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Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi

Yıl 2022, Cilt: 9 Sayı: 1, 24 - 46, 01.05.2022
https://doi.org/10.9733/JGG.2022R0003.T

Öz

Teknik altyapı tesisleri, elektrik, su, doğalgaz, telekomünikasyon gibi hizmetleri ileten fiziksel nesneler ile bu nesnelerin oluşturduğu şebekeleri ifade eder. Günümüzde özellikle kentlerdeki nüfus artışı ile yer altı kullanımı yoğunlaşmakta; aynı zamanda özelleştirme süreçleriyle birlikte teknik altyapı sektöründe dağınık ve parçalı bir yapı meydana gelmektedir. Teknik altyapı tesislerine ait coğrafi veriler genellikle ilgili kuruluşlar tarafından işletme veya varlık yönetimi amacıyla çeşitli format ve yapılarda tutulmaktadır. Tesislerin planlama, inşa, bakım ve onarım süreçleri ile acil durum müdahaleleri, afet planlama ve müdahale ile akıllı kent programları gibi uygulamalar, tüm kullanıcıların güncel konumsal veriye kısa sürede erişmelerini zorunlu kılar. Bu nedenle, teknik altyapı kuruluşları, yerel yönetimler ve diğer kamu kurumları arasında coğrafi veri değişiminin etkinleştirilmesi gerekir. Birçok ulusal ve uluslararası standardizasyon kuruluşu, coğrafi veri değişimi gerektiren farklı kullanım durumlarına yönelik gereksinimlere odaklanan veri (değişim) modelleri geliştirmekte ve/veya veri değişim yöntemleri belirlemektedir. Bu çalışma, teknik altyapı tesislerine ait coğrafi verilerin paylaşım süreçlerinin iyileştirilmesine olanak veren uluslararası veri standartları ve modellerini irdelemektedir. Uluslararası veri standartları ve modellerinin içerik, kapsam, işlevsellik ve coğrafi temsil yeteneklerinin, odaklandıkları kullanım durumlarına göre farklılık gösterdiği belirlenmiş; tüm gereksinimlere yanıt verecek bir coğrafi veri modelinin bulunmadığı vurgulanmıştır.

