The uptake of urban digital twins in the built environment: a pathway to resilient and sustainable cities

Abstract

Urban Digital Twin (UDT) technology is increasingly recognised as a promising tool for designing and developing sustainable, resilient urban environments. Nonetheless, the current literature lacks a comprehensive understanding of UDTs’ current applications in the built environment. Therefore, this study addresses the identified gap by analysing scholarly literature and industry reports connected to UDT implementations. The results of scientometric analysis revealed five key research fields including: (i) UDT for urban monitoring and controlling, (ii) UDT for smart urban planning, (iii) UDT for environmental management, (iv) UDT for decision-making, and (v) UDT for smart and sustainable cities. Further, this study analysed 10 industry reports on UDT technology to identify practical insights and evaluate industry-driven approaches for implementing UDT solutions in urban environments. Despite promising progress, the findings indicate the absence of a clear, structured process to facilitate consistent implementation, scalability, and interoperability in UDT technology. This further highlights the need for globally recognised guidelines and well-defined KPIs to fully realise its potential in urban environments. The study also presents a new classification model developed from analysing the research flow to elaborate on the main outcomes from five clusters towards UDT pathways. The new proposed model reintroduces the structure of UDT literature with a new flow to interpret and correlate the content identified in previous studies. Based on these insights, the study offers recommendations to support the advancement of UDT technology for building resilient, sustainable cities.

Keywords

Digital twin / Smart cities / Urban planning / Sustainability / Industry 4.0 / Built environment

References

[1] AbdeenFN, ShirowzhanS, SepasgozarSM. Citizen-centric digital twin development with machine learning and interfaces for maintaining urban infrastructure. Telematics and Informatics, 2023, 84: 102032.

[2] AdreaniL, BelliniP, FanfaniM, NesiP, PantaleoG. Smart city digital twin framework for real-time multi-data integration and wide public distribution. IEEE Access, 2024, 12: 76277-76303.

[3] AlvaP, Mosteiro-RomeroM, MillerC, StouffsR. Mitigating operational greenhouse gas emissions in ageing residential buildings using an Urban Digital Twin dashboard. Energy and Buildings, 2024, 322. 114681

[4] Anschütz, C., Ebner, K., & Smolnik, S. (2022). Free ride in rush-hour traffic–designing gamified smart mobility systems for sustainable use. ICIS 2022 Proceedings. 6. Available on https://aisel.aisnet.org/icis2022/user_behaivor/user_behaivor/6. Accessed 28 Jan 2025.

[5] AnschützC, EbnerK, SmolnikS. Size does matter: A maturity model for the special needs of small and medium-sized smart cities. Cities, 2024, 150. 104998

[6] Anthopoulos, L., Janssen, M., & Weerakkody, V. (2019). A Unified Smart City Model (USCM) for smart city conceptualization and benchmarking. In Smart cities and smart spaces: Concepts, methodologies, tools, and applications (pp. 247–264).

[7] ANZLIC. (2019). Principles for spatially enabled digital twins of the built and natural environment in Australia. Retrieved 24/09/2024, from https://www.anzlic.gov.au/sites/default/files/files/principles_for_spatially_enabled_digital_twins_of_the_built_and_natural_.pdf

[8] Argyroudis, S. A., Mitoulis, S. A., Chatzi, E., Baker, J. W., Brilakis, I., Gkoumas, K., ... & Linkov, I. (2022). Digital technologies can enhance climate resilience of critical infrastructure. Climate Risk Management, 35, 100387.

[9] ARUP. (2019). Digital twin: Towards a meaningful framework. Retrieved 24/09/2024, from https://www.arup.com/globalassets/downloads/insights/digital-twin-towards-a-meaningful-framework.pdf

[10] AustinM, DelgoshaeiP, CoelhoM, HeidarinejadM. Architecting smart city digital twins: Combined semantic model and machine learning approach. Journal of Management in Engineering, 2020, 36404020026.

