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  • Urban Planet
  • Knowledge towards Sustainable Cities
  • Online publication date: April 2018
  • pp 147-260
  • Publisher: Cambridge University Press

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Part II Global Urban Sustainable Development

Chapter 7: Rethinking Urban Sustainability and Resilience

David Simon , Corrie Griffith , and Harini Nagendra

This chapter provides a critical review of the evolution, framings, and disciplinary underpinnings of narratives and discourses around two core concepts in this field – namely urban sustainability and resilience – over the last few decades. It further assesses the recent contributions and limitations of these approaches both conceptually and operationally with respect to an urbanizing world. Both terms entered the lexicon in relation to profound societal challenges of our time and were only subsequently applied to more specific contexts, including urban areas. Therefore, our account starts by surveying this broad canvas in order to contextualize the more detailed assessment of urban sustainability and resilience debates that follows. Strategically, this discussion introduces Part 2 on account of both the central importance of these twin concepts and the need to understand some of the diverse ways that they now find expression in key current urban challenges.

7.1 The Evolution of Urbanization and Sustainability Thinking

Following Silent Spring, Rachel Carson’s (Reference Carson1962) landmark study of the effects of excessive pesticide use on bird life and food webs in the United States, international concern for humans’ impact on the environment and the unsustainability of resource-intensive, consumerist lifestyles increased steadily. This concern was spurred by a series of industrial and shipping accidents that caused major pollution disasters, as well as other disparate strands in the 1960s. Consequently, the United Nations convened its landmark Conference on the Human Environment in Stockholm in 1972, for which three other classic texts in the sustainability canon were published from rather different perspectives on the need to live within resource constraints and in harmony with ecological principles. These were the Club of Rome’s Limits to Growth (Meadows et al. Reference Meadows, Meadows, Randers and Behrens1972), Barbara Ward and René Dubos’ Only One Earth (Reference Ward and Dubos1972), and The Ecologist magazine’s A Blueprint for Survival (1972). A key outcome of the Stockholm summit was the establishment of two specialist agencies, the United Nations Environment Programme (UNEP) and the UN Centre for Human Settlements (now the UN Human Settlements Programme, or UN-Habitat), to address environmental conservation and sustainability concerns in general and the complex challenges of urban development and sustainability, respectively.

Stockholm was also the first in what has become established as a regular series of global environmental sustainability summits, most notably the UN Conference on Environment and Development, or UNCED, in Rio de Janeiro in 1992; the World Summit on Sustainable Development, also called WSSD or “Rio+10” in Johannesburg in 2002; and the UN Conference on Sustainable Development, also called UNCSD or “Rio+20,” held again in Rio in 2012. In parallel, the more specific annual UN Framework Convention on Climate Change (UNFCCC) Conferences of the Parties, and equivalent initiatives on other conventions and treaties have helped to focus attention and political negotiations, not always very successfully, on issues of sustainability. In addition, innumerable NGOs and other agencies operating at all spatial scales and from diverse philosophical and theoretical positions have emerged to create an immensely diverse ecosystem of environmentalisms, some of which advocate particular versions of sustainable development, while others argue for “deep” or other ecological environmentalism that is implicitly or explicitly antidevelopmental (compare with Giddens Reference Giddens2011; Bond Reference Bond2012; Middleton et al. Reference Middleton, O’Keefe and Moyo1993; Death Reference Death2010).

Essentially, therefore, sustainable development has become successfully mainstreamed, to the stage that world political and religious leaders across the spectrum profess at least rhetorical commitment to the objective at summits and in policy statements, even if their actions are less than fully aligned with or even directly contradictory to this aim. Having become a “sloganized” concept, for want of a better term – and with which all wish to be associated, since it is universally considered to be a good thing – sustainability has inevitably lost its original progressive (or even radical and subaltern) purchase in relation to poverty reduction, redistribution, and environmental justice, for instance. The Brundtland Report’s popularization of sustainable development came in response to a concern about limits to economic growth and associated environmental problems (WCED 1987), but there has always been disagreement over interpretation of the concept, including the extent to which it could be both a goal and a process, and how the economic, social, and environmental dimensions could be reconciled (WCED 1987; Simon Reference Simon1989). Even now, most official policies and programmes constitute examples of “weak” sustainable development, comprising modest reform or regulatory measures, accompanied by much “greenwashing” to ensure minimal change to business as usual. “Strong” sustainable development initiatives involving more substantive changes to current practices and lifestyles are generally associated with radical or progressive NGOs, grassroots movements, and the like, although some private firms are perhaps emerging as strong pioneers now that the green economy is seen increasingly to make business sense (for example, Zorrilla Reference Zorrilla2002; Simon Reference Simon2003; Weiss and Burke Reference Weiss and Burke2012).

Although it had earlier origins – and, indeed, one can usefully understand sustainability in the context of the longer perspective of urban history (Lumley and Armstrong Reference Lumley and Armstrong2004; Douglas Reference Douglas2013) – direct concern with applying sustainability principles to urban contexts gained rapid momentum after the UNCED summit in Rio in 1992. The specific instrument of urban sustainability intervention has been Local Agenda 21 (LA21), the urban component of Agenda 21, one of the two principal outcomes of the UNCED summit. Local Agenda 21 required local governments worldwide to formulate a sustainability plan for their towns and cities via a consultative process. The International Council for Local Environmental Initiatives (now known as ICLEI- Local Governments for Sustainability), an international NGO established in 1990, was commissioned to oversee implementation of LA21.

Inevitably, progress in urbanizing the sustainability agenda has varied greatly by world region and even within individual countries. Even in high-income countries, it initially proved quite challenging to gain the political will of elected councillors and to engage citizens beyond small, environmentally aware and already engaged minorities, while town planners and engineers grappled with the necessary revisions of planning and building codes and materials, infrastructural provision, and even funding models. Initially, at least, the geographical concentration of wealth; industry; energy-intensive, elite lifestyles; and emissions – and the vested interests they represent – in large urban areas were widely perceived to provide formidable obstacles to major change (for example, see Pugh Reference Pugh1996).

