Digital disillusions: smart technologies as a panacea for sustainable cities

Digital disillusions: smart technologies as a panacea for sustainable cities

Thursday 28.4 at 13.15–14.45

Visualizing different sources of uncertainty of green elements in 3D visualizations

Viktorija Prilenska, Tallinn University of Technology; Henna Fabritius, Tallinn University of Technology; Petri Kangassalo, Aalto University & Pilvi Nummi, Aalto University

In urban planning, 3D visualisations are found useful for communicating plans to various stakeholders by stimulating discussion and helping to understand impacts of plans. There is always a degree of uncertainty in plans, and this has been illustrated, for example, by adjusting the level of detail and realism of the built environment in models. However, modelling and visualizing the green environment involves also two other sources of uncertainty. First, existing green areas may entail uncertainty due to gaps in the empirical data they are based on (e.g. imprecise measurements or missing information on the species, ages, sizes, or exact locations of green objects).  Second, a source of (statistical) uncertainty is introduced if temporal projections of green area change are included in the 3D visualizations: Ecological processes are inherently stochastic due to the random elements in biological processes and earth systems. Therefore, the longer the development of green elements is simulated into the future, the less certainty there is on their resulting states.

In this paper, we focus on the challenge of how to visualize the different sources of uncertainty of green elements in interactive 3D visualizations. Our aim is to analyze in an empirical study how users of a co-planning application perceive and understand the different types of uncertainties related to visualizing vegetation models and their future projections.  Different visualization styles for 3D plants will be evaluated in a series of user testing sessions by means of a game-engine based 3D co-planning application entitled Virtual Green Planner. The results can be utilized when developing advanced simulations, e.g. storm simulations, which are used to predict the consequences of extreme weather conditions.

Towards a resilient city in the digital age

Osunkoya Modupe & Partanen Jenni, Taltech / Tampere University

In today’s world, societies have become increasingly complex and unpredictable, the need to provide cities’ decision-making models, strategic development tools and methods should advance. In the age of digitalization, there are available data in the urban ecosystem that can interact with urban elements and provide data-driven decisions for smart cities such as mobility, infrastructures, citizens, places, and spaces. From this standpoint, cities should embrace tools to address, improve the quality of life, determine socio-economic diversity and urban vitality to plan newer towns. The availability of big data enhances Urban vitality’s determination about human activities, temporal patterns, and the flows of people interacting with the built environment.  New digital tools introduce more vitality indicators related to the available location data. The transition from traditional to digital methods and data enables analyzing spatial and temporal dynamics in detail and different cities in a comparable manner. This paper examines the city’s evolution in time series to determine the spatial and socio-economic diversity. We explore using the Geographical Information System (GIS) primary and secondary spatial data collected from statistical companies and mobile phone data to determine how well urban elements are connected which human users interact within urban space. The result provides an overview of applied methods, their possibilities, and their limitations. It suggests new ways to measure urban vitality using suitable digital methods extensive and traditional data in a complementary manner. As technology and science become available, urban stakeholders see these tools and paradigms of thought as the future of smart city management to strengthen the resilience system. Future studies will include analyses applying social media data such as Twitter and international comparative case studies.

Can cities afford to not solve problems of environmental sustainability with technology?

Jakonen Olli, University of Turku, TalTech

The role of cities has been recognized as key in both “the good” and “the bad” of solving or adjusting to problems of environmental sustainability. On the one hand, cities are “engines” of economic growth, and as such have contributed to problems such as overconsumption of resources and energy and pollution of the environment. On the other hand, cities are considered to be diverse loci of innovation that facilitate the creation of solutions to environmental problems. In her 1969 book “The Economy of Cities”, the renowned urban scholar Jane Jacobs argued that while developing economies are ruthless to nature, the destruction they cause is overshadowed by the destruction of economies that through their stagnation are locked-in to heavily exploiting a narrow range of resources. This argument put forth by Jacobs works to mediate the conversation about the role of cities in producing positive or detrimental effects towards the environment. The presentation revisits this argument and seeks to assess it in the context of contemporary “smart” cities and more contemporary texts about the effects of urban development on the environment. In the light of Jacobs’ argument, it asks whether the solutions of a smart city (“smart solutions”) should be understood as an impactful effort that prevents stagnation (i.e. lack of Jacobsian urban vitality) or a type of solutionism that does not contribute to urban vitality acting as an important resource that tackles problems of environmental sustainability. Can cities afford to not solve problems of environmental sustainability with technology?

