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Measuring the City: The Power of Urban Metrics

Published onJun 20, 2022
Measuring the City: The Power of Urban Metrics


Big data, AI, and smart cities have entered the realm of urban planning as dei ex machina in the past couple of decades. New urban data sources, such as GPS, traces collected from cell phone data, social media, sensors, and satellite imagery provide new vantage points on the formerly hidden environmental, social and physical realities. For example, GPS traces are instrumental in revealing unmapped spatial dynamics, such as semiformal transportation networks (Williams 2020) and walking patterns (Malleson et al. 2018; Salazar Miranda et al. 2021; Sevtsuk et al. 2016), and the richness of social media data is critical to monitor changing activity centers, and their content can reveal insights about how places are perceived by their users (Cranshaw et al. 2012; Hu et al. 2019; Saiz et al. 2018), and the use of sensors and satellite imagery can support the monitoring of environmental conditions posing a challenge to cities, such as urban heat islands (Ignaccolo 2021) and spaces of conflict (Kurgan 2013). Along with these augmented and diversified data sources, more complex algorithmic models are also being developed to address global challenges, such as the climate crisis and the widening inequalities in cities (Kariman et al. 2019; Castro et al. 2020; Li et al. 2021; Zekić-Sušac et al. 2021; Rolnick et al. 2022). 

Scholars, practitioners, and public officials are leveraging data and pairing it with models to better understand, visualize, and simulate urban problems.

However, with new methodologies come rising challenges related to the processing of data, data analysis, and how to build models that can accurately characterize complex city environments. One of the main challenges associated with leveraging the troves of newly available data is the emergence of an “exploratory science,” in which opportunistic data define the research questions through intensive explorations of patterns and relations in the data (Kitchin 2014). This approach is inherently limited by the available data types, which are not necessarily valuable for informing theoretical debates in the field or addressing pressing questions. A second challenge is to build models that are aware of local cultures and contexts so that they do not oversimplify the complex reality of our cities (Boyd and Crawford 2012; Wilson 2017). For the study of urban form, in particular, the growth of using crowd-generated big data provides opportunities to gain insights into how people perceive and associate meaning with the built environment (Crooks et al. 2016). However, these processes typically require ground-truthing and the combination of auxiliary data sources to alleviate selection bias concerns (Acolin and Kim 2022). In light of the above, urban metrics that characterize the life and form of cities should be adapted to their local context to provide nuanced insights into their functioning. 

The act of shaping cities remains a political gesture often legitimized through measurements to quantify urban life.

The implementation of urban data and models is inextricably linked to the sociopolitical context of each location. For example, heavy criticism was placed on the early models of smart cities built from scratch in Masdar (2006) and Songdo (2008). Moreover, scholars problematized how optimization models that use proprietary data and platforms alienated citizens from the design process, creating “non-places” that lack community involvement (Greenfield 2013; Benedikt 2016; Jensen 2016; Shin 2016; Karvonen et al. 2019). More recently, the controversy around data anonymization derailed the Sidewalk Toronto (2017–2020) project, further demonstrating how data-driven urbanism must effectively engage the local community to be successful (Coodman and Powles 2019). In the meantime, calls for data actions for the public good (Williams 2020), smart enough cities (Green 2019), and smart but meaningfully inefficient data governance (Cordon and Mugar 2020) have charted alternative pathways for data-driven urban solutions that move toward more local engagement when developing such solutions. Evaluating how best to implement these models is critical to developing new methods that can further our understanding of how societies inhabit urban spaces.

Projections Volume 16, titled “Measuring the City: The Power of Urban Metrics,” brings together papers that reflect on spatial data models for city making. The issue includes the work of scholars studying political structures and how they relate to the built environment using novel data sets and methodologies and others who study the politics of urban design and policy development using urban data. As the editors, we hope that this volume animates a discussion to build better data models that extend our collective understanding of social life and urban form while remaining cognizant of their inherent limitations. 

Overview of the Papers and Reflections

The papers in Projections Volume 16 share several commonalities across the topics and methods they employ. 

The papers engage with various urban data and modeling techniques but pay particular attention to contextual and behavioral nuances. Three papers, "From exceptional architecture to city icons? Analyzing data scraped from Flickr" by Nadia Alaily-Mattar, Lukas Vordemann, Diane Arvanitakis, Alain Thierstein, "Do you live in a bubble? Designing critical metrics to intervene in the cartography of urban diversity" by Anders Koed Madsen, and “Parallel Worlds: Revealing the Inequity of Access to Urban Spaces in Mexico City Through Mobility Data” by Emmanuel Letouzé, Zinnya del Villar, Rodrigo Lara Molina, Berenice Fernandez Nieto, Guillermo Romero, Julie Ricard, Diego Vazquez, and Laura Arely Centeno Maya introduce novel approaches to broaden our understanding about architectural symbolism, political diversity and access to public space across different income groups through mining social media and mobility data. 

