Sabri, Soheil

Witte, Patrick

Utrecht University Repository

Journal of Urban Management 12 (2023) 1–3HOSTED BY Contents lists available at ScienceDirectJournal of Urban Managementjournal homepage: www.elsevier.com/locate/jumEditorialDigital technologies in urban planning and urban management1. IntroductionOver the last decade, there has been growing attention to applying digital technologies in urban planning and management (seeGeertman and Stillwell, 2020 for an overview). One of the underpinning reasons for this is the technological development and the globalpolitical, social, and economic push toward developing smart cities concepts and applications (Sabri, 2021). Similarly, attention tourban informatics, urban analytics, and city science paradigms is rising. Accordingly, the demand for new skill sets led the highereducation institutes to offer new programs for training the next generation of urban planners with capabilities of urban analytics, urbaninformatics, and city science (see, e.g., Punt et al., 2020). Therefore, there is more appreciation for the practice of urban planning andmanagement of emerging technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), and Digital Twins (Lin & Ben-neker, 2022).In addition, the advancements in digital technologies, including cloud computing, high-performance, and optimized computingsystems, as well as customized sensor manufacturing, increased the capability of agencies to collect, store, and process an unprecedentedamount of data in very high resolution (Liu et al., 2022). For example, the essential role of cloud computing and digital platforms wasacknowledged during the recent pandemic due to the COVID-19 outbreak (Kim et al., 2021). With these advancements in knowledgeand technologies, we expect a paradigm shift and improvement in the quality of public services. However, the evidence suggestsotherwise, and inmany jurisdictions, the planning process is manual, paper-based, and tedious (Daniel& Pettit, 2021). As an example, inthe process of decision-making for the development of infrastructure and assessment of building development proposals, there is a lackof data harmonization, which generate inaccurate, complex, and contestable results.While many ad hoc planning and decision-making processes may not be evidence-based, the role of digital technologies and bestpractices to support collaborative and inclusive decision-making needs to be further communicated. Therefore, in the wake of uncer-tainty on the implications of digital technologies and smart city investments for changing urban planning and urban managementfunctions, this special issue aims to enlighten on their implications for urban planners.Recent literature indicates that the role of digital technologies in the urban planning and management context should be beyond thescope of automated routine functions serving buildings, infrastructures, and people (Sabri et al., 2015; Jiang, 2021). Instead, thesetechnologies should create an integrative and collaborative ecosystem that facilitates a network and stream of continuous information toplan for equity, environmental sustainability, quality of place and life, and efficiency in cities (Sabri et al., 2016).Many governments, industries, and academia worldwide believe that adopting emerging technologies, including Digital Twins,Artificial Intelligence (AI), Machine Learning, and IoT, can improve the quality of public services and result in community satisfactionand quality of life (ANZLIC, 2019; Dembski et al., 2020; Deren et al., 2021). However, it is unclear which planning processes can beaffected and what are the benefits, advantages, risks, and implications of adopting such technologies. Against this background, thepresent special issue on ‘Digital Technologies in Urban Planning and UrbanManagement’ aims to stimulate theoretical discussion on thistopic and contribute to a roadmap for the digital transformation of planning that supports quality urban planning and management.2. Outline of the special issueThe contributions to the special issue are structured as follows. After presenting a holistic overview of the academic debate ondigitalization in urban planning and urban management (Mortaheb & Jankowski, 2022), we will highlight different examples of digitalapplications in urban planning from a planning professional's perspective (Liyanage et al., 2022; Al-Sehrawy et al., 2023), beforereflecting on different examples of how such technologies are implemented in the local planning context (Jiang et al., 2022; Sucupirahttps://doi.org/10.1016/j.jum.2023.02.003Available online 24 February 20232226-5856/© 2023 The Authors. Published by Elsevier B.V. on behalf of Zhejiang University and Chinese Association of Urban Management. This isan open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Editorial Journal of Urban Management 12 (2023) 1–3Furtado et al., 2023) and what this implies for the role of the planner (Nummi et al., 2022) and leadership (Bastidas et al., 2023).First, to give a holistic overview of the debate, Mortaheb and Jankowski (2022) highlight the role of GeoAI (Geospatial ArtificialIntelligence) in enhancing the efficiency of urban services, improving the quality of urban life, and addressing sustainability andresilience challenges. They suggest integrating IT infrastructure and planning activities to leverage