The international community also recognized that urban areas in low- and lower-middle income countries would be unable to implement LA21 unaided. Local resource and revenue constraints, a lack of perceived relevance, the immediate basic needs deficits that demanded priority attention, and the rural orientation of official development assistance programmes at the time represented a severe combination of constraints (see Pugh Reference Pugh2000). Consequently, ICLEI came to focus much of its attention on devising specific measures that would be appropriate and acceptable in such countries. The Human Settlements Programme of the London-based International Institute of Environment and Development, long headed by David Satterthwaite, has also played a consistent and invaluable role in engaged thinking, writing, and advocacy around urban sustainability challenges in the Global South, not least in influencing policy within UN-Habitat (for examples, see Satterthwaite Reference Satterthwaite1993, Reference Satterthwaite1997; Parnell Reference Parnell2016; see also Chapter 9). Satterthwaite’s (Reference Satterthwaite1997) paper remains important for clearly highlighting the fallacy that cities could become sustainable as urban islands, without sustainability in the wider territories and societies of which they form integral parts.

Programmes, organizations, and agendas developed under the banner of sustainability have grown steadily in number since the late twentieth century, and also across world regions and at multiple scales – from the level of the city or neighborhood to much broader global initiatives (Du Pisani Reference Du Pisani2007). UN-Habitat’s twin series of biennial publications, Global Report on Human Settlements, and State of the World’s Cities (and the latter’s continental companion reports) reflect how that agency’s thinking and programming on urban sustainability have evolved since the 1990s. Since its establishment in its current form in 2004, United Cities and Local Governments, the global association of subnational governments, has also played a prominent role in galvanizing urban sustainability actions, not least on climate change and the Urban Sustainable Development Goal, by its membership.

7.2 Urban Resilience: Evolution, Scope, Application, and Challenges

As with its counterpart term, “sustainability,” the application of the term “resilience” to socioecological systems gained prominence in relation to discussions of broader issues of conservation (Folke Reference Folke2006); both have been relatively recently applied to urban systems. Originally developed for application in fields as diverse as mathematics, engineering, materials science, and psychology (Olsson et al. Reference Olsson, Jerneck, Thoren, Persson and O’Byrne2015), researchers later applied resilience to ecological systems theory via mathematical models of population ecology (Bodin and Wiman Reference Bodin and Wiman2004). People later broadened the concept of resilience to include issues of human drivers and responses to ecological change, and eventually to the consideration of the adaptive management of coupled social-ecological systems. In contrast to sustainability, the idea of resilience places greater emphasis on issues of coupled system dynamics that can lead to nonlinear feedbacks and to slow, as well as abrupt, system changes. Resilience keeps at its core the acceptance and management of constant change, uncertainty, and “unknowability,” that is, the impossibility of achieving definite knowledge about system trajectories in complex social-ecological systems.

With the rapid acceleration of urban growth and its associated challenges, exacerbated by global environmental and climate change, resilience has become an increasingly visible term in discussions of urban planning and policy (Meerow et al. Reference Meerow, Newell and Stults2016). Resilience has found favor among widely divergent groups of actors, in large part because of the fuzziness and malleability of the term that enables it to act as a “boundary object” (Brand and Jax Reference Brand and Jax2007), representing different things to different sets of players. Yet the fuzziness of the term also generates challenges for operationalization of resilience planning, making it difficult to develop clear metrics and indicators of resilience that can be monitored over time. For instance, resilience, in the urban planning context, has been defined variously as a goal, as a desired outcome, and as a process, making progress difficult to grasp or measure.

Like sustainability, resilience is fundamentally a normative concept (Strunz Reference Strunz2012), although not always explicitly defined as such. Most discussions around urban sustainability implicitly assume resilience to be a desirable property, although this has been increasingly criticized by research that addresses problems such as urban inequity (such as Vale and Campanella Reference Vale and Campanella2005). In contrast to sustainability, the concept of resilience (and its counterpart, vulnerability) implies a greater emphasis on urban processes, including adaptive capacity to maintain dynamic equilibria and transformation to alternative desired social-ecological states. The goal of such planning has typically been geared towards achieving specific outcomes in response to global challenges, such as climate change (Romero-Lankao and Dodman Reference Romero-Lankao and Dodman2011). Some critics (for example, Olsson et al. Reference Olsson, Jerneck, Thoren, Persson and O’Byrne2015) argue that a fundamental dissonance exists in the way resilience is framed in the natural sciences, as a desirable system property, and in the social sciences, where the resilience of certain sociocultural norms that perpetuate inequity and power imbalances may be inherently problematic, requiring transformation and system change rather than resilience and the perpetuation of the status quo.

In recent years, the importance of resilience planning in an era of increased uncertainty has also gained ground, leading some scholars to propose the idea of cities that accept concepts of disturbance and change as fundamental to urban planning (Ahern Reference Ahern2011). Planning for resilience in an era of change requires the effective incorporation of typical characteristics of twenty-first century urban centers, including challenges of social, ecological, and economic diversity; balancing modularity with teleconnected networks (Seto et al. Reference Seto, Reenberg, Boone, Fragkias, Haase and Langanke2012); and redundancy with efficiency. A city with a diverse economy and reduced socioeconomic inequities can be expected to rebound more quickly from disasters as compared to a city with a specialized, narrow economic base with strong economic and social hierarchies, for example (Campanella Reference Campanella2006).

