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Challenges and Opportunities for Cities

URBAN THEORY TO UNDERSTAND CITY CHALLENGES AND OPPORTUNITIES

Luís Bettencourt, University of Chicago

Luís Bettencourt, University of Chicago, spoke about the state of urban theory—the science of cities that provides the framework for understanding data and modeling. Urban theory relies on a convergence of ideas from geography, economics, sociology, and engineering, with newer contributions from data and comparative analysis across cities, to understand the human experience with scientific rigor. Bettencourt directs the Mansueto Institute for Urban Innovation at the University of Chicago,¹ where he tries to triangulate concepts and methods from ecology, evolution, and the natural sciences with emerging perspectives from the social, political, and economic sciences and new empirical evidence.

Bettencourt showed participants an image from Apollo 8 in 1968, which changed people’s perspectives about the state of the Earth and is credited with the beginning of the environmental movement, when sustainability entered mainstream public consciousness. He pointed out that such a global perspective was both compelling and paralyzing, because it is difficult to know why and from where challenges to the global

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¹ For more information about the Mansueto Institute for Urban Innovation, see https://miurban.uchicago.edu, accessed March 13, 2019.

environment are arising. Aerial photographs and satellite images of India, Beijing, and Hong Kong demonstrate that air quality, diversity, transportation, information, and continual change present ongoing challenges and opportunities within cities. Bettencourt argued that a new focus on cities—as demographic, economic, and information centers where consumption and innovation occur—is making it possible to generate a more scientific understanding of human societies and their relationship to Earth’s natural environments and to initiate policies with more traction. He stressed that cities are ultimately about people (and their societal interactions) whose needs could be better understood by looking at cities from the ground up instead of from the sky. This new perspective defines the challenge of the science and practice of urban planning and policy.

Bettencourt presented the United Nations Habitat’s new declaration for what urban policy should be by 2030, a “New Urban Agenda.”² It asks for an approach to urban planning that is about people-centered cities, and people’s rights to the cities, which are inclusive and sustainable from an environmental perspective. This vision comes from the larger framework of the United Nations’ 17 Sustainable Development Goals. Goal number 11, in particular, focuses on sustainable development in cities, targeting housing, transportation, sustainable planning, culture, resilience, pollution and health, and green public spaces. Although he noted the challenge in trying to achieve these goals, he expressed his encouragement at the worldwide mobilization for this systemic process. He described this as an example of an approach toward global policy and mentioned that similar attempts to drive policy are being echoed in almost every American city. For example, he described the city of Los Angeles’s plan, Sustainable City pLAn,³ which aims to integrate quantitative goals to create a cleaner environment, a stronger economy, and a more equitable community.

Against a backdrop of aspirational policy, it is necessary to create a fundamental knowledge about cities and urbanization that can guide these changes at the necessary scope and speed, Bettencourt continued. These difficulties are illustrated by questions such as the following: What does it mean to create a good city? Why are cities growing so fast? What can cities deliver for human societies? He explained that a societal transformation related to communication and information technology lies ahead and that universal urbanization is occurring along with the digital technologies revolution. Data computing and comparative analysis enable the practice of urban science and urban analytics and present new ways

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² For more information about the United Nations’ plan, see http://nua.unhabitat.org, accessed March 12, 2019.

³ For more information about the Sustainable City pLAn, see http://plan.lamayor.org, accessed March 12, 2019.

to deal with data and problems such as urban logistics. However, a challenge remains in how to use this information to better understand how cities work fundamentally.

Bettencourt showed a three-dimensional model of Chicago, noting that Google Earth (and other technology companies) now has similar models for all North American cities. Such models help researchers to think about how the physical environment of a city works and to understand how the built environment is changing. He added that in the next few years, everything will be known about the built environment; researchers must be asking how these data can be used. Other images and measurements from satellites and sensors can measure every tree in a city, for example, or can be used to improve air quality and manage urban heat islands. He emphasized that these types of innovations are a result of the ability to feed ambient data into simulations and real-time analyses. He provided an example of a map of spatial mixing in Chicago that was derived from mobile phone data; he mentioned that this work shows the data’s potential for surveillance and ability to identify a city’s equity issues (see Figure 4.1) in terms of the urban amenities, spaces, and communities available to someone living in a specific neighborhood.

Simply providing the data of people’s movements and the built environment is not science; the objective is to understand why people move, and making sense of cities requires a particular type of theoretical knowledge. Although a city is a physical infrastructure, it is really about people’s socioeconomic interactions and information—the goal is to have generalizable knowledge that can be used to understand multiple cities. Bettencourt emphasized that cities, at their essence, are socioeconomic networks of people and organizations concentrated in space and time. Many researchers are presently aiming to redefine the foundations of social science from this richer and more unifying perspective, based on better empirical evidence and with a renewed focus on human cognition and behavior in complex urban environments.

Bettencourt described four critical scales of urban theory: urban systems (i.e., nations made up of many cities), cities, neighborhoods, and individuals (see Figure 4.2). The scales in between relate to how a city is put together as a network, scaling agglomeration effects and neighborhood effects. Urban theory takes in all of these scales, explains their articulation, and begins to understand how they are interrelated.