networked computing and inter-operable data and analytics would remove the barriers to applying GeoAI in the planning, design, and management of cities. To do so,they offer a schematic overview of how city planning interacts with fields of GIScience, data science, and big data to achieve smart citygoals. This schematic overview is illustrated with practical experiences using real empirical cases. They argue that the discipline of(urban) planning should play a more prominent role in the planning, design, and management of smart cities.Next, from a planning professional's perspective, the special issue indicates that new business models as outcomes of emergingtechnologies will impact the skillset and code of practice among planning experts. For instance, Liyanage et al. (2022) explain applyingAI-based neural network models in the city of Melbourne to forecast public transport demands. This modelling practice requirestransportation planners to improve their capabilities using AI and Deep Learning (DL) analytics for scenario-based developments. Theirfindings show that applying AI outperforms existing forecasting models and leads to passenger demand predictions with over 90%accuracy. In terms of urban management, costs and efficiency of transport operations can be improved, as well as customer satisfactionand sustainability of public transport.As the example of applying AI and DL in Melbourne shows, technological development is ever-increasing. New technologies, such asDigital Twins, are introduced to the planning society, with significant potential opportunities to improve public services. However,according to Al-Sehrawy et al. (2023), their variety and extent of applications in urban management need further investigation. Theypoint out that however refined Digital Twins could be, they still largely fail to shed light on the underlying worldviews and values of theurban planners that are either developing or using these Digital Twins in their daily practices. This calls for more specific attention to therole of the planner, and the urban context in which digital technologies are applied.The next contribution of Jiang et al. (2022) is continuing on the point of putting a planner's perspective central in the contextu-alization of smart city technologies. They argue that given that the adoption of digital technologies in urban planning and managementis growing fast, the contextualization of smart city technologies in different jurisdictions is important. Planners and smart city advocatesshould consider the role of context in the handling of urban issues with the support of digital technologies. Three smart city projects inChina, Singapore, and the Netherlands were compared. It was concluded that the difference in sociotechnical and political contextsdetermine the scale and multiple domain application areas of digital technologies. For smart city strategies to be successful, a closeconnection between the technology itself and the socio-spatial context in which the technology is embedded is needed. The plannerplays a key role in establishing such a connection. Moreover, Sucupira Furtado et al. (2023), examined smart governance and digitalgovernment in Brazil. Their findings highlighted the critical role of data literacy, transparency, and commitment to social justice amongplanners and policymakers to achieve a sustainable smart city.In line with this, Nummi et al. (2022) emphasize the planning context and planners' requirements to determine the scale and level ofsophistication in adopting digital technologies. They argue that the adoption of Information Model (IM)-based planning practices is notonly based on the planning outcomes, but also the planners' capabilities, planning legislation, as well as planning practice. Therefore, thecontextual elements of organizations, governance, and practice are important determinants for deciding the type and level of digitaltechnologies. They draw on insights from the digitalization of planning processes in Finland to show how factors such as local planningpractices, rhetoric, planners’ cognitive frames and mindsets, and collaboration between planners are often undervalued for driving theimplementation of digital technologies in planning practice.Finally, in looking forward, Bastidas et al. (2023) explore the topic of leadership for responsible digital innovation in the builtenvironment. From a multi- and inter-disciplinary perspective, they reflect on competencies needed for leaders to create public value indealing with digital technologies in urban planning. They conclude that comprehensiveness is often lacking in identifying competencyrequirements. Their suggested framework helps to define multi-faceted competencies in city ‘smartification’, to discover multidisci-plinary strategic and operational leadership roles, and to define tasks in digital innovation processes more clearly.3. Concluding remarksIn conclusion, this special issue indicates that changing the planning practice and code of conduct in dealing with digital technol-ogies in urban planning and urban management is inevident. City planning is becoming a dominant integration domain in the widerdebate on geo-/spatial AI, data science, and big open data. This is reflected in how digital technologies are already transforming urbanpractices, for instance, through AI-based urban modeling