Finally, the protection and restoration of urban ecosystems is a historically neglected component of resilience planning that is now gaining significant traction across the globe (McPhearson et al. Reference McPhearson, Andersson, Elmqvist and Frantzeskaki2015). Cities with functioning, diverse, interconnected, multifunctional ecosystems exhibit greater resilience to natural disasters such as tornadoes and floods (Ahern Reference Ahern2011). Urban ecosystems thus provide cost-effective approaches to increasing the capacity of urban landscapes to deal with uncertainties and shocks that are typically more robust compared to anthropogenic, engineered solutions (Ernstson et al. Reference 160Ernstson, van der Leeuw, Redman, Meffert, Davis, Alfsen and Elmqvist2010). Further, given their multifunctionality, urban ecosystems provide diverse services in cities, acting to increase human well-being. Urban green and blue spaces constitute public goods that increase the quality of the environment (including air and water) and, as commons, provide food, fodder, and fuel wood to many urban residents, particularly in cities of the Global South. Thus, urban ecosystems increase the resilience of residents to food shortages in times of crisis, providing common pool resources accessed by all, but in particular used by disadvantaged sections of society, such as practitioners of ecosystem-based livelihoods and urban migrant laborers (Colding and Barthel Reference Colding and Barthel2013; Nagendra Reference Nagendra2016). Urban social movements, drawing on a wide base of urban cultural and social diversity, can be especially important in acting as a buffer against the problematic trends of privatization of urban green spaces witnessed in many cities. In this context, urban ecosystems connect the social and the ecological, providing an important motivation for social and community action that cuts across sociocultural and economic barriers, facilitates social entrepreneurship, and maintains feedback loops that contribute to the renewal of social capital in cities from Bogotá – where a gradient of ecological networks has been suggested as a way to connect wild habitats to built spaces (Andrade et al. Reference Andrade, Remolina and Wiesner2013) – to Cape Town, where a proposed urban biosphere reserve has the potential to address ecological goals of biodiversity conservation as well as social goals of inclusion and poverty alleviation (Krasny et al. Reference Krasny, Lundholm, Shava, Lee, Kobori, Elmqvist, Fragkias, Goodness, Güneralp, Marcotullio and McDonald2013).

7.3 Global Sustainability through Urbanization and Environmental Change

Whether or not it is an oxymoronic concept, as often claimed, sustainability pervades today’s politics, research, and practice in efforts to meet human development goals without compromising the resources and environment that sustain the economic goods and services needed to support them (see Section 7.1). However, in reality, the three pillars that underpin traditional sustainability thought (economic, social, and environmental) are rarely approached together, resulting in fragmented research perspectives and policies. Efforts have tended to focus on economic and environmental dimensions, with less focus on the social; however, more holistic interpretations of sustainability are emerging that focus on urbanization and cities as key components of this process (see Bina Reference Bina2013; Seto et al. Reference Seto, Reenberg, Boone, Fragkias, Haase and Langanke2012, Pickett et al. Reference 161Pickett, Cadenasso and McGrath2013; Steele et al. Reference Steele, Mata and Fuenfgeld2015). “Ecosystem services,” “well-being,” and “low-carbon” are just some of the new ideas and concepts that have moved the sustainable development discourse forward (Bina Reference Bina2013), increasingly in the urban context.

Moreover, the importance of a better understanding of urbanization processes, interactions, and feedbacks with other systems for global sustainability has become increasingly clear over the last decade. Urban environmental change research has expanded the place-based approach associated with traditional urban studies to address the temporal and spatial interactions that urbanization, a social-ecological process itself, has with other biophysical systems (Sánchez-Rodríguez et al. Reference Sánchez-Rodríguez, Seto, Simon, Solecki, Kraas and Laumann2005; Seto et al. Reference Seto, Solecki and Griffith2016). Knowledge and actions that deal with these interactions are critical for a modern agenda towards a more equitable and healthy world. Any hope of achieving global sustainability in holistic terms requires that we understand the connections between urban processes, natural resources, land change, human migration, financial flows, and technology transfers and innovation with environmental change in this broader context (Seto et al. Reference Seto, Reenberg, Boone, Fragkias, Haase and Langanke2012; Pincetl Reference Pincetl, Seto, Solecki and Griffith2016).

The next section briefly reviews salient areas within urbanization and global environmental change (GEC) research and practice that have added to sustainability and resilience thinking over the last decade.

7.4 Urban Adaptation and Mitigation within Sustainability and Resilience

The connections between urbanization and GECs, including the more frequent consequences of climate-related disasters and greater climate uncertainty, have increased the need to climate-proof and adapt urban areas to potential risks (Richards and Bradbury Reference Richards and Bradbury2007; Thornbush et al. Reference Thornbush, Golubchikov and Bouzarovski2013). Concerned parties have traditionally focused on the impacts in rural areas, since damage therein was often more extreme, causing concern over potential damage to natural resources and disruption of agricultural systems (Birkmann et al. Reference Birkmann, Garschagen, Kraas and Quang2010). However, attention to urban areas grew rapidly following numerous weather extremes and reports thereafter, highlighting existing gaps in our understanding of the unique urban challenges related to adaptation (Commission on Climate Change and Development 2009). These challenges are attributed to cities’ regional and global connectivity and their diverse characteristics, including their population size and density, stage within their respective development processes, and variances in hard and soft infrastructure. Particularly within low- and middle-income countries, where cities are often rapidly urbanizing, exposure to disease and other health problems became cause for deep concern and inquiry into urban coping capacity in the context of nonexistent or substandard development infrastructure, such as weak water and sanitation systems; high concentrations of urban poverty, including slums and informal settlements; and weak social and political institutions (Birkmann et al. Reference Birkmann, Garschagen, Kraas and Quang2010).

In the last decade, as more frequent and often more severe occurrences of extreme events – including intense rains and flooding, hurricanes and storm surges, and heat waves – persisted, so did the emergence of urban adaptation responses, prompting research on multiscale responses within urban areas (that is, at the individual, neighborhood, community, or city levels) (Bicknell et al. Reference Bicknell, Dodman and Satterthwaite2009). A number of research advancements followed, including the identification and assessment of the diversity of actions and comprehensive adaptation strategies in cities across regions (Carmin et al. Reference Carmin, Nadkarni and Rhie2012), the urban governance and institutional capacities to pursue adaptation (Anguelovski and Carmin Reference 159Anguelovski and Carmin2011; Aylett Reference Aylett2015), and more nuanced understandings of drivers of vulnerability and risk in various urban populations (Garschagen and Romero Lankao Reference Garschagen and Romero Lankao2015). In the latter case, resilience theory has provided a lens or tool to approach climate change adaptation and to manage social-ecological systems (Garschagen Reference Garschagen2011; Section 7.2). Today, “resilience” is often used in the same manner as “adaptation”; that is, building urban resilience often implies building urban adaptive capacity to stresses and shocks from climatic events. Efforts to create urban resilience “toolkits” through disciplinary integration have grown in recent years, along with attempts to codesign comprehensive city strategies with the involvement of multiple stakeholders (Solecki et al. Reference 162Solecki, Leichenko and O’Brien2011).