Kaynakça

  • Al-Hader, M., Rodzi, A., Sharif, A. R., & Ahmad, N. (2009). SOA of smart city geospatial management. Proceedings of the 2009 Third UKSim European Symposium on Computer Modeling and Simulation, 6-10.
  • ASCE (2018). Standard Guideline for Recording and Exchanging Utility Infrastructure Data White Paper. https://www.asce.org/uploadedFiles/Technical_Areas/Construction_Engeering/Content_Pieces/as-built-standards-whitepaper.pdf (Erişim Tarihi: 20.05.2021).
  • Beck, A. R., Fu, G., Cohn, A. G., Bennett, B., & Stell, J. G. (2008). A framework for utility data integration in the UK. Urban and Regional Data Management, 261-276.
  • Becker, T., Nagel, C., & Kolbe, T. H. (2011). Integrated 3D modeling of multi-utility networks and their interdependencies for critical infrastructure analysis. T. Kolbe, G. König, & C. Nagel (ed), Advances in 3D geo-information sciences. Berlin, Heidelberg: Springer.
  • Becker, T., Bartels, M., Hahne, M., Hempel, L., & Lieb, R. (2012). Cascading effects and interorganisational crisis management of critical infrastructure operators. Findings of a research project. on Geo-information for Disaster Management–Best Practices, 105.
  • Becker, T., Nagel, C., & Kolbe, T. H. (2013). Semantic 3D modeling of multi-utility networks in cities for analysis and 3D visualization. Pouliot, J., Daniel, S., Hubert, F., & Zamyadi, A. (ed) Progress and New Trends in 3D Geoinformation Sciences. Berlin, Heidelberg: Springer.
  • Biljecki, F., Kumar, K., & Nagel, C. (2018). CityGML application domain extension (ADE): overview of developments. Open Geospatial Data, Software and Standards, 3(1), 1-17.
  • Boates, I., Agugiaro, G., & Nichersu, A. (2018). 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 & Spatial Information Sciences, 4(4).
  • buildingSMART (2018a), Introduction, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/link/introduction. htm (Erişim Tarihi: 10.05.2021)
  • buildingSMART (2018b), Resource definition data schemas, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/ HTML/schema/chapter-8.htm (Erişim Tarihi: 10.05.2021)
  • buildingSMART (2018c), Core data schemas, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/schema /chapter-5.htm (Erişim Tarihi: 10.05.2021)
  • buildingSMART (2018d), Shared element data schemas, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/ schema/chapter-5.htm (Erişim Tarihi: 10.05.2021)
  • CBSGM (2020). Türkiye Ulusal Coğrafi Bilgi Sistemi Altyapı Teması Veri Tanımlama Dokümanı. https://tucbs-public-api.csb.gov.tr/tucbs/tucbs_tanimlama_dokumanlari/TUCBS_AY.pdf (Erişim Tarihi: 21.05.2021)
  • Cheng, J. C., & Deng, Y. (2015). An integrated BIM-GIS framework for utility information management and analyses. Computing in Civil Engineering 2015, 667-674.
  • den Duijn, X., Agugiaro, G., & Zlatanova, S. (2018). Modelling below-and above-ground utility network features with the CityGML Utility Network ADE: Experiences from Rotterdam. Proceedings of the 3rd International Conference on Smart Data and Smart Cities, Delft, The Netherlands, 43-50.
  • Fossatti, F., Agugiaro, G., olde Scholtenhuis, L., & Dorée, A. (2020). Data modeling for operation and maintenance of utility networks: Implementation and testing. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 6(4/W1), 69-76.
  • Gale, W., & Hammerschmidt, A. (2015). Innovation in Technologies to Support the Storage, Retrieval, and Use of 3-D Utility Location Data in Highway Renewal: Transportation Research Board of the National Academies.
  • Geonovum. (2015), IMKL2015 - Dataspecificatie Utiliteitsnetten https://register.geostandaarden.nl/informatiemodel/imkl2015/1.0.0RC1/ IMKL2015_Dataspecificatie_1.0RC1.pdf (Erişim Tarihi: 20.05.2021)
  • 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), 310.
  • Hijazi, I., Ehlers, M., Zlatanova, S., & Isikdag, U. (2009). IFC to CityGML transformation framework for geo-analysis: a water utility network case. 4th International Workshop on 3D Geo-Information.
  • Hijazi, I., Ehlers, M., Zlatanova, S., Becker, T., & Berlo, L. v. (2011). Initial investigations for modeling interior Utilities within 3D Geo Context: Transforming IFC- interior utility to CityGML/UtilityNetworkADE. T. H. Kolbe, G. König, & C. Nagel (ed) Advances in 3D Geo-Information Sciences. Lecture Notes in Geoinformation and Cartography. Berlin, Heidelberg: Springer.
  • 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. INSPIRE (2013). D2.8.III.6 Data Specification on Utility and Government Services Technical Guidelines.
  • Islam, T., & Moselhi, O. (2012). Modeling geospatial interdependence for integrated municipal infrastructure. Journal of Infrastructure Systems, 18(2), 68-74.
  • Jung, Y. J. (2012). Evaluation of subsurface utility engineering for highway projects: Benefit–cost analysis. Tunnelling and underground space technology, 27(1), 111-122.