The paper “From exceptional architecture to city icons? Analyzing data scraped from Flickr” leverages millions of photos taken by individuals in 2009, 2014, and 2019 to understand how an iconic architectural project like the Hamburg concert hall —also known as the Elbphilharmonie— is perceived by Flickr users. The results show that the Elbphilharmonie has been attracting sustained attention across the study period, as revealed by the increase in the number of photographs taken in proximity to the building. The paper uses text analysis to show that some hashtags have reduced frequency while other topics in the photos have gained prominence. These findings underscore the diversification and shift of activity around cultural points of interest and deliver empirical evidence to understand how photographs from online photo-sharing platforms can be leveraged to study architectural developments.

The paper “Do you live in a bubble? Designing critical metrics to intervene in the cartography of urban diversity” discusses the limitations and benefits of a recently launched tool that measures political diversity in Copenhagen. The tool uses Facebook “check-ins” to expose the political tendency of people and provides a new lens to study the diversity (and the political landscape) of different neighborhoods and locations in the city. The paper details how the tool was produced, how it sparked new debates around urban diversity, and the importance of engaging in “imaginative cartographies” beyond algorithmic prediction.

The paper “Parallel Worlds: Revealing the Inequity of Access to Urban Spaces in Mexico City Through Mobility Data” leverages a year of mobility data to study the use of public spaces by different income groups in Mexico City. Although different income groups do mix in particular urban spaces, it is common for these spaces to be frequented by high or low-income groups only, providing few opportunities for social mixing across income groups. The paper also points to spaces like government services and cultural sites, which are particularly unequal. Also, it highlights costly access as one of the main barriers restricting people living on the city's outskirts from accessing museums and sports clubs.

The three papers leverage the rich cultural context to interpret their results. Alaily-Mattar et al. show the importance of validating their findings by cross-examining them with local events and the typical urban design of the city. Madsen enhances the discussion around political diversity using Facebook data in Copenhagen by incorporating complementary data on public discourses found on other social media channels and news articles. Similarly, the study by Letouzé et al. focuses on Mexico City, which is salient in terms of socioeconomic inequality and uses mobility data to shed light on its dynamics.

Other papers tackle the limitations of data availability across different contexts. Two papers, “Scrutinizing the Buzzwords in the Mobility Transition: The 15-Minute City, the One-Hour Metropolis, and the Vicious Cycle of Car Dependency,” by Christian Gerten and Stefan Fina, and “Urban MorphoMetrics + Earth Observation: An Integrated Approach to Rich/Extra-Large-Scale Taxonomies of Urban Form,” by Sergio Porta, Alessandro Venerandi, Alessandra Feliciotti, Shibu Raman, Ombretta Romice, Jiong Wang, and Monika Kuffer, develop novel approaches to measure urban form across different contexts. 

The paper “Scrutinizing the Buzzwords in the Mobility Transition: The 15-Minute City, the One-Hour Metropolis, and the Vicious Cycle of Car Dependency” develops a new tool to assess cities in their shift toward implementing plans that encourage active mobility, such as the 15-minute city or the one-hour metropolis. In particular, the paper uses a combination of metrics, including measures of the pedestrian network, green spaces, land use mix, and proximity to services, to map neighborhoods into one of four typologies (walking/transit, walking, transit, and car-dependent) and illustrate its application for Paris, Portland, and Melbourne. Their within-city comparisons show that cities differ significantly in their mobility offerings. The approach outlined in the paper can help evaluate transportation policies. 

The paper “Urban MorphoMetrics + Earth Observation: An Integrated Approach to Rich/Extra-Large-Scale Taxonomies of Urban Form” combines elements, such as buildings, streets, plots, and functional characteristics, such as dimension, shape, and connectivity, to map urban form. Their methodology is deployed in Amsterdam, Bologna, Kochi, and Nairobi, providing a consistent way to measure urban form across different geographical contexts. 

Both studies, by Gerten and Fina and Porta and colleagues, are motivated by the limited availability of data to measure urban form and human behavior comparatively across contexts. Gerten and Fina propose a measure for the “15-minute city” concept that relies on relatively easy data to find in different cities to facilitate comparisons across cities. Porta and colleagues tackle the limitations of data availability and quality by generating a taxonomy of urban form that can be used across cities in the Global South and North and informal settlements. 