On the other side of the coin, mitigation actions, like adaptive actions, are often implemented locally in cities as part of national efforts to reduce GHG emissions. In aggregate, aggressive urban mitigation actions could have profound global impacts (Seto et al. Reference Seto, Dhakal, Bigio, Blanco, Delgado, Dewar, Edenhofer, Pichs-Madruga, Sokona, Farahani, Kadner and Seyboth2014). Since the 1992 Kyoto Protocol and events thereafter, such as Rio+20 and the 2015 UNFCCC summit in Paris (COP 21) (see Section 7.1), many nations have committed to reducing their emissions footprints as part of broader sustainability efforts. This has translated given impetus to cities, where the majority of emissions occur and where the majority of efforts to curb them are undertaken. Many cities have created baseline GHG emissions inventories and sustainability portfolios that include consumption- and production-based efforts to reduce emissions. Some of these efforts include municipal and residential emissions reductions through improving energy efficiencies in built infrastructure, encouraging alternative modes of transportation, and increasing efficiencies in water treatment and distribution; promoting urban food production, composting and recycling, and reduction in water use; and integrating green infrastructure and tree planting into the urban landscape for carbon sequestration. These and myriad other efforts and innovations have been tailored to cities’ individual needs and cultural, geographical, and economic characteristics (Seto et al. Reference Seto, Dhakal, Bigio, Blanco, Delgado, Dewar, Edenhofer, Pichs-Madruga, Sokona, Farahani, Kadner and Seyboth2014; Simon Reference Simon and Simon2016 ). “Low-carbon” cities are a new trend found in the discourse of mitigation that people are employing in urban environments worldwide. Such cities are increasingly being touted as having capabilities to transform sociotechnical and governance systems (Bulkeley et al. Reference Bulkeley, Castán Broto, Hodson and Marvin2011) through the redesign and reconfiguration of energy infrastructures. Personnel at ICLEI, the World Bank, and the World Wildlife Fund in China, among others, for example, are pursuing a low-carbon agenda wherein “a low-carbon city recognizes its responsibility to act. It pursues a step-by-step approach towards carbon neutrality, urban resilience and energy security, supporting an active green economy and stable green infrastructure” (ICLEI 2016). Such actions represent what some refer to as the emergence of a low-carbon urban transition. However, both actual progress and the extent to which urban adaptation or resilience and carbon reduction efforts are integrated with broader development goals are unclear and remain in need of further research.

7.5 Integrating Adaptation, Mitigation, and Urban Development for an Equitable Future

Urban system complexity and dynamics across scales are not new to the understanding of urban sustainability, but approaches often continue to oversimplify the interactions of urban systems with other socioeconomic, geopolitical, and environmental processes. Urbanization and GEC research foster multidimensional perspectives that transcend the short term and cross spatial scales, but they would benefit from further disciplinary integration to build new theories and methods. Such knowledge, for example, would be useful for cities to better operationalize adaptation to and mitigation of the negative impacts of climate and other environmental change, and could strengthen the social dimension in the sustainability narrative (Sánchez-Rodríguez Reference Sánchez-Rodríguez, Martine, McGranahan, Montgomery and Fernández-Castilla2008).

As a term, sustainability has often been used to bridge mitigation and adaptation; it has been well documented that to achieve long-term urban sustainability, efforts to promote urban resilience to climate change that are inclusive of both adaptation and mitigation strategies must be bundled with broader development policies and plans (Leichenko Reference Leichenko2011). Research continues to stress the importance of integrating the two often conceptually distinct strands of sustainability and mitigation/adaptation (Golubchikov Reference Golubchikov2011; Dodman Reference Dodman2009; Thornbush et al. Reference Thornbush, Golubchikov and Bouzarovski2013), as findings show that adaptation actions (such as greater use of air conditioning as urban temperatures rise) can sometimes have an inverse effect on mitigation (a proportional higher energy use and GHG emissions) – known as maladaptation.

The idea that integral components of long-term urban sustainability and global sustainability include justice and equity is emerging within urban responses to climate change. This shift arises from our recognition that, first, the responsibility for climate change is not equally distributed, meaning that some nations and cities are doing more with respect to mitigation and reducing emissions than others. Second, climate change does not affect all people equally or in the same ways, as some populations, and groups within populations, are more vulnerable due to historically rooted, political-economic relationships and processes that are not beneficial for all (Steele et al. Reference Steele, Mata and Fuenfgeld2015). Recent inquiry into the relationship between climate justice principles in urban policy development has found remarkable differences in both mitigation and adaptation policies in terms of distributional and procedural justice in cities of both the Global North and South (Bulkeley et al. 2012).

Further research into vulnerability, equity, and social justice could help frame policies with fair or just outcomes through a greater understanding of existing inequality or where/how future inequality might occur. Resilience theory that incorporates governance, institutional processes, and organizational structures could add to the understanding of the existing strengths and constraints of governments, institutions, and organizations in different sociocultural contexts, yielding more successful integration of concepts of resilience and transformation in sectoral policies, urban planning, and design (Garschagen Reference Garschagen2011). Emerging eco-social justice perspectives are also broadening the sustainability agenda by increasing attention to the needed integration between environmental change, social change, human vulnerability or resilience, and biodiversity loss in the city (Steele et al. Reference Steele, Mata and Fuenfgeld2015).