  • Kolbe, T. H. (2009). Representing and exchanging 3D city models with CityGML. T. H. Kolbe, G. König, & C. Nagel (ed) Advances in 3D Geo-Information Sciences. Lecture Notes in Geoinformation and Cartography. Berlin, Heidelberg: Springer.
  • Kutzner, T., & Kolbe, T. H. (2016). Extending semantic 3D city models by supply and disposal networks for analysing the urban supply situation. Lösungen für eine Welt im Wandel, Dreiländertagung der SGPF, DGPF und OVG, 36. Wissenschaftlich-Technische Jahrestagung der DGPF, pp. 382-394.
  • Kutzner, T., Hijazi, I., & Kolbe, T. H. (2018). Semantic modelling of 3D multi-utility networks for urban analyses and simulations: The CityGML utility network ADE. International Journal of 3-D Information Modeling (IJ3DIM), 7(2), 1-34.
  • Kutzner, T., Chaturvedi, K., & Kolbe, T. H. (2020). CityGML 3.0: New functions open up new applications. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 88(1), 43-61.
  • Lee, P. C., Wang, Y., Lo, T. P., & Long, D. (2018). An integrated system framework of building information modelling and geographical information system for utility tunnel maintenance management. Tunnelling and Underground Space Technology, 79, 263-273.
  • Lieberman, J., & Ryan, A. (2017). OGC Underground Infrastructure Concept Study Engineering Report: Open Geospatial Consortium.
  • Lieberman, J. (2019). Model for Underground Data Definition and Integration (MUDDI) Engineering Report: Open Geospatial Consortium.
  • Lieberman, J., & Roensdorf, C. (2020). Modular Approach to 3D Representation of Underground Infrastructure in the Model for Underground Data Definition and Integration (MUDDI). The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 75-81.
  • Marzouk, M., & Othman, A. (2020). Planning utility infrastructure requirements for smart cities using the integration between BIM and GIS. Sustainable Cities and Society, 57, 102120.
  • OGC (2016). P. Scarponcini (ed) OGC Land and Infrastructure Conceptual Model Standard (LandInfra).
  • OGC (2017a). P. Scarponcini (ed) OGC InfraGML 1.0: Part 0 – LandInfra Core - Encoding Standard. P.
  • OGC (2017b). P. Scarponcini (ed) OGC InfraGML 1.0: Part 2 – LandInfra Facilities and Projects – Encoding Standard. P.
  • olde Scholtenhuis, L. L., Hartmann, T., & Dorée, A. G. (2016). 4D CAD based method for supporting coordination of urban subsurface utility projects. Automation in construction, 62, 66-77.
  • olde Scholtenhuis, L. L., den Duijn, X., & Zlatanova, S. (2018). Representing geographical uncertainties of utility location data in 3D. Automation in construction, 96, 483-493.
  • Ribberink, O. (2017). Standardization of geo data exchange between network operators and contractors in underground utilities (Yüksek Lisans Tezi). Geographical Information Management and Applications (GIMA), Hollanda.
  • Rinaldi, S. M., Peerenboom, J. P., & Kelly, T. K. (2001). Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE control systems magazine, 21(6), 11-25.
  • Sterling, R. L., Anspach, J. H., Allouche, E. N., Simicevic, J., Rogers, C. D., Weston, K. E., & Hayes, K. (2009). Encouraging innovation in locating and characterizing underground utilities (No. SHRP 2 Report S2-R01-RW).
  • Talmaki, S., Kamat, V. R., & Cai, H. (2013). Geometric modeling of geospatial data for visualization-assisted excavation. Advanced Engineering Informatics, 27(2), 283-298.
  • van den Brink, L., Stoter, J., & Zlatanova, S. (2013). UML‐based approach to developing a CityGML application domain extension. Transactions in GIS, 17(6), 920-942.
  • van den Brink, L., Janssen, P., & Quak, W. (2017). IMKL2015 - Dataspecificatie Utiliteitsnetten. Geonovum. https://register.geostandaard en.nl/informatiemodel/imkl2015/1.2.1/IMKL2015_Dataspecificatie_1.2.1.pdf (Erişim Tarihi: 15.01.2021)
  • Vishnu, E., & Saran, S. (2018). SEMANTIC MODELING OF UTILITY NETWORKS IMPLEMENTATION OF USE CASES FOR DEHRADUN CITY. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, XLII-5, 139-145.
  • Wang, M., Deng, Y., Won, J., & Cheng, J. C. (2019). An integrated underground utility management and decision support based on BIM and GIS. Automation in Construction, 107, 102931.
  • Yang, Y., Ng, S. T., Xu, F. J., & Skitmore, M. (2018). Towards sustainable and resilient high density cities through better integration of infrastructure networks. Sustainable Cities and Society, 42, 407-422.
  • Yao, Z., Nagel, C., Kunde, F., Hudra, G., Willkomm, P., Donaubauer, A., Adolphi, T., & Kolbe, T. H. (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(1), 1-26.
  • Zhao, L., Liu, Z., & Mbachu, J. (2019). An integrated BIM–GIS method for planning of water distribution system. ISPRS International Journal of Geo-Information, 8(8), 331.