[11] BeilC, RuhdorferR, CoduroT, KolbeTH. Detailed streetspace modelling for multiple applications: Discussions on the proposed CityGML 3.0 transportation model. ISPRS International Journal of Geo-Information, 2020, 910603.

[12] Bibri, S. E., Huang, J., Jagatheesaperumal, S. K., & Krogstie, J. (2024). The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities: A comprehensive systematic review. Environmental Science and Ecotechnology, 20, 100433.

[13] BrooDG, Bravo-HaroM, SchoolingJ. Design and implementation of a smart infrastructure digital twin. Automation in Construction, 2022, 136: 104171.

[14] CaoW, ZhouL. Resilient microgrid modeling in digital twin considering demand response and landscape design of renewable energy. Sustainable Energy Technologies and Assessments, 2024, 64. 103628

[15] Capgemini Research Institute. (2022). Digital twins: Adding intelligence to the real world. Retrieved 24/09/2024, from https://www.capgemini.com/gb-en/wp-content/uploads/sites/5/2022/11/DigitalTwins_adding-intelligence-to-the-real-world.pdf

[16] CaprariG, CastelliG, MontuoriM, CamardelliM, MalvezziR. Digital twin for urban planning in the green deal era: A state of the art and future perspectives. Sustainability, 2022, 1410. 6263

[17] ChenL, LiX, ZhuJ. Carbon peak control for achieving net-zero renewable-based smart cities: Digital twin modeling and simulation. Sustainable Energy Technologies and Assessments, 2024, 65. 103792

[18] ChenM, ChenL, LiY, XianY. Developing computable sustainable urbanization science: Interdisciplinary perspective. Computational Urban Science, 2022, 2117.

[19] CuretonP, HartleyE. City information models (CIMs) as precursors for urban digital twins (UDTs): A case study of lancaster. Frontiers in Built Environment, 2023, 9: 1048510.

[20] DaniAAH, SupangkatSH, LubisFF, NugrahaIGBB, KinandaR, RizkiaI. Development of a smart city platform based on digital twin technology for monitoring and supporting decision-making. Sustainability, 2023, 151814002.

[21] DembskiF, WössnerU, LetzgusM, RuddatM, YamuC. Urban digital twins for smart cities and citizens: The case study of Herrenberg, Germany. Sustainability, 2020, 126. 2307

[22] Deng, M., Menassa, C. C., & Kamat, V. R. (2021a). From BIM to digital twins: A systematic review of the evolution of intelligent building representations in the AEC-FM industry. Journal of Information Technology in Construction, 26, 58–83.

[23] DengT, ZhangK, ShenZJM. A systematic review of a digital twin city: A new pattern of urban governance toward smart cities. Journal of Management Science and Engineering, 2021, 62125-134.

[24] Diaz-SarachagaJM. Developing an assessment governance framework for urban digital twins: Insights from smart cities. Cities, 2025, 156: 105558.

[25] DingC, HoIWH. Digital-twin-enabled city-model-aware deep learning for dynamic channel estimation in urban vehicular environments. IEEE Transactions on Green Communications and Networking, 2022, 631604-1612.

[26] DittmannS, MathieuMP, ZhangP, GloddeA, DietrichF. Device recognition assistants as additional data management method for digital twins. CIRP Journal of Manufacturing Science and Technology, 2024, 51: 73-90.

[27] EL Azzaoui, A., Kim, T. W., Loia, V., Park, J. H. (2021). Blockchain-based secure digital twin framework for smart healthy city. In Advanced multimedia and ubiquitous engineering: MUE-FutureTech 2020 (pp. 107–113). Springer.

[28] Esri UK. (2024). https://www.esriuk.com/en-gb/digital-twin/overview?gad_source=1&gclid=EAIaIQobChMIx77aqJaPiwMVPZdQBh05CBFjEAAYAiAAEgI0cfD_BwE#the-university-of-warwick. Accessed 26 Jan 2025.