A final set of papers warns against the pitfalls of urban metrics. Two papers, “Failure to Innovate: Urban Technocracy and the Making and Unmaking of Sidewalk Labs’ Smart City,” by Justin Collar, and “Politics of Open Land Data: The Case of Delhi's Land Pooling Policy,” by Sumedha Jain, Benjamin John, and Abhik Banerji, examine the politics of data-driven master plans and policies through a historical and ethnographic lens.

The paper “Failure to Innovate: Urban Technocracy and the Making and Unmaking of Sidewalk Labs' Smart City” examines innovation models in urban management. In particular, it studies the Sidewalk Labs smart city project in Toronto to argue for technologies embedded in the public sector’s actual processes. The paper argues that smart technologies should complement or augment existing practices instead of duplicating urban management efforts that have a track record of working efficiently. The paper uses the Sidewalk Labs project as an example of a cautionary tale for the future implementation of smart city models. 

The paper “Politics of Open Land Data: The Case of Delhi’s Land Pooling Policy” studies the impact of the land pooling policy in Delhi. It sheds light on the frictions in land ownership and community structures that have hampered the implementation of the policy, highlighting the lack of trust between landowners and development authorities as the main explanation. The lack of communication between the government and landowners has been a crucial roadblock to successfully implementing the land pooling policy and has ultimately contributed to the increasing trend of unauthorized development.

Collar and Jain and colleagues offer a historical and ethnographical lens on the development and implementation of urban metrics. Collar focuses on the Sidewalk Labs project to show how projects implemented without proper citizen participation alienate its citizens. Jain and colleagues trace how data asymmetry among stakeholders unfolds and leads to a lack of trust and a subsequent halt of the land pooling policy. By delving into the consequences, both papers underscore the need to use technology as a means, not an end, and call for more transparency in and around data-driven policies.

In conclusion, Projections Volume 16 provides a venue for critical reflections on nuanced and situated practices of urban planning that can hopefully inform and transform cities. Each paper engages with the call through a new approach to urban measurements: some papers illustrate data-intensive work, others propose alternatives for widely used measurements to evaluate urban form, and the remainder offer critiques of data-driven master plans and policies. Collectively, the papers show the breadth of work in the scholarship on data and cities. 


We are grateful to the authors who contributed to this volume and the anonymous reviewers who provided invaluable feedback. We would also like to thank the members of our editorial board for their participation and the team at MIT Press and PubPub for their support during the publication process. We also thank the MIT Press Copyediting Services. Special thanks go to Benjamin Preis, Binzhe Wang, and Rounaq Basu for additional support in the review process.

We launched a data visualization competition, "Visualizing Cities" (, to accompany Projections Volume 16. We want to express our gratitude to the competition contributors, the DUSP CRON team, for setting up the website domain and offer a special thanks to Calvin Phung (MIT Undergraduate Research Opportunities Program student), who helped us design and develop the website. 

We want to express our deep gratitude to our department head, Professor Christopher Zegras, the DUSP HQ, and Takeo Kuwabara for the funding and administrative support. Finally, we thank our managing editor, Professor Lawrence Vale, and our faculty advisor, Professor Sarah Williams, for their thoughtful guidance throughout the process from the theme’s inception to the publication of this volume.

[Image credit: “The Atlas of the Carbon Economy” by Jamie Williams]

Editorial Board

Shlomo Angel, Professor of Urban Planning at New York University's Marron Institute

Michael Batty, Bartlett Professor of Planning at University College London

Catherine D’Ignazio, Assistant Professor of Urban Science and Planning at MIT DUSP

Annette Kim, Associate Professor at the USC Sol Price School of Public Policy

Rob Kitchin, Professor of Human Geography at the National University of Ireland, Maynooth

Laura Kurgan, Professor of Architecture at Columbia University GSAPP

Andres Sevtsuk, Associate Professor of Urban Science and Planning at MIT DUSP

Emily Talen, Professor of Urbanism at the University of Chicago

Eyal Weizman, Professor of Spatial and Visual Cultures at Goldsmiths, University of London

Lawrence J. Vale, Ford Professor of Urban Design and Planning at MIT DUSP [Managing Editor, Projections 16]

Sarah Williams, Associate Professor of Technology and Urban Planning at MIT DUSP [Faculty Advisor, Projections 16]

Image credit: “The Atlas of the Carbon Economy” by Jamie Williams


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