An analysis of international geospatial information models for urban utility networks

Yıl 2022, Cilt: 9 Sayı: 1, 24 - 46, 01.05.2022
https://doi.org/10.9733/JGG.2022R0003.T

Öz

Utility networks consist of physical constructions which transport utility service products such as power, water, gas and telecommunication. The pressure of urban population growth increases the density of urban underground areas, moreover, privatization of utilities increases decentralization and fragmentation in the utility sector. Geographic information related to utility networks are mainly held in various formats by utility organizations for operation and asset management activities. Integration and information exchange of utility data are required for numerous activities, namely design, construction and repair of utility networks, disaster planning, emergency response. The differences in data models and information systems limit the ability of integration of different utility data, as well as information exchange among relevant parties such as utility companies, local authorities and other public bodies. Several national and international standardization organizations develop data models and/or data exchange methods that focus on the needs for different use cases which require geospatial data exchange. This paper examines international data models for sharing and exchange of utility network data. It is emphasized that there is no international data model addressing the needs of all use cases, while the models’ content, scope, functionality, and geographic representation capabilities depend on the use cases they focus on.

Kaynakça

  • Al-Hader, M., Rodzi, A., Sharif, A. R., & Ahmad, N. (2009). SOA of smart city geospatial management. Proceedings of the 2009 Third UKSim European Symposium on Computer Modeling and Simulation, 6-10.
  • ASCE (2018). Standard Guideline for Recording and Exchanging Utility Infrastructure Data White Paper. https://www.asce.org/uploadedFiles/Technical_Areas/Construction_Engeering/Content_Pieces/as-built-standards-whitepaper.pdf (Erişim Tarihi: 20.05.2021).
  • Beck, A. R., Fu, G., Cohn, A. G., Bennett, B., & Stell, J. G. (2008). A framework for utility data integration in the UK. Urban and Regional Data Management, 261-276.
  • Becker, T., Nagel, C., & Kolbe, T. H. (2011). Integrated 3D modeling of multi-utility networks and their interdependencies for critical infrastructure analysis. T. Kolbe, G. König, & C. Nagel (ed), Advances in 3D geo-information sciences. Berlin, Heidelberg: Springer.
  • Becker, T., Bartels, M., Hahne, M., Hempel, L., & Lieb, R. (2012). Cascading effects and interorganisational crisis management of critical infrastructure operators. Findings of a research project. on Geo-information for Disaster Management–Best Practices, 105.
  • Becker, T., Nagel, C., & Kolbe, T. H. (2013). Semantic 3D modeling of multi-utility networks in cities for analysis and 3D visualization. Pouliot, J., Daniel, S., Hubert, F., & Zamyadi, A. (ed) Progress and New Trends in 3D Geoinformation Sciences. Berlin, Heidelberg: Springer.
  • Biljecki, F., Kumar, K., & Nagel, C. (2018). CityGML application domain extension (ADE): overview of developments. Open Geospatial Data, Software and Standards, 3(1), 1-17.
  • Boates, I., Agugiaro, G., & Nichersu, A. (2018). 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 & Spatial Information Sciences, 4(4).
  • buildingSMART (2018a), Introduction, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/link/introduction. htm (Erişim Tarihi: 10.05.2021)
  • buildingSMART (2018b), Resource definition data schemas, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/ HTML/schema/chapter-8.htm (Erişim Tarihi: 10.05.2021)
  • buildingSMART (2018c), Core data schemas, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/schema /chapter-5.htm (Erişim Tarihi: 10.05.2021)
  • buildingSMART (2018d), Shared element data schemas, https://standards.buildingsmart.org/IFC/RELEASE/IFC4/ADD2_TC1/HTML/ schema/chapter-5.htm (Erişim Tarihi: 10.05.2021)
  • CBSGM (2020). Türkiye Ulusal Coğrafi Bilgi Sistemi Altyapı Teması Veri Tanımlama Dokümanı. https://tucbs-public-api.csb.gov.tr/tucbs/tucbs_tanimlama_dokumanlari/TUCBS_AY.pdf (Erişim Tarihi: 21.05.2021)
  • Cheng, J. C., & Deng, Y. (2015). An integrated BIM-GIS framework for utility information management and analyses. Computing in Civil Engineering 2015, 667-674.
  • den Duijn, X., Agugiaro, G., & Zlatanova, S. (2018). Modelling below-and above-ground utility network features with the CityGML Utility Network ADE: Experiences from Rotterdam. Proceedings of the 3rd International Conference on Smart Data and Smart Cities, Delft, The Netherlands, 43-50.
  • Fossatti, F., Agugiaro, G., olde Scholtenhuis, L., & Dorée, A. (2020). Data modeling for operation and maintenance of utility networks: Implementation and testing. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 6(4/W1), 69-76.
  • Gale, W., & Hammerschmidt, A. (2015). Innovation in Technologies to Support the Storage, Retrieval, and Use of 3-D Utility Location Data in Highway Renewal: Transportation Research Board of the National Academies.
  • Geonovum. (2015), IMKL2015 - Dataspecificatie Utiliteitsnetten https://register.geostandaarden.nl/informatiemodel/imkl2015/1.0.0RC1/ IMKL2015_Dataspecificatie_1.0RC1.pdf (Erişim Tarihi: 20.05.2021)
  • 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), 310.
  • Hijazi, I., Ehlers, M., Zlatanova, S., & Isikdag, U. (2009). IFC to CityGML transformation framework for geo-analysis: a water utility network case. 4th International Workshop on 3D Geo-Information.