[29] Ferré-BigorraJ, CasalsM, GangolellsM. The adoption of urban digital twins. Cities, 2022, 131. 103905

[30] FordDN, WolfCM. Smart cities with digital twin systems for disaster management. Journal of Management in Engineering, 2020, 36404020027.

[31] FranciscoA, MohammadiN, TaylorJE. Smart city digital twin–enabled energy management: Toward real-time urban building energy benchmarking. Journal of Management in Engineering, 2020, 36204019045.

[32] FullerA, FanZ, DayC, BarlowC. Digital twin: Enabling technologies, challenges and open research. IEEE Access, 2020, 8: 108952-108971.

[33] GholamiM, TorreggianiD, TassinariP, BarbaresiA. Developing a 3D city digital twin: Enhancing walkability through a green pedestrian network (GPN) in the city of Imola, Italy. Land, 2022, 11111917.

[34] Grieves, M., & Vickers J. (2017). Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. In Transdisciplinary perspectives on complex systems: New findings and approaches (pp. 85–113).

[35] Griffith, C., & Truelove, M. (2021). Framework for spatially enabled digital twins: Information paper. Retrieved 24/09/2024, from https://www.anzlic.gov.au/sites/default/files/files/Data61%20Digital%20Twin%20Framework%20Information%20Paper%20-%20February%202021.pdf

[36] HamY, KimJ. Participatory sensing and digital twin city: Updating virtual city models for enhanced risk-informed decision-making. Journal of Management in Engineering, 2020, 36304020005.

[37] HämäläinenM. Urban development with dynamic digital twins in Helsinki city. IET Smart Cities, 2021, 34201-210.

[38] HaraguchiM, FunahashiT, BiljeckiF. Assessing governance implications of city digital twin technology: A maturity model approach. Technological Forecasting and Social Change, 2024, 204. 123409

[39] Henriksen, H. J., Schneider, R., Koch, J., Ondracek, M., Troldborg, L., Seidenfaden, I. K., ... & Stisen, S. (2022). A new digital twin for climate change adaptation, water management, and disaster risk reduction (HIP digital twin). Water,15(1), 25.

[40] IammarinoS, Rodriguez-PoseA, StorperM. Regional inequality in Europe: Evidence, theory and policy implications. Journal of Economic Geography, 2019, 192273-298.

[41] IBM. (2021). What is a digital twin?. https://www.ibm.com/think/topics/what-is-a-digital-twin. Accessed 25 Jan 2025.

[42] IEC. (2021). Technical report: City information modelling and urban digital twins. Retrieved 24/09/2024, from https://www.iec.ch/system/files/2024-04/iec_tec_cim_udt_en.pdf

[43] Industry, A. (2021). Designing disruption: The critical role of virtual twins in accelerating sustainability. Retrieved 24/09/2024, from https://www.accenture.com/content/dam/accenture/final/a-com-migration/r3-3/pdf/pdf-147/accenture-virtual-twin-and-sustainability.pdf

[44] JavaidM, HaleemA, SumanR. Digital twin applications toward industry 4.0: A review. Cognitive Robotics, 2023, 3: 71-92.

[45] JiangF, MaL, BroydT, ChenW, LuoH. Digital twin enabled sustainable urban road planning. Sustainable Cities and Society, 2022, 78. 103645

[46] KhokhlovAN. How scientometrics became the most important science for researchers of all specialties. Moscow University Biological Sciences Bulletin, 2020, 75: 159-163.

[47] KumarD, BassillNP. Analysing trends of computational urban science and data science approaches for sustainable development. Computational Urban Science, 2024, 411-27.

[48] KumarSA, MadhumathiR, ChelliahPR, TaoL, WangS. A novel digital twin-centric approach for driver intention prediction and traffic congestion avoidance. Journal of Reliable Intelligent Environments, 2018, 44199-209.

[49] KuruK. Metaomnicity: Toward immersive urban metaverse cyberspaces using smart city digital twins. IEEE Access, 2023, 11: 43844-43868.