and digital twins. Our contribution point to the urgency of putting the plannermore central in the management of such technologies in the urban realm. To sustain professional services and ensure the success ofdigital technologies applications, attention to the context elements is crucial, together with more in-depth attention to planning culture,planners’ cognitive frames, and the role of multi-faceted and multi-disciplinary leadership of digital innovation processes in cities.ReferencesAl-Sehrawy, R., Kumar, B., & Watson, R. (2023). The pluralism of digital twins for urban management: Bridging theory and practice. Journal of Urban Management.https://doi.org/10.1016/J.JUM.2023.01.002ANZLIC. (2019). Principles for spatially enabled digital Twins of the built and natural environment in Australia.Bastidas, V., Oti-Sarpong, K., Nochta, T., Wan, L., Tang, J., & Schooling, J. (2023). Leadership for responsible digital innovation in the built environment: A socio-technical review for re-establishing competencies. Journal of Urban Management. https://doi.org/10.1016/j.jum.2023.01.0042Editorial Journal of Urban Management 12 (2023) 1–3Daniel, C., & Pettit, C. (2021). Digital disruption and planning – use of data and digital technology by professional planners, and perceptions of change to planningwork. Australian Planner, 57(1), 50–64. https://doi.org/10.1080/07293682.2021.1920995Dembski, F., W€ossner, U., Letzgus, M., Ruddat, M., & Yamu, C. (2020). Urban digital twins for smart cities and citizens: The case study of herrenberg, Germany.Sustainability, 12, 2307.Deren, L., Wenbo, Y., & Zhenfeng, S. (2021). Smart city based on digital twins. Computational Urban Science, 1, 1–11.Geertman, S., & Stillwell, J. (Eds.). (2020). Handbook of planning support science. Edward Elgar Publishing.Jiang, H. (2021). Smart urban governance in the ‘smart’era: Why is it urgently needed? Cities, 111, 103004.Jiang, H., Geertman, S., & Witte, P. (2022). The contextualization of smart city technologies: An international comparison. Journal of Urban Management. https://doi.org/10.1016/J.JUM.2022.09.001Kim, H. M., Sabri, S., & Kent, A. (2021). Smart cities as a platform for technological and social innovation in productivity, sustainability, and livability: A conceptualframework. In Smart cities for technological and social innovation (pp. 9–28). Elsevier.Lin, Y., & Benneker, K. (2022). Assessing collaborative planning and the added value of planning support apps in The Netherlands. Environment and Planning B: UrbanAnalytics and City Science, 49(2), 391–410.Liyanage, S., Abduljabbar, R., Dia, H., & Tsai, P. W. (2022). AI-based neural network models for bus passenger demand forecasting using smart card data. Journal ofUrban Management, 11(3), 365–380. https://doi.org/10.1016/J.JUM.2022.05.002Mortaheb, R., & Jankowski, P. (2022). Smart city re-imagined: City planning and GeoAI in the age of big data. Journal of Urban Management. https://doi.org/10.1016/J.JUM.2022.08.001Nummi, P., Staffans, A., & Helenius, O. (2022). Digitalizing planning culture: A change towards information model-based planning in Finland. Journal of UrbanManagement. https://doi.org/10.1016/J.JUM.2022.12.001Punt, E. P., Geertman, S. C., Afrooz, A. E., Witte, P. A., & Pettit, C. J. (2020). Life is a scene and we are the actors: Assessing the usefulness of planning support theatresfor smart city planning. Computers, Environment and Urban Systems, 82, Article 101485.Sabri, S. (2021). Introduction: Being smarter for productivity, livability, and sustainability. In Smart cities for technological and social innovation (pp. 1–8). Elsevier.https://doi.org/10.1016/b978-0-12-818886-6.00001-0.Sabri, S., Rajabifard, A., Ho, S., Amirebrahimi, S., & Bishop, I. (2016). Leveraging VGI integrated with 3D spatial technology to support urban intensification inMelbourne, Australia. Urban Planning, 1(2), 32–48. https://doi.org/10.17645/up.v1i2.623Sabri, S., Rajabifard, A., Ho, S., Namazi-Rad, M.-R., & Pettit, C. (2015). Alternative planning and Land administration for future smart cities [leading edge]. IEEETechnology and Society Magazine, 34(4). https://doi.org/10.1109/MTS.2015.2494298Sucupira Furtado, L., da Silva, Ferreira, M. G. F., de Macedo, & de Melo Lima Cavalcanti Moreira, J. K. (2023). A framework for Digital Transformation towards SmartGovernance: using big data tools to target SDGs in Ceara, Brazil. Journal of Urban Management. https://doi.org/10.1016/J.JUM.2023.01.003.Soheil Sabri, Guest Editor *Center for Spatial Data Infrastructures and Land Administration (CSDILA), Department of Infrastructure Engineering, Faculty of Engineeringand Information Technology, The University of Melbourne, Level 6, 700, Swanston Street, Carlton, Vic, 3053, AustraliaPatrick Witte, Guest EditorFaculty of Geosciences, Department of Human Geography & Spatial Planning, Princetonlaan 8a, Utrecht Vening Meinesz Building A, Room6.18, P.O. Box 80.115, 3508 TC, Utrecht, the NetherlandsE-mail address: P.A.Witte@uu.nl.* Corresponding author.E-mail address: soheil.sabri@unimelb.edu.au (S. Sabri).3

Digital technologies in urban planning and urban management

https://dspace.library.uu.nl/bitstream/1874/427468/1/1_s2.0_S2226585623000079_main.pdf

Digital technologies in urban planning and urban management

Abstract

Similar works

Full text

Available Versions

Utrecht University Repository