Semantic Modelling of 3D Multi-Utility Networks for Urban Analyses and Simulations: : The CityGML Utility Network ADE
Pages 1 - 34
Abstract
Current data models for representing, exchanging, and storing utility networks often meet the needs of specific domains only, i.e. they do not consider the integration of different network systems, mutual relations between networks and the embedding into 3D urban space. These important prerequisites for urban analyses and simulations are met by the CityGML extension Utility Network ADE. Originally developed for disaster management, this article presents the further development of the ADE by new and revised concepts that result from an extensive analysis of relevant use cases. A catalogue of requirements is presented, current data models are evaluated against these requirements, and the recent developments and refinements of the ADE are explained in detail. This includes the concepts of inter-feature links and network links, the linking of network components with city objects, the modelling of functional characteristics, a refined network components module, and a new electricity network package. In addition, an overview of projects that successfully have applied the ADE is provided.
References
[1]
Agugiaro, G., Benner, J., Cipriano, P., & Nouvel, R. (2018). The Energy Application Domain Extension for CityGML: Enhancing interoperability for urban energy simulations. Open Geospatial Data . Software and Standards, 3(1), 1–30.
[2]
Agugiaro, G., Hauer, S., & Nadler, F. (2015). Coupling of CityGML-based Semantic City Models with Energy Simulation Tools: some Experiences. In REAL CORP 2015. PLAN TOGETHER–RIGHT NOW–OVERALL. From Vision to Reality for Vibrant Cities and Regions, Proceedings of 20th International Conference on Urban Planning, Regional Development and Information Society (pp. 191-200). CORP–Competence Center of Urban and Regional Planning.
[3]
BeckerT.BartelsM.HahneM.HempelL.LiebR. (2012a). Cascading Effects and Interorganisational Crisis Management of Critical Infrastructure Operators. In ZlatanovaS.PetersR.FendelE. (Eds.), Proceedings of the 8th International Conference on Geo-Information for Disaster Management (pp. 105-116).
[4]
Becker, T., Nagel, C., & Kolbe, T. H. (2011). Integrated 3D Modeling of Multi-utility Networks and Their Interdependencies for Critical Infrastructure Analysis. In Kolbe, T. H., König, G., & Nagel, C. (Eds.), Advances in 3D Geo-Information Sciences, Lecture Notes in Geoinformation and Cartography (pp. 122–138). Springer.
[5]
Becker, T., Nagel, C., & Kolbe, T. H. (2012b). Semantic 3D Modeling of Multi-Utility Networks in Cities for Analysis and 3D Visualization. In Pouliot, J., Daniel, S., Hubert, F., & Zamyadi, A. (Eds.), Progress and New Trends in 3D Geoinformation Sciences, Lecture Notes in Geoinformation and Cartography (pp. 41–62). Springer.
[6]
Biljecki, F., Kumar, K., & Nagel, C. (2018). CityGML Application Domain Extension (ADE): Overview of developments. Open Geospatial Data . Software and Standards, 3(1), 1–13.
[7]
Biljecki, F., Stoter, J., Ledoux, H., Zlatanova, S., & Çöltekin, A. (2015). Applications of 3D City Models: State of the Art Review. ISPRS International Journal of Geo-Information, 4(4), 2842–2889.
[8]
Boates, I. (2018b). Sample of Utility Network ADE data model using water network from Nanaimo, Canada. Retrieved from https://github.com/iboates/CityGML-UtilityNetwork-ADE-Nanaimo-Water-Network-Sample
[9]
Boates, I., Agugiaro, G., & Nichersu, A. (2018a). Network Modelling and Semantic 3D City Models: Testing the Maturity of the Utility Network ADE for CityGML with a Water Network Test Case. ISPRS Annals of Photogrammetry . Remote Sensing and Spatial Information Science, IV-4, 13–20.
[10]
Boguslawski, P., & Gold, C. (2008). Construction Operators for Modelling 3D Objects. In Plassmann, P. & Roach, P. (Eds.), 3rd Research Student Workshop (pp. 70-74), University of Glamorgan, UK.
[11]
Chaturvedi, K., & Kolbe, T. H. (2016). Integrating Dynamic Data and Sensors with Semantic 3D City Models in the context of Smart Cities. In ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, IV-2/W1, 11th 3D Geoinfo Conference (pp. 31-38).
[12]
Coors, V. (2003). 3D-GIS in networking environments. Computers, Environment and Urban Systems, 27(4), 345–357.
[13]
den Duijn, X. (2018a). A 3D data modeling approach for integrated management of below and above ground utility network features [Master’s thesis]. Delft University of Technology, Netherlands.
[14]
den Duijn, X. (2018c). Utility Network ADE test data set of sewer network in Rotterdam, Netherlands. Retrieved from https://github.com/XanderdenDuijn/CityGML-Utility-Network-ADE/tree/master/data
[15]
den Duijn, X., Agugiaro, G., & Zlatanova, S. (2018b). Modelling Below- and Above-Ground Utility Network Features with the CityGML Utility Network ADE: Experiences from Rotterdam. ISPRS Annals of Photogrammetry . Remote Sensing and Spatial Information Science, IV-4(W7), 43–50.
[16]
Egenhofer, M. J. (1995). Topological relations in 3D. Technical report. USA: University of Maine.
[17]
Ellul, C. (2007). Functionality and Performance - Two Important Considerations when Implementing Topology in 3D [Doctoral Dissertation]. University College London.
[18]
EPA. (2019). Clean Water Act. Retrieved from https://www.epa.gov/cwa-methods/methods-update-rule-2019
[19]
EPRI. (2015). Common Information Model Primer (Third ed.). Palo Alto, CA: EPRI.