[50] KwonJW, YunSJ, KimWT. A semantic data-based distributed computing framework to accelerate digital twin services for large-scale disasters. Sensors, 2022, 22186749.

[51] LehtolaVV, KoevaM, ElberinkSO, RaposoP, VirtanenJP, VahdatikhakiF, BorsciS. Digital twin of a city: Review of technology serving city needs. International Journal of Applied Earth Observation and Geoinformation, 2022, 114: 102915.

[52] LeiB, JanssenP, StoterJ, BiljeckiF. Challenges of urban digital twins: A systematic review and a Delphi expert survey. Automation in Construction, 2023, 147. 104716

[53] LiB, TanW. A novel framework for integrating solar renewable source into smart cities through digital twin simulations. Solar Energy, 2023, 262. 111869

[54] LiX, LiuH, WangW, ZhengY, LvH, LvZ. Big data analysis of the internet of things in the digital twins of smart city based on deep learning. Future Generation Computer Systems, 2022, 128: 167-177.

[55] Li, X., Luo, J., Li, Y., Wang, W., Hong, W., Liu, M., ... & Lv, Z. (2022b). Application of effective water-energy management based on digital twins technology in sustainable cities construction. Sustainable Cities and Society, 87, 104241.

[56] Li, Y., den Hartog, H., Liu, T., & Cheng, Y. (2020). Research progress in thermal comfort assessment of urban green spaces based on scientific knowledge mapping technology. In 2020 International Conference on Innovation Design and Digital Technology (ICIDDT) (pp. 306–311). IEEE.

[57] LiuM, MaH, BaiY. Understanding the drivers of land surface temperature based on multisource data: A spatial econometric perspective. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 12263-12272.

[58] LiuM, ZhangK. Smart city landscape design for achieving net-zero emissions: Digital twin modeling. Sustainable Energy Technologies and Assessments, 2024, 63: 103659.

[59] LiuP, ZhaoT, LuoJ, LeiB, FreiM, MillerC, BiljeckiF. Towards human-centric digital twins: Leveraging computer vision and graph models to predict outdoor comfort. Sustainable Cities and Society, 2023, 93. 104480

[60] LiuZ, ZhuZ, SunZ, LiA, NiS. A digital twin-based green construction management method for prefabricated buildings. Digital Twin, 2023, 3: 8.

[61] LuoJ, LiuP, CaoL. Coupling a physical replica with a digital twin: A comparison of participatory decision-making methods in an urban park environment. ISPRS International Journal of Geo-Information, 2022, 118. 452

[62] LuoW, SandanayakeM, HouL, TanY, ZhangG. A systematic review of green construction research using scientometrics methods. Journal of Cleaner Production, 2022, 366. 132710

[63] Macatulad, E. & Biljecki, F. (2024). Continuing from the Sendai framework midterm: Opportunities for urban digital twins in disaster risk management. International Journal of Disaster Risk Reduction, 102, 104310.

[64] MasoumiH, ShirowzhanS, EskandarpourP, PettitCJ. City digital twins: Their maturity level and differentiation from 3D city models. Big Earth Data, 2023, 711-36.

[65] MeerowS. The politics of multifunctional green infrastructure planning in New York City. Cities, 2020, 100. 102621

[66] MerloA, LavorattiG. Documenting urban morphology: From 2d representations to metaverse. Land, 2024, 132. 136

[67] Mohamad ZaidiNH, LimCH, RazaliH. Mitigating the energy consumption and carbon emissions of a residential area in a tropical city using digital twin technology: A Case study of Bertam, Penang. Buildings, 2024, 143638.

[68] MorenoC, AllamZ, ChabaudD, GallC, PratlongF. Introducing the “15-minute city”: Sustainability, resilience and place identity in future post-pandemic cities. Smart Cities, 2021, 4193-111.