Smart art in the cities: Examples of using digital public art in presenting urban data and information

Lundman Riina, University of Turku

With smart technologies, it is possible to monitor, collect, process, and present a vast amount of urban data and information. This material can then be used and applied in urban management and planning in various ways. Smart screens, mobile technologies, and other applications based on urban informatics and ubiquitous computing enable presenting urban information to wider public in real time and actual sites. However, the content and meaning of such presentations may remain distant and uninteresting to ordinary citizens. In this presentation, I discuss whether digital public art can be used as a means to make the communication regarding urban data and information more accessible and approachable to people. I go through several international and Finnish examples of how digital art has been utilized in such cases, with the focus on artworks that aim to promote urban sustainability. I ask, what smart art in the cities is and could be and whether there is a place for a critical approach regarding the topic. As a wider goal, my aim is to combine the discussions about smart cities, public art, and citizen participation into a future research project combining arts, sciences, and urban planning.

Simulating the effect of reducing the maximum road speed in the city of Tallinn

Rasoulinezhad Mahdi & Partanen Jenni, Taltech / Tampere University

Understanding how to manage change in increasingly complex cities is becoming more important than ever mainly due to the fast-ongoing change in the ICT. However, urban planners are often unaware of how to deal with and plan for change, especially in the context of the multiple complexities in cities. This issue becomes tangible particularly in the case of mobility systems. There is a growing need to understand the complex urban dynamics for planning future cities. Computer simulations are established tools for evaluating the behavior of the urban, also mobility systems. Many of the tools in practical use apply large scale statistical computation limited regarding the unpredictable pattern emerging from behavior of individual agents. The commercial microsimulation models are detailed and heavy, making them inappropriate for regional use. In this study we apply and modify a dynamic computer model called MATSim to simulate a traffic control choice(reducing the maximum speed in the city of Tallinn). We use sensor data from a telecommunication company and OD-matrix to verify and calibrate the model. Our presentation explains what kind of unexpected outcomes, failures, and achievements will result from this decision

Dynamic delineation of urban areas resulting from daily mobility patterns – case of Tallinn

Vanhatalo Jaana, Tampere University

The urban areas reflecting urban figures, such as urban population percentage and urbanization rate, are mostly based on national urban area definitions. These definitions are essential when defining what is urban. Further, they pertain e.g. to urban planning, policies and funding instruments. Our prior study shows that the comparison of these definitions results in widely varying outcomes (Vanhatalo & Partanen 2022). Furthermore, many urban area definitions are based solely or mostly to population, i.e. to the place of residence. Therefore, they disregard many of the spatio-functional and temporal features of urbanity. Characteristics, which are essential in current urban discourse. To grasp these essential features, mobile and other digital data can be utilized. These are not yet applied in the official definitions, but we argue that mapping and analyzing time series of telecommunication data reflecting the daily mobilities of inhabitants, could reveal dynamicity of urbanity beyond the stable residency.  We analyze spatially (GIS) mobile phone location data to produce novel, dynamic readings of delineation of urban areas. We compare these results with the urban areas produced by certain national definitions in order to provide potential directions for developing urban area definitions. The case city of our study is Tallinn, Estonia. In addition to mobile phone data, common spatial datasets, such as population and buildings, are utilized. The results contribute to the discussion in urban studies and planning of future development needs of urban area delineations.