Ultimately, the call to transform our cities and to push the “urbanization transition” along more sustainable trajectories is urgent, but challenging. To be successful, it requires understanding context and leverage points for change, which will require continued analysis of urbanization processes (including drivers, interactions, and outcomes) that occur at multiple scales (see Part III, “Urban Transformations to Sustainability”). Research approaches that frame urbanization as an opportunity for global sustainability, wherein principles of equity and justice are centralized, hold promise for achieving such transformations.

References
Ahern, J. (2011). From Fail-Safe to Safe-To-Fail: Sustainability and Resilience in the New Urban World. Landscape and Urban Planning 100(4): 341–43.
Andrade, G.I., Remolina, F., and Wiesner, D. (2013). Assembling the Pieces: A Framework for the Integration of Multi-Functional Ecological Main Structure in the Emerging Urban Region of Bogotá, Colombia. Urban Ecosystems 16: 723739.
Anguelovski, I., and Carmin, J. (2011). Something Borrowed, Everything New: Innovation and Institutionalization in Urban Climate Governance. Current Opinion in Environmental Sustainability 3: 169175.
Aylett, A. (2015) Institutionalizing the Urban Governance of Climate Change Adaptation: Results of an International Survey, Urban Climate 14(1) December: 416
Bicknell, J., Dodman, D., and Satterthwaite, D. (eds.). (2009). Adapting Cities to Climate Change: Understanding and Addressing the Development Challenges. London: Earthscan.
Bina, O. (2013). The Green Economy and Sustainable Development: An Uneasy Balance? Environment and Planning C: Government and Policy 31: 10231047.
Birkmann, J., Garschagen, M., Kraas, F., and Quang, N. (2010). Adaptive Urban Governance: New Challenges for the Second Generation of Urban Adaptation Strategies to Climate Change. Sustain Science 5(2):185206
Bodin, P., and B. Wiman. (2004). Resilience and Other Stability Concepts in Ecology: Notes on Their Origin, Validity, and Usefulness. ESS Bulletin 2.2: 3343.
Bond, P. (2012) Politics of Climate Justice: Paralysis Above, Movement Below. Durban: UKZN Press.
Brand, F.S., and Jax, K. (2007). Focusing the Meaning (s) of Resilience: Resilience as a Descriptive Concept and a Boundary Object. Ecology and Society 12: 23. www.ecologyandsociety.org/vol12/iss1/art23/
Bulkeley, H., Carmin, J., Castán Broto, V., Edwards, G.A.S., and Fuller, S. (2013). Climate Justice and Global Cities: Mapping the Emerging Discourses. Global Environmental Change, 23(5): 914925. DOI: 10.1016/j.gloenvcha.2013.05.010.
Bulkeley, H., Castán Broto, V., Hodson, M., and Marvin, S. (2011). Cities and Low Carbon Transitions. Abingdon, Oxon: Routledge.
Campanella, T.J. (2006). Urban Resilience and the Recovery of New Orleans. Journal of the American Planning Association 72(2): 141146.
Carmin, J., Nadkarni, N. , and Rhie, C. (2012). Progress and Challenges in Urban Climate Adaptation Planning: Results of a Global Survey. Cambridge, MA: DUSP/MIT.
Carson, R. (1962). Silent Spring. New York: Houghton Mifflin [later also Penguin Modern Classic]
Colding, J., and Barthel, S. (2013). The potential of ‘Urban Green Commons’ in the resilience building of cities. Ecological Economics 86:156–66.
Commission on Climate Change and Development (2009). Governance Gaps in Closing the Gaps: Disaster Risk Reduction and Adaptation to Climate Change in Developing Countries, Commission on Climate Change and Development, Stockholm: Commission on Climate Change and Development, pp. 2433.
Death, C. (2010). Governing Sustainable Development. London and New York: Routledge.
Dodman, D. (2009). Blaming Cities for Climate Change? An Analysis for Urban Green-House Gas Emissions Inventories. Environment and Urbanization, 21(1): 185201.
Douglas, I. (2013). Cities: An Environmental History. London and New York: I.B. Tauris.
Du Pisani, J.A. (2007). Sustainable Development – Historical Roots of the Concept, Environmental Sciences, 3(2): 8396, DOI:10.1080/15693430600688831
Ernstson, H., van der Leeuw, S.E., Redman, C.L., Meffert, D.J., Davis, G., Alfsen, C., and Elmqvist, T. (2010). Urban Transitions: On Urban Resilience and Human-Dominated Ecosystems Ambio 39(8): 531545.
The Ecologist, (1972). A Blueprint for Survival. London: The Ecologist Magazine.
Folke, C. (2006). Resilience: The Emergence of a Perspective for Social–Ecological Systems Analyses. Global environmental change 16(3): 253267.
Garschagen, M., (2011). Resilience and Organisational Institutionalism from a Cross-Cultural Perspective: An Exploration Based on Urban Climate Change Adaptation in Vietnam. Natural Hazards (2013) 67: 2546 DOI 10.1007/s11069-011–9753–4.
Garschagen, M., and Romero Lankao, P. (2015). Exploring the relationships between urbanization trends and climate change vulnerability. Climatic Change, 133 (1): 3752. doi:10.1007/s10584-013–0812-6.
Giddens, A. (2011). The Politics of Climate Change, 2nd edn. Cambridge: Polity.
Golubchikov, O. (2011). Climate Neutral Cities: How to Make Cities Less Energy and Carbon Intensive and More Resilient to Climatic Challenges. Geneva: United Nations Economic Commission for Europe (UNECE).
ICLEI (2016, March 4). Low-Carbon City.
Krasny, M.E., Lundholm, C., Shava, S., Lee, E., and Kobori, H. (2013). Urban Landscapes as Learning Arenas for Biodiversity and Ecosystem Services Management, in Elmqvist, T., Fragkias, M., Goodness, J., Güneralp, B., Marcotullio, P.J., and McDonald, R.I., et al. (eds.) Urbanization, Biodiversity and Ecosystem Services: Challenges and Opportunities. The Netherlands: Springer, pp. 629664.
