2021), can be used to populate the vertices in this layer. The framework proposed in this research allows flexible structuring of each layer, meaning that entire layers can be reorganized into a corresponding graph representation of a class inheritance hierarchy as long as they satisfy the requirements of the network given in Section 3.1.…”

Section: Change Type Layer (L2)mentioning

confidence: 99%

“…as individual beings (citizens), companies (private sectors) and organizations (non-governmental and governmental organizations), etc. Similarly to previous layers, a conceptual model for actors in layer L4 and stakeholders in layer L5, such as proposed by (Nguyen and Kolbe, 2021), can be employed to populate the network.…”

Section: Actor Role Layer (L4) and Stakeholder Layer (L5)mentioning

confidence: 99%

See 2 more Smart Citations

Path-Tracing Semantic Networks to Interpret Changes in Semantic 3d City Models

Nguyen

Kolbe

2022

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

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Abstract. Recent years have seen a significant and rapid rise in the development and deployment of many urban digital twins worldwide. Urban digital twins provide a central platform for incorporating data and knowledge from different sources and fields, and can thus be used for many urban-related processes such as urban planning, analysis, monitoring and visualization. One of the key requirements of digital twins in general and urban digital twins in particular is the continuous, bidirectional data flow between the physical entity and its digital counterpart. Consequently, this requires the ability to both detect and understand changes between different temporal versions of the physical and digital entities. In the context of smart cities and semantic 3D city models however, only a few studies have addressed this so far. This is due to the facts that: (1) Semantic 3D city models (mostly encoded in CityGML) contain multifaceted information modelled in a complex inheritance hierarchy, which complicates their change detection process; (2) As cities constantly evolve over time, matching their datasets often results in a large number of changes, which must be further analysed and processed to produce meaningful information; (3) Individual changes in the datasets are multi-layered as well as often correlated and cannot be fully understood without considering their context in the city model; and (4) Different types of changes are perceived and interpreted differently by different stakeholders, meaning that the outcome of the change detection and interpretation process must ultimately serve the human factor. Therefore, to address these challenges, this research proposes a Path-tracing Semantic Network (PSN) to interpret detected changes in semantic 3D city models. The framework represents the multidimensional nature of changes together with stakeholders in a semantic network, where their interrelations can be analysed explicitly using graph-based path-tracing methods.

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Identification and Interpretation of Change Patterns in Semantic 3D City Models

Nguyen,

Kolbe

2024

Lecture Notes in Geoinformation and Cartography

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Urban Digital Twins have received significant attention in recent years due to their economic and research importance. Although many definitions exist, the general consensus agrees on a continuous twoway data flow between a physical entity and its virtual counterpart in a digital twin. In the context of smart cities and semantic 3D city models, however, no major breakthrough in realizing such complex change detection and analysis systems has yet been achieved. While several methods for change detection in semantic 3D city models have been proposed, the analysis of found changes, especially the identification of patterns among a large number of changes, has not been given as much attention. Without a proper handling of patterns, it is difficult to provide useful interpretation of changes with respect to stakeholders. Therefore, this research proposes a framework to define, detect and decipher complex semantic change patterns in semantic 3D city models. The approach provides a central rule network to describe aggregation relations between changes as well as methods to identify and capture detected change patterns directly in the graph representation of a city model.

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

Cited by 11 publications

References 12 publications

Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution

Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution

Path-Tracing Semantic Networks to Interpret Changes in Semantic 3d City Models

Identification and Interpretation of Change Patterns in Semantic 3D City Models

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