[69] MouratidisK. Time to challenge the 15-minute city: Seven pitfalls for sustainability, equity, livability, and spatial analysis. Cities, 2024, 153. 105274

[70] Nazim, I., & Joyce, S. C. (2024). Urban analytics and generative deep learning for context responsive design in digital twins. In Proceedings of the 29th International Conference of the Association for Computer Aided Architectural Design Research in Asia (CAADRIA) 2024, Association for Computer-Aided Architectural Design Research in Asia (CAADRIA), Hong Kong, vol. 2 (pp. 495–504).

[71] NochtaT, WanL, SchoolingJM, ParlikadAK. A socio-technical perspective on urban analytics: The case of city-scale digital twins. Journal of Urban Technology, 2021, 281–2263-287.

[72] Ohueri, C. C., Masrom, M. A. N., Habil, H., & Ambashe, M. S. (2023). IoT-based digital twin best practices for reducing operational carbon in building retrofitting: a mixed-method approach. Engineering, Construction and Architectural Management, 32(3), 2044–2065.

[73] Omrany, H., & Al-Obaidi, K. M. (2024). Application of digital twin technology for Urban Heat Island mitigation: Review and conceptual framework. Smart and Sustainable Built Environment IN PRESS. https://doi.org/10.1108/SASBE-05-2024-0189

[74] Omrany, H., Al-Obaidi, K. M., Ghaffarianhoseini, A., Chang, R. D., Park, C., & Rahimian, F. (2025). Digital twin technology for education, training and learning in construction industry: implications for research and practice. Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-10-2024-1376

[75] OmranyH, Al-ObaidiKM, HossainM, AlduaisNA, Al-DuaisHS, GhaffarianhoseiniA. IoT-enabled smart cities: A hybrid systematic analysis of key research areas, challenges, and recommendations for future direction. Discover Cities, 2024, 112.

[76] OmranyH, Al-ObaidiKM, HusainA, GhaffarianhoseiniA. Digital twins in the construction industry: A comprehensive review of current implementations, enabling technologies, and future directions. Sustainability, 2023, 1514. 10908

[77] OmranyH, ChangR, SoebartoV, ZhangY, GhaffarianhoseiniA, ZuoJ. A bibliometric review of net zero energy building research 1995–2022. Energy and Buildings, 2022, 262. 111996

[78] OmranyH, MehdipourA, OtengD. Digital twin technology and social sustainability: Implications for the construction industry. Sustainability, 2024, 1619. 8663

[79] PapyshevG, YarimeM. Exploring city digital twins as policy tools: A task-based approach to generating synthetic data on urban mobility. Data & Policy, 2021, 3. e16

[80] ParkJ, YangB. GIS-enabled digital twin system for sustainable evaluation of carbon emissions: A case study of Jeonju city, south Korea. Sustainability, 2020, 1221. 9186

[81] PatelT, GuoBH, ZouY. A scientometric review of construction progress monitoring studies. Engineering, Construction and Architectural Management, 2022, 2993237-3266.

[82] PatelUR, GhaffarianhoseiniA, GhaffarianhoseiniA, BurgessA. Digital twin technology for sustainable urban development: A review of its potential impact on SDG 11 in New Zealand. Cities, 2024, 155. 105484

[83] PeldonD, BanihashemiS, LeNguyenK, DerribleS. Navigating urban complexity: The transformative role of digital twins in smart city development. Sustainable Cities and Society, 2024, 111. 105583

[84] Price Waterhouse Coopers. (2022). How digital twins can make smart cities better. Retrieved 24/09/2024, from https://www.pwc.com/m1/en/publications/documents/how-digital-twins-can-make-smart-cities-better.pdf

[85] Quek, H. Y., Sielker, F., Akroyd, J., Bhave, A. N., von Richthofen, A., Herthogs, P., ... & Kraft, M. (2023). The conundrum in smart city governance: Interoperability and compatibility in an ever-growing ecosystem of digital twins. Data and Policy, 5, e6.

[86] RaesL, MichielsP, AdolphiT, TampereC, DalianisA, McAleerS, KogutP. DUET: A framework for building interoperable and trusted digital twins of smart cities. IEEE Internet Computing, 2021, 26343-50.