Leichenko, R. (2011). Climate Change and Urban Resilience. Current Opinion in Environmental Sustainability. 3: 164168.
Lumley, S., and Armstrong, P. (2004). Some of the Nineteenth Century Origins of the Sustainability Concept, Environment, Development and Sustainability 6(3): 367378.
McPhearson, T., Andersson, E., Elmqvist, T., and Frantzeskaki, N. (2015). Resilience of and through Urban Ecosystem Services. Ecosystem Services 12: 152156.
Meadows, M., Meadows, M., Randers, J., and Behrens, W. (1972). The Limits to Growth. London: Pan Books.
Meerow, S., Newell, J.P., and Stults, M. (2016). Defining Urban Resilience: A Review. Landscape and Urban Planning 147: 3849.
Middleton, N., O’Keefe, P., and Moyo, S. (1993). Tears of the Crocodile: from Rio to reality in the Developing World. London: Pluto.
Nagendra, H. (2016). Nature in the City: Bengaluru in the Past, Present, and Future. Delhi: Oxford University Press.
Olsson, L., Jerneck, A., Thoren, H., Persson, J. and O’Byrne, D. (2015). Why Resilience Is Unappealing to Social Science: Theoretical and Empirical Investigations of the Scientific Use of Resilience. Science Advances 1(4), p.e1400217, DOI: 10.1126/sciadv.1400217.
Parnell, S. (2016). Defining a Global Urban Development Agenda, World Development 78: 529540. http://dx.doi.org/10.1016/j.worlddev.2015.10.028.
Pickett, S.T.A., Cadenasso, M.L., McGrath, M. (eds.) (2013). Resilience in Ecology and Urban Design: Linking Theory and Practice for Sustainable Cities. New York: Springer.
Pincetl, S. (2016). Urban Precipitation: A Global Perspective, in K.C. Seto, W.D. Solecki, and C.A. Griffith (eds.) The Routledge Handbook of Urbanization and Global Environmental Change. London and New York: Routledge, pp. 152168.
Pugh, C. (ed.) (1996). Sustainability, the Environment and Urbanization. London: Earthscan.
Pugh, C. (ed.) (2000). Sustainable Cities in Developing Countries. London: Earthscan.
Richards, J., and Bradbury, S. (2007). Sustainability is not only about carbon emissions. Building Engineer 82(9): 40.
Romero-Lankao P, and Dodman D. (2011). Cities in Transition: Transforming Urban Centers from Hotbeds of GHG Emissions and Vulnerability to Seedbeds of Sustainability and Resilience: Introduction and Editorial Overview. Current Opinion in Environmental Sustainability 3(3): 113120.
Sánchez-Rodríguez, R. (2008). Urban Sustainability and Global Environmental Change: Reflections for an Urban Agenda in G. Martine, G. McGranahan, M. Montgomery and R. Fernández-Castilla (Eds.), The New Global Frontier Urbanization, Poverty and Environment in the 21st Century. London and Sterling, VA: Earthscan, pp. 149164.
Sánchez-Rodríguez, R., Seto, K. C., Simon, D., Solecki, W. D., Kraas, F., and Laumann, G. (2005). Science Plan Urbanization and Global Environmental Change Project (IHDP Report No. 15). Bonn: International Human Dimensions Programme on Global Environmental Change.
Satterthwaite, D. (1993). The Impact on Health of Urban Environments. Environment and Urbanization, 5 (2): 87111.
Satterthwaite, D. (1997). Sustainable Cities or Cities That Contribute to Sustainable Development? Urban Studies 34 (10): 16671691.
Seto, K.C., Solecki, W.D., and Griffith, C.A. (eds.) (2016). The Routledge Handbook of Urbanization and Global Environmental Change. London and New York: Routledge.
Seto K.C., S. Dhakal, A. Bigio, H. Blanco, G.C. Delgado, D. Dewar, et al. (2014). Human Settlements, Infrastructure and Spatial Planning in Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, et al. (eds.) Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.
Seto, K.C., Reenberg, A., Boone, C.G, Fragkias, M., Haase, D., Langanke, T., et al. (2012). Urban Land Teleconnections and Sustainability. Proceedings of the National Academy of Sciences, 109(20): 76877692.
Simon, D. (1989). Sustainable Development: Theoretical Construct or Attainable Goal? Environmental Conservation 16(1): 4148.
Simon, D. (2003). Dilemmas of Development and the Environment in a Globalising World: Theory, Policy and Praxis, Progress in Development Studies 3(1): 541.
Simon, D. (2016) Green cities: from tokenism to incrementalism and transformation, in Simon, D. (ed.) Rethinking Sustainable Cities: Accessible, green and fair. Bristol: Policy Press.
Solecki, W., R. Leichenko, and K. O’Brien. (2011). Climate Change Adaptation Strategies and Disaster Risk Reduction in Cities: Connections, Contentions, and Synergies. Current Opinion in Environmental Sustainability 2011 (3): 35141.
Steele, W., Mata, L., and Fuenfgeld, H. (2015). Urban climate Justice: Creating Sustainable Pathways for Humans and Other Species. Current Opinion in Environmental Sustainability 2015(14): 121126.
Strunz, S. (2012). Is Conceptual Vagueness an Asset? Arguments from Philosophy of Science Applied to the Concept of Resilience. Ecological Economics 76: 112118.
Thornbush, M., O. Golubchikov, and S. Bouzarovski (2013) Sustainable Cities Targeted by Combined Mitigation–Adaptation Efforts for Future-Proofing. Sustainable Cities and Society, 9: 19.
Vale, L.J., and Campanella, T.J. (2005). The Resilient City: How Modern Cities Recover from Disaster. New York: Oxford University Press.
Ward, B., and Dubos, R. (1972). Only One Earth. Harmondsworth: Penguin.
Weiss, T. and Burke, M.J. (2012). Legitimacy, Identity and Climate Change: Moving from International to World Society? Third World Quarterly 32(6): 10571072.
World Commission on Environment and Development (WECD) (1987). Our Common Future. Oxford: Oxford University Press.
Zorrilla, C. (2002). Reflections on Sustainability from the Trenches. Development 45(3): 5458.