Bettencourt explained that all models of economic geography rely on the notion of the city as a bound state in space (i.e., a spatial equilibrium). The classical Alonso model of the monocentric city represents the simplest instantiation of these ideas as a balance between a net income (including consumption costs) that an individual makes from his or her interactions in the city as well as land rents and commuting costs. He noted a trade-off

between these spatialized costs (e.g., an individual would pay higher rent to live in a city than in a suburb, but then in a suburb one might have to pay to commute to the city for work). The model assumes a continuum in terms of managing rents and commuting costs, gives a spatial limit to the city, and defines functional urban areas (i.e., the systems in which people live and work together, known in the United States as metropolitan areas). It follows from elaborations of these models that cities express strong network effects, which relate the outcomes of socioeconomic variables nonlinearly to measures of city size, such as population. For example, the

volume of infrastructure in a city is not proportional to its population: as cities become larger, there is less area of infrastructure per person but simultaneously an increase in gross domestic product per person and many other socioeconomic outputs that result from human interactions. Bettencourt continued by noting that the density of people within cities, both in terms of space and time, promotes diverse interactions that can be measured in relation to production, consumption, and crime, for example. Increasing density can help manage the physical, social, and economic aspects of a city, but such density has to be made livable for residents via more developed urban systems and institutions. He explained that housing is often not affordable in large cities because land surface decreases per capita on average with city size (because of higher densities) and incomes increase. This leads to a rapid increase in land rents (i.e., costs per unit time and area) with city size—faster than incomes. The antidote is either sprawl, with severe congestion and energy costs, or greater building heights and more sophisticated infrastructure (Washington, D.C., is an example of a city in which such construction is prohibited).

These effects taken together result in a specific kind of human experience in cities, which has been discussed in sociology and social psychology

but can now be developed theoretically (i.e., with empirical tests). From this perspective, cities can be understood as a social network in which each person has a varied trajectory through the built environment with consequences for information, energy, and resources. An increase in interactions per capita enlarges on average the opportunities for knowledge creation, specialization, and interdependence, he continued. The impacts of a city can be measured in terms of associated social benefits and costs; equity and sustainability in cities can be measured in terms of the properties of specific neighborhoods, where spatial selection is associated with income, race and ethnicity, and education.

Bettencourt began a brief discussion about scientific and data-driven tools for urban planning, such as OpenStreetMap, which maps the built environment. It is possible to identify places that are not connected via streets (i.e., where people will not have access to services) and use that information to create networks for urban planning. During a later discussion, Rhiannan Price, DigitalGlobe, asked whether Bettencourt has observed that governments are hesitant to give OpenStreetMap data credibility in data-poor environments. Bettencourt said that there will always be political resistance to what is happening at the city level, but mapping data can be verified and consequently can be a basis for consensus. He shared his excitement about data from organizations such as DigitalGlobe and OpenStreetMap because these technologies have the potential to allow people to create a desirable future for their cities.

He concluded by explaining that there are many challenges and opportunities for urban science, particularly to enable equal opportunities and economic, sustainable growth in each neighborhood and across the globe. He emphasized that improvements are needed to increase the quality of models for cognition, agency, and institutions in relation to innovation and economic development. He added that a better quantitative understanding of how energy and resource use are connected to value would also be beneficial. Lastly, he emphasized the need to focus on design and planning that starts with an individual but embraces the complexity of the city.

DISCUSSION

Aniruddha Dasgupta, World Resources Institute, noted that cities are trying to connect economic growth, environmental footprint management, and quality of life. He asked how innovations in data science and modeling could help to balance those three entities. Bettencourt responded that more could be known about these processes starting from the bottom up—people, their behaviors, and the physical and economic conditions of the city. Cities change on a daily basis, and this change can

be directed to enable sustainability, economic growth, and more equitable outcomes. However, it is important to be aware of how these processes articulate across time and over various social and spatial scales; otherwise, unintended consequences are possible. Through data and an improved understanding of underlying principles, Bettencourt believes it is possible to comprehend the fundamental ingredients for innovation and economic growth. He added that researchers are beginning to see how the physical, social, and innovation aspects of a city are coming together across scales, starting with people and organizations. Auroop Ganguly, Northeastern University, wondered how to hold policy makers and citizens accountable for their roles in urban sustainability. Bettencourt explained that almost all large cities are setting up quantitative targets for their energy consumption and carbon emissions, and quantitative harmonized standards have now been developed to measure energy expenditures across cities. Responsibility is being taken by cities, and methods are being developed, but questions about the end goal still remain: How much energy should a city use? Would a city use more energy as it becomes greener? What are the social and economic trade-offs?

Audience member David Rabinowitz asked about underlying lifestyle assumptions built into the United Nations’ Sustainable Development Goals. Bettencourt replied that cities are open systems that sustain a great diversity of individuals, choices, and lifestyles; understanding cities requires understanding diversity in human behaviors. Anu Ramaswami, University of Minnesota, noted that many policies are aimed at changing the norm and asked if methods exist to detect effective policy outliers. Bettencourt said that both positive and negative exceptions are always defined against a norm and that urban theory reveals what is typical to most cities, while local deviations express some of these contextual factors. Ramaswami asked about the presence of causal loops, and Bettencourt responded that the city’s spatial equilibrium (i.e., what happens every day in the city) implies a logic of circular causality so that change tends to happen in virtuous and vicious cycles of self-reinforcing effects. It is possible to see how well cities handle certain problems, but the causality connected to making the city more sustainable depends on the accumulation of effects over time and has historical underpinnings. This shows how human development, economic growth, health, and living conditions are changing systematically over time and makes it possible to compare transformations and extract general trends over time, he continued. Understanding and creating positive self-reinforcing cycles of change in different contexts remains a critical goal, he said. Marjorie Lightman, QED Associates, LLC, said that institutional forces may be antithetical to change, but this political reality is an important part of how to create change. Bettencourt emphasized that politics started in

cities and still happens most naturally in cities, where balancing civic and economic issues with basic livelihoods tends to make politics more open and capable of accommodating change. Ideas for change are typically developed in the civic and nonprofit sectors and then enter the political agenda if judged to garner popular support. He asserted that cities benefit from incubating these ideas, typically through advocacy at the civic-sector level, which could improve innovation, mobilize public opinion on larger scales, and increase the pressure to create change in politics.