[87] Ramani, V., Ignatius, M., Lim, J., Biljecki F., & Miller, C. (2023). A dynamic urban digital twin integrating longitudinal thermal imagery for microclimate studies. In Proceedings of the 10th ACM international conference on systems for energy-efficient buildings, cities, and transportation (pp. 421–428).

[88] RoudbariNS, PunekarSR, PattersonZ, EickerU, PoullisC. From data to action in flood forecasting leveraging graph neural networks and digital twin visualization. Scientific Reports, 2024, 14118571.

[89] SaeedZO, ManciniF, GlusacT, IzadpanahiP. Artificial intelligence and optimization methods in construction industry. Buildings, 2022, 12: 685.

[90] ScalasA, CabidduD, MortaraM, SpagnuoloM. Potential of the geometric layer in urban digital twins. ISPRS International Journal of Geo-Information, 2022, 116. 343

[91] SchrotterG, HürzelerC. The digital twin of the city of Zurich for urban planning. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2020, 88199-112.

[92] Scopus. (2024). Scopus: Comprehensive, multidisciplinary, trusted abstract and citation database. Retrieved 24/09/2024, from https://www.elsevier.com/products/scopus

[93] SepasgozarSM. Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sustainable built environment. Buildings, 2021, 114151.

[94] ShahatE, HyunCT, YeomC. City digital twin potentials: A review and research agenda. Sustainability, 2021, 136. 3386

[95] Shan, S., Song, Y., Wang, C., & Ji, W. (2024). Influencing factors and action paths for public crisis governance performance improvement in digital twin cities. Library Hi Tech, ahead of print.

[96] SomanathS, NaserentinV, EleftheriouO, SjölieD, WästbergBS, LoggA. Towards urban digital twins: A workflow for procedural visualization using geospatial data. Remote Sensing, 2024, 1611. 1939

[97] Tancev, G., & Toro, F. G. (2022). Towards a digital twin for air quality monitoring networks in smart cities. In 2022 IEEE International Smart Cities Conference (ISC2) (pp. 1–4). IEEE

[98] TeixeiraJF, SilvaC, SeisenbergerS, BüttnerB, McCormickB, PapaE, CaoM. Classifying 15-minute cities: A review of worldwide practices. Transportation Research Part A: Policy and Practice, 2024, 189: 104234

[99] TheriasA, RafieeA. City digital twins for urban resilience. International Journal of Digital Earth, 2023, 1624164-4190.

[100] TrevisaniS, OmodeoPD. Earth scientists and sustainable development: Geocomputing, new technologies, and the humanities. Land, 2021, 103294.

[101] TuhaiseVV, TahJHM, AbandaFH. Technologies for digital twin applications in construction. Automation in Construction, 2023, 152. 104931

[102] UN-Habitat. (2022). Envisaging the future of cities, world city report 2022. from https://unhabitat.org/sites/default/files/2022/06/wcr_2022.pdf

[103] Van Eck, N. J., & Waltman, L. (2023). VOSviewer manual. In Manual for VOSviewer version 1.6.20. Available on: https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.20.pdf. Accessed 6/01/2025.

[104] VanDerHornE, MahadevanS. Digital twin: Generalization, characterization and implementation. Decision Support Systems, 2021, 145. 113524

[105] WajidMS, Terashima-MarinH, NajafiradP, PablosSEC, WajidMA. DTwin-TEC: An AI-based TEC district digital twin and emulating security events by leveraging knowledge graph. Journal of Open Innovation: Technology, Market, and Complexity, 2024, 102. 100297

[106] Walker, A. (2023). Singapore’s digital twin—from science fiction to Hi-Tech reality. In Infrastructure Global. Available on: https://infra.global/singapores-digital-twin-from-science-fiction-to-hi-tech-reality/. Accessed 4 Jan 2025.