Chapter 8: Indicators for Measuring Urban Sustainability and Resilience

David Gómez-Álvarez , and Eduardo López-Moreno , with Edgardo Bilsky , Karina Blanco Ochoa , and Efrén Osorio Lara
8.1 Introduction

Due to the unprecedented growth and emergence of urban areas around the world, urbanization is one of the most significant trends of the twenty-first century. By 2030, 60 percent of the world’s population is expected to live in cities, and by 2050, nearly 70 percent (UN-Habitat 2015). The acceleration of the urban phenomenon poses unexpected and motley challenges for contemporary societies, which are in need of new metrics to measure the dimensions circumscribing today’s urbanization.

Urban indicators offer an overall snapshot of the city in order to determine intra-urban variations and areas that require greater attention from policy-makers. In terms of policy use and analysis, urban indicators play a key role in creating good policies for three main reasons: first, they highlight relevant issues that should be considered throughout the design and implementation of public policies; second, they are effective tools for policy-makers to set concrete targets for urban policies (OECD 2000); and third, they can help to assess the performance of the policies implemented by local, regional, and national authorities.

New metrics require a shift in the conceptualization and understanding of city progress, moving well beyond traditional economic metrics towards more comprehensive and holistic perspectives that position both human and environmental well-being at their cores. The shortcomings and inadequacies of conventional economic indicators as development standards reveal that urban well-being can no longer be equated with economic progress. Thus, a paradigmatic transformation that moves away from this traditional perspective towards new measurements of development becomes fundamental.

This chapter addresses the importance and value of urban indicators and their contribution to the design of better informed, sound policies. It briefly reviews the evolution of different developments in measuring and understanding cities, demonstrating that models based on classical economics have been insufficient. The New Urban Agenda, the Paris Agreement, and the 2030 Development Agenda – embodied in the urban Sustainable Development Goal (SDG) 11 (see Chapters 7 and 9) – require the introduction of new and innovative sets of indicators. We must use such tools in analyzing current urbanization patterns through multidimensional approaches to improve the difficult task of managing cities and to refine policy-making in accordance with the SDGs. This work seeks to demonstrate the value of urban data as an essential tool for the formulation of better informed policies at local, national, and international levels. Such data provide useful information that allows for strategic decision-making oriented towards the mitigation of both direct and indirect consequences of urbanization in diverse contexts and city sectors.

The next section presents the evolution of measurement tools, emphasizing the main characteristics and contributions of each generation of indicators. Thereafter, the chapter provides a discussion of the importance of local and regional government empowerment for meeting the 2030 Development Agenda and concludes by emphasizing the need for greater efforts to design better measurement instruments to fill the gaps in existing sets of urban indicators.

8.2 The Need for Urban Indicators

In many parts of the world, urban phenomena and processes of urbanization remain poorly documented, understood, and measured. Many cities around the world are suffering from inadequate urban data, leading to an information crisis that is undermining their capacity to develop effective urban policies (Muhammad Reference Muhammad, Pereira and Komoo2001). Too often, the existing data that cities have are not adequately detailed, documented, or harmonized, or are not available and accessible for critical issues relating to urban growth and development.

Further, numerous cities lack a sustained or systematic appraisal of urban problems, such as loss of public space, environmental impact, and land consumption. Due to the inadequacy of existing measurement tools along with urban data deficiencies in these cities, there is little internal appreciation of what their own policies and programs are achieving (Muhammad Reference Muhammad, Pereira and Komoo2001). This impedes appropriate monitoring and assessment, as well as an accurate formulation of public policies. Even in countries with a strong monitoring culture and data collection practices, the development of a coherent and reliable set of indicators for urban areas is not a simple task (Wong Reference Wong2006).

The arrival of the 2030 Development Agenda, along with the SDGs, marks a turning point with great potential to fill the urban data vacuum in the upcoming years. According to the monitoring framework proposed by the “Urban SDG,” embodied in SDG 11, which calls on us to “make cities and human settlements inclusive, safe, resilient and sustainable,” accurate urban data and metrics enable cities to make decisions about the best policies and means to track urban progress, while also documenting a city’s performance in terms of policy outcomes and achievements (UN-Habitat 2015). The assessment and monitoring of the effects of urban dynamics are frequently used as tools in urban planning for guaranteeing a more sustainable development path. Therefore, a monitoring framework oriented towards improving the difficult task of administering and managing cities in accordance with the 2030 Development Agenda is a fundamental precondition to meeting the SDG targets.

Furthermore, according to the Organisation for Economic Co-operation and Development, or OECD, “Indicators are needed to monitor and evaluate the impact of compact city policies. They will make it possible to benchmark progress and establish future goals. In particular, internationally comparable indicators can help policy makers analyze their policy performance from a wider perspective and improve their policy actions” (OECD 2012: 80). In this regard, urban indicators are crucial tools for providing objective evidence of prevailing conditions and changes over time (Muhammad Reference Muhammad, Pereira and Komoo2001) associated with complex urban phenomena, yet they must also be able to evolve as the world becomes more urbanized. It will become increasingly important to develop a greater amount of meaningful urban indicators that aim for a broader depiction of urban dynamics.

8.3 The Evolution of Measuring and Monitoring Cities: What Has Been Done?

To date, there have been several attempts to measure a city’s progress towards sustainable urban development. Diverse actors and stakeholders working at different scales have immersed themselves in the difficult task of defining a set of indicators covering the totality of the urban picture in order to assess the state of urban development across nations. However, due to the increasing need to measure a broader conception of human and societal well-being, both global and local efforts to develop urban indicators have moved beyond economic growth as a metric for progress towards a comprehensive and integral understanding of human and ecological welfare. This has meant a change from a national income accounting system to a more localized and people-centered approach (Wong Reference Wong2014).