[20]
ESRI. (2017a). What are geometric networks? Retrieved from http://desktop.arcgis.com/en/arcmap/latest/manage-data/geometric-networks/what-are-geometric-networks-.htm
[21]
ESRI. (2017b). What is Schematics? Retrieved from http://desktop.arcgis.com/de/arcmap/latest/extensions/schematics/what-is-schematics-.htm.
[22]
FlickS. (1996). An object-oriented framework for the realization of 3D Geographic Information Systems. In Second Joint European Conference & Exhibition on Geographical Information, Barcelona, Spain (pp. 187-196).
[23]
Frank, A. U. (1991). Properties of geographic data: Requirements for spatial access methods. In Günther, O., & Schek, H. J. (Eds.), Advances in Spatial Databases. SSD 1991 (pp. 225–234). Springer.
[24]
Gilbert, T., Barr, S., James, P., Morley, J. & Ji, Q. (2018). Software Systems Approach to Multi-Scale GIS-BIM Utility Infrastructure Network Integration and Resource Flow Simulation. ISPRS International Journal of Geo-Information, 7(8), 1-20.
[25]
Goodrich, M. T., Tamassia, R., & Goldwasser, M. H. (2014). Data Structures and Algorithms in Java. Wiley Publishing.
[26]
Gröger, G., Kolbe, T. H., Nagel, C., & Häfele, K.-H. (Eds.). (2012). OGC City Geography Markup Language (CityGML) Encoding Standard, Version 2.0.0. Open Geospatial Consortium.
[27]
Hao, T., Rogers, C. D. F., Metje, N., Chapman, D. N., Muggleton, J. M., Foo, K. Y., & Saul, A. J. et al. (2012). Condition assessment of the buried utility service infrastructure. Tunnelling and Underground Space Technology, 28, 331–344.
[28]
Hijazi, I. H., Ehlers, M., & Zlatanova, S. (2012). NIBU: A new approach to representing and analysing interior utility networks within 3D geo-information systems. International Journal of Digital Earth, 5(1), 22–42.
[29]
IBPSA. (2019). BIM/GIS and Modelica Framework for building and community energy system design and operation. Retrieved from https://ibpsa.github.io/project1/
[30]
ISO (2013). ISO 16739:2013 Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries.
[31]
JRC. (2013a). D2.8.III.6 INSPIRE Data Specification on Utility and Governmental Services – Technical Guidelines. European Commission Joint Research Centre.
[32]
JRC. (2013b). D2.10.1: INSPIRE Data Specifications – Base Models – Generic Network Model, Version 1.0rc3. European Commission Joint Research Centre.
[33]
Kofler, M., & Gruber, M. (1997). Toward a 3D GIS Database . GIM, 11(5), 55–57.
[34]
Kutzner, T. (2018). CityGML Utility Network ADE github repository. Retrieved from https://github.com/TatjanaKutzner/CityGML-UtilityNetwork-ADE/
[35]
Kutzner, T., & Kolbe, T. H. (2016). Extending Semantic 3D City Models by Supply and Disposal Networks for Analysing the Urban Supply Situation. In Kersten, T. P. (Ed.), Lösungen für eine Welt im Wandel, 36. Wissenschaftlich-Technische Jahrestagung der DGPF (Vol. 25, pp. 382-394). München: Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation (DGPF).
[36]
Mark, D. M., & Turk, A. G. (2003). Landscape Categories in Yindjibarndi Ontology, Environment, and Language. In Spatial Information Theory - Foundations of Geographic Information Science (pp. 31–49). Springer.
[37]
Montello, D., & Freundschuh, S. (2005). Cognition of Geographic Information. In McMaster, R., & Usery, E. (Eds.), A research agenda for geographic information science (pp. 61–91). CRC Press.
[38]
Ofwat. (2019). Surface water drainage. Retrieved from https://www.ofwat.gov.uk/households/your-water-bill/surfacewaterdrainage/
[39]
OGC. (2016). PipelineML. Retrieved from http://www.pipelineml.org/
[40]
OGC. (2017). Model for Underground Data Definition and Integration (MUDDI) Engineering Report.
[41]
Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering & System Safety, 121, 43–60.
[42]
RaperJ.McCarthyT.UnwinD. (1998). Multi Dimensional Virtual Reality Geographic Information System (VRGIS): Research Guidelines. In Proceedings GISRUK 98, Edinburgh, UK.
[43]
SEDRIS. (2006). SEDRIS standards. Retrieved from http://standards.sedris.org/
[44]
SIG3D. (2018). CityGML Utility Network ADE Wiki. Retrieved from https://en.wiki.utilitynetworks.sig3d.org
[45]
Sohail, M., Cavill, S., & Cotton, A. P. (2005). Sustainable Operation and Maintenance of Urban Infrastructure: Myth or reality? Journal of Urban Planning and Development, 131(1), 39–49.
[46]
Tempfli, K., & Pilouk, M. (1996). Practical Photogrammetry for 3D-GIS. ISPRS, 31(Part B4), Vienna, Austria, 859-867.
[47]
Vishnu, E., & Saran, S. (2018). Semantic Modeling of Utility Network Implementation of Use Cases for Dehradun City . The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-5, 139–145.
[48]
Widl, E., Agugiaro, G., & Puerto, P. (2018). First steps towards linking semantic 3D city modelling and multi-domain co-simulation for energy modelling at urban scale, ISPRS Annals of Photogrammetry . Remote Sensing and Spatial Information Science, IV-4, 227–234.
[49]
Yao, Z., Nagel, C., Kunde, F., Hudra, G., Willkomm, P., Donaubauer, A., & Kolbe, T. H. et al. (2018). 3DCityDB - a 3D geodatabase solution for the management, analysis, and visualization of semantic 3D city models based on CityGML. Open Geospatial Data . Software and Standards, 3(5), 1–26.
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