  • Hijazi, I., Ehlers, M., Zlatanova, S., Becker, T., & Berlo, L. v. (2011). Initial investigations for modeling interior Utilities within 3D Geo Context: Transforming IFC- interior utility to CityGML/UtilityNetworkADE. T. H. Kolbe, G. König, & C. Nagel (ed) Advances in 3D Geo-Information Sciences. Lecture Notes in Geoinformation and Cartography. Berlin, Heidelberg: Springer.
  • 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. INSPIRE (2013). D2.8.III.6 Data Specification on Utility and Government Services Technical Guidelines.
  • Islam, T., & Moselhi, O. (2012). Modeling geospatial interdependence for integrated municipal infrastructure. Journal of Infrastructure Systems, 18(2), 68-74.
  • Jung, Y. J. (2012). Evaluation of subsurface utility engineering for highway projects: Benefit–cost analysis. Tunnelling and underground space technology, 27(1), 111-122.
  • Kolbe, T. H. (2009). Representing and exchanging 3D city models with CityGML. T. H. Kolbe, G. König, & C. Nagel (ed) Advances in 3D Geo-Information Sciences. Lecture Notes in Geoinformation and Cartography. Berlin, Heidelberg: Springer.
  • Kutzner, T., & Kolbe, T. H. (2016). Extending semantic 3D city models by supply and disposal networks for analysing the urban supply situation. Lösungen für eine Welt im Wandel, Dreiländertagung der SGPF, DGPF und OVG, 36. Wissenschaftlich-Technische Jahrestagung der DGPF, pp. 382-394.
  • Kutzner, T., Hijazi, I., & Kolbe, T. H. (2018). Semantic modelling of 3D multi-utility networks for urban analyses and simulations: The CityGML utility network ADE. International Journal of 3-D Information Modeling (IJ3DIM), 7(2), 1-34.
  • Kutzner, T., Chaturvedi, K., & Kolbe, T. H. (2020). CityGML 3.0: New functions open up new applications. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 88(1), 43-61.
  • Lee, P. C., Wang, Y., Lo, T. P., & Long, D. (2018). An integrated system framework of building information modelling and geographical information system for utility tunnel maintenance management. Tunnelling and Underground Space Technology, 79, 263-273.
  • Lieberman, J., & Ryan, A. (2017). OGC Underground Infrastructure Concept Study Engineering Report: Open Geospatial Consortium.
  • Lieberman, J. (2019). Model for Underground Data Definition and Integration (MUDDI) Engineering Report: Open Geospatial Consortium.
  • Lieberman, J., & Roensdorf, C. (2020). Modular Approach to 3D Representation of Underground Infrastructure in the Model for Underground Data Definition and Integration (MUDDI). The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 44, 75-81.
  • Marzouk, M., & Othman, A. (2020). Planning utility infrastructure requirements for smart cities using the integration between BIM and GIS. Sustainable Cities and Society, 57, 102120.
  • OGC (2016). P. Scarponcini (ed) OGC Land and Infrastructure Conceptual Model Standard (LandInfra).
  • OGC (2017a). P. Scarponcini (ed) OGC InfraGML 1.0: Part 0 – LandInfra Core - Encoding Standard. P.
  • OGC (2017b). P. Scarponcini (ed) OGC InfraGML 1.0: Part 2 – LandInfra Facilities and Projects – Encoding Standard. P.
  • olde Scholtenhuis, L. L., Hartmann, T., & Dorée, A. G. (2016). 4D CAD based method for supporting coordination of urban subsurface utility projects. Automation in construction, 62, 66-77.
  • olde Scholtenhuis, L. L., den Duijn, X., & Zlatanova, S. (2018). Representing geographical uncertainties of utility location data in 3D. Automation in construction, 96, 483-493.
  • Ribberink, O. (2017). Standardization of geo data exchange between network operators and contractors in underground utilities (Yüksek Lisans Tezi). Geographical Information Management and Applications (GIMA), Hollanda.
  • Rinaldi, S. M., Peerenboom, J. P., & Kelly, T. K. (2001). Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE control systems magazine, 21(6), 11-25.
  • Sterling, R. L., Anspach, J. H., Allouche, E. N., Simicevic, J., Rogers, C. D., Weston, K. E., & Hayes, K. (2009). Encouraging innovation in locating and characterizing underground utilities (No. SHRP 2 Report S2-R01-RW).
  • Talmaki, S., Kamat, V. R., & Cai, H. (2013). Geometric modeling of geospatial data for visualization-assisted excavation. Advanced Engineering Informatics, 27(2), 283-298.
  • van den Brink, L., Stoter, J., & Zlatanova, S. (2013). UML‐based approach to developing a CityGML application domain extension. Transactions in GIS, 17(6), 920-942.
  • van den Brink, L., Janssen, P., & Quak, W. (2017). IMKL2015 - Dataspecificatie Utiliteitsnetten. Geonovum. https://register.geostandaard en.nl/informatiemodel/imkl2015/1.2.1/IMKL2015_Dataspecificatie_1.2.1.pdf (Erişim Tarihi: 15.01.2021)
  • Vishnu, E., & Saran, S. (2018). SEMANTIC MODELING OF UTILITY NETWORKS IMPLEMENTATION OF USE CASES FOR DEHRADUN CITY. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, XLII-5, 139-145.
  • Wang, M., Deng, Y., Won, J., & Cheng, J. C. (2019). An integrated underground utility management and decision support based on BIM and GIS. Automation in Construction, 107, 102931.
  • Yang, Y., Ng, S. T., Xu, F. J., & Skitmore, M. (2018). Towards sustainable and resilient high density cities through better integration of infrastructure networks. Sustainable Cities and Society, 42, 407-422.
  • Yao, Z., Nagel, C., Kunde, F., Hudra, G., Willkomm, P., Donaubauer, A., Adolphi, T., & Kolbe, T. H. (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(1), 1-26.
  • Zhao, L., Liu, Z., & Mbachu, J. (2019). An integrated BIM–GIS method for planning of water distribution system. ISPRS International Journal of Geo-Information, 8(8), 331.
Toplam 49 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Azer İlgar 0000-0003-0624-4623