[107] WangH, ChenX, JiaF, ChengX. Digital twin-supported smart city: Status, challenges and future research directions. Expert Systems with Applications, 2023, 217. 119531

[108] WangH, WangY. Smart cities net zero planning considering renewable energy landscape design in digital twin. Sustainable Energy Technologies and Assessments, 2024, 63. 103629

[109] WangX, PanY, ChenJ. Digital twin with data-mechanism-fused model for smart excavation management. Automation in Construction, 2024, 168. 105749

[110] WeckS, BeißwengerS. Coping with peripheralization: Governance response in two German small cities. European Planning Studies, 2014, 22102156-2171.

[111] WeilC, BibriSE, LongchampR, GolayF, AlahiA. A systemic review of urban digital twin challenges, and perspectives for sustainable smart cities. Sustainable Cities and Society, 2023, 99. 104862

[112] WhiteG, ZinkA, CodecáL, ClarkeS. A digital twin smart city for citizen feedback. Cities, 2021, 110. 103064

[113] World Bank Group. (2022). Smart cities in the Republic of Korea. Retrieved 24/09/2024, from https://documents1.worldbank.org/curated/en/099501509212220541/pdf/IDU09bc4586900d9a047080a9de0afa91af324a9.pdf

[114] World Economic Forum. (2022). Digital twin cities: Framework and global practices. Retrieved 24/09/2024, from https://www3.weforum.org/docs/WEF_Global_Digital_Twin_Cities_Framework_and_Practice_2022.pdf

[115] World Economic Forum. (2023). Digital twin cities: Key insights and recommendations. Retrieved 24/09/2024, from https://www3.weforum.org/docs/WEF_Digital_Twin_Cities_2023.pdf

[116] Wu, T. G., & Guan, C. (2024). Advancing intra and inter-city urban digital twins: An updated review. Journal of Planning Education and Research, 0739456X241260887.

[117] WuY, ZhangK, ZhangY. Digital twin networks: A survey. IEEE Internet of Things Journal, 2021, 81813789-13804.

[118] XiaH, LiuZ, EfremochkinaM, LiuX, LinC. Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration. Sustainable Cities and Society, 2022, 84. 104009

[119] XuW, LiuS. Novel economic models for advancing urban energy management and transition: Simulation of urban energy system in digital twin. Sustainable Cities and Society, 2024, 101. 105154

[120] Ye, X., Du, J., Han, Y., Newman, G., Retchless, D., Zou, L., ... , & Cai Z. (2023). Developing human-centered urban digital twins for community infrastructure resilience: A research agenda. Journal of Planning Literature, 38(2), 187–199.

[121] YevuSK, OwusuEK, ChanAP, SepasgozarSM, KamatVR. Digital twin-enabled prefabrication supply chain for smart construction and carbon emissions evaluation in building projects. Journal of Building Engineering, 2023, 78: 107598.

[122] Yossef RavidB, Aharon-GutmanM. The social digital twin: The social turn in the field of smart cities. Environment and Planning b: Urban Analytics and City Science, 2023, 5061455-1470

[123] ZhangG, ChengS, GaoY. A visibility-based approach to manage the vertical urban development and maintain visual sustainability of urban mountain landscapes: A case of Mufu Mountain in Nanjing, China. Environment and Planning B: Urban Analytics and City Science, 2024, 512384-400

[124] ZhangH, FengX. Reliability improvement and landscape planning for renewable energy integration in smart cities: A case study by digital twin. Sustainable Energy Technologies and Assessments, 2024, 64. 103714

[125] ZhangM, TaoF, HuangB, LiuA, WangL, AnwerN, NeeAYC. Digital twin data: Methods and key technologies. Digital Twin, 2022, 1: 2.

[126] ZhaoX, ZhangY. Integrated management of urban resources toward net-zero smart cities considering renewable energies uncertainty and modeling in digital twin. Sustainable Energy Technologies and Assessments, 2024, 64. 103656

[127] ZhongB, WuH, LiH, SepasgozarS, LuoH, HeL. A scientometric analysis and critical review of construction related ontology research. Automation in Construction, 2019, 101: 17-31.

Funding

University of Adelaide

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