Volkan Çağdaş 0000-0002-5200-0075

Yayımlanma Tarihi 1 Mayıs 2022
Gönderilme Tarihi 24 Mayıs 2021
Yayımlandığı Sayı Yıl 2022 Cilt: 9 Sayı: 1

Kaynak Göster

APA İlgar, A., & Çağdaş, V. (2022). Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi. Jeodezi Ve Jeoinformasyon Dergisi, 9(1), 24-46. https://doi.org/10.9733/JGG.2022R0003.T
AMA İlgar A, Çağdaş V. Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi. hkmojjd. Mayıs 2022;9(1):24-46. doi:10.9733/JGG.2022R0003.T
Chicago İlgar, Azer, ve Volkan Çağdaş. “Kentsel Teknik Altyapı Tesislerine yönelik Uluslararası coğrafi Veri Modellerinin Analizi”. Jeodezi Ve Jeoinformasyon Dergisi 9, sy. 1 (Mayıs 2022): 24-46. https://doi.org/10.9733/JGG.2022R0003.T.
EndNote İlgar A, Çağdaş V (01 Mayıs 2022) Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi. Jeodezi ve Jeoinformasyon Dergisi 9 1 24–46.
IEEE A. İlgar ve V. Çağdaş, “Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi”, hkmojjd, c. 9, sy. 1, ss. 24–46, 2022, doi: 10.9733/JGG.2022R0003.T.
ISNAD İlgar, Azer - Çağdaş, Volkan. “Kentsel Teknik Altyapı Tesislerine yönelik Uluslararası coğrafi Veri Modellerinin Analizi”. Jeodezi ve Jeoinformasyon Dergisi 9/1 (Mayıs 2022), 24-46. https://doi.org/10.9733/JGG.2022R0003.T.
JAMA İlgar A, Çağdaş V. Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi. hkmojjd. 2022;9:24–46.
MLA İlgar, Azer ve Volkan Çağdaş. “Kentsel Teknik Altyapı Tesislerine yönelik Uluslararası coğrafi Veri Modellerinin Analizi”. Jeodezi Ve Jeoinformasyon Dergisi, c. 9, sy. 1, 2022, ss. 24-46, doi:10.9733/JGG.2022R0003.T.
Vancouver İlgar A, Çağdaş V. Kentsel teknik altyapı tesislerine yönelik uluslararası coğrafi veri modellerinin analizi. hkmojjd. 2022;9(1):24-46.