The initial attempts to measure and assess urban development through standardized metrics were carried out by supranational organizations such as the World Bank, the UN, and the OECD, among others. They focused on developing isolated and sectoral indicators that would monitor and collect information from the national level, leading to an incomplete depiction of urban dynamics. More recently, national efforts through domestic statistical agencies have also collected data at the national and subnational levels within certain countries. Both public and private subnational and local efforts have also collected data in a decentralized fashion, which, under certain circumstances, could be more reliable.

In the context of the Post-2015 Development Agenda, former UN Secretary General Ban Ki-moon pointed out that we need to “look beyond the confines of economic growth that have dominated development policy and agendas for many years” (UN-Habitat 2013: iii). Current urban indicators should “examine how cities can generate and equitably distribute the benefits and opportunities associated with prosperity, ensuring economic well-being, social cohesion, environmental sustainability, and a better quality of life in general” (ibid.). In addition, the OECD has emphasized that “the measurement of sustainable development requires drawing together indicators from the three dimensions of sustainable development, the economy, the environment and society. The two primary aims are to form a coherent picture of sustainable development trends and to provide information that is relevant to policy questions” (OECD 2000: 7).

In this spirit, during the 2016 World Economic Forum in Davos, the leaders of international organizations and institutions that have traditionally relied on economic metrics to measure development argued that GDP is not a good way to assess national economic health and that a new measure is urgently required which better assesses the dynamics that have emerged as a result of urbanization processes. (Thomson Reference Thomson2016). This echoes longstanding critiques by social activists, progressive economists, and some international agencies. The current GDP-based approach emerged as the result of a long process of empirical and conceptual evolution, which began early in the twentieth century when Simon Kuznets introduced GDP in the 1930s. Since then, the design and the development of concepts, metrics, and monitoring frameworks have been a constant around the world.

After analyzing the main urban indicators, one can distinguish three main generations in their evolution over time. These generations attempt to quantify a greater number of urban dynamics components in order to better measure and understand complex urban phenomena, each conceived from diverse contexts, frameworks, and international consensus regarding the conceptualization of development. The first generation is based on classical economic indicators as a metric for city progress; the second generation is characterized by the use and design of thematic indicators based on a broader understanding of development, which is embodied in the Millennium Development Goals, or MDGs; the third generation corresponds to the current set of indicators that address more holistically and comprehensively the new conceptualization of city prosperity contained in the 2030 Development Agenda and the SDGs (Figure 8.1).

Figure 8.1 The evolution of urban indicators

It is important to emphasize that their evolution through successive generations does not mean that indicators from the first and second generations are now useless, obsolete, or invalid due to their antiquity. What this evolution demonstrates is ongoing progress in the increasing complexity and improvement of urban indicators to offer a broader approach to urban dynamics. Indeed, first-generation indicators continue to be used in different contexts, not least as updates to long time series, and demand remains for some data used in them. Not all are amenable to incorporation into newer generation indicators, but having some basic data is preferable to none. In Sections 8.38.5, we will explain in further detail each generation of indicators and their respective main characteristics. We will also provide some examples of urban indicators that best illustrate each generation.

8.4 First Generation of Urban Indicators

Over most of the past century, our understanding of city dynamics was very limited, due in part to data sparseness and deficiencies. The main indicators to measure progress and development were economic metrics with a macro-perspective, which only addressed three main dimensions of the city: the economic dimension, through GDP; the demographic dimension, through population count; and the size dimension, through city sprawl. In this manner, people measured cities using isolated indicators that reflected only a small piece of the city puzzle. Even basic attempts to understand urban dynamics through population size are problematic, in part because of the diverse institutions carrying them out. Urban indicators that emerged within this first generation illustrate the urban reality with an atomistic, unidimensional, and simplistic approach. Because these indicators were based on economics, they were not useful for explaining subjective urban issues such as well-being in terms of quality of life. Furthermore, the monitoring frameworks of this generation lack local contextualization. They have a generic and objective quantitative nature, and they serve only for comparative exercises.

The first attempt to develop urban indicator sets by a supranational organization occurred during the 1960s when the World Bank launched the first World Development Indicators Series, which aimed to monitor city achievements by the international development goals of that time (Wong Reference Wong2006, Reference Wong2014). These series continue to be published annually, with each year’s report focusing on a specific aspect of development (World Bank 2016) to reflect development’s increasing breadth and complexity.

8.5 Second Generation of Urban Indicators

The arrival of the new millennium marked a watershed moment in assessing cities. As the world became increasingly urbanized and global challenges more complex – or, at least, were becoming recognized as such – the year 2000 provided a unique opportunity to reverse the unsustainable evolution of cities. Great enthusiasm and optimism surrounded the introduction of the MDGs, a suite of eight goals that established measurable, universally agreed-upon objectives oriented towards the achievement of progress in “developing countries” in areas such as income, poverty, access to improved sources of water, primary school enrollment, and child mortality (UNDP 2016).

However, the arrival of the second generation of urban indicators in 1992, the year when Agenda 21 was launched at the United Nations Conference on Environment and Development, or UNCED (see Chapter 7), preceded the MDG innovation. Authors of the Agenda stressed that as “the need for information arises at all levels, from that of senior decision-makers at the national and international levels to the grass-roots and individual levels” (UN 1992), it is crucial to bridge data gaps and improve information availability in order to ensure better decision-making based on increasingly sound information. As a result, the sectoralization of indicator sets, linked to the narrowing of aims to target specific policy questions (OECD 2000), and the application of greater attention to local dimension of cities became the most visible trends among the second generation of urban indicators. These trends necessitated a shift from the conventional macroeconomic perspective towards a broader approach to urban dynamics that included new dimensions, themes, and methods to measure and assess city performance.

During this period, people realized that cities could no longer be measured and understood as the sum of income, population, and city sprawl; the accelerated urbanization phenomenon required the introduction of new dimensions into the city equation in order to obtain a broader picture of urban dynamics. Thus, the indicator sets that emerged paid greater attention to human and ecological well-being. Some examples of international urban indicator sets that clearly illustrate the main characteristics and the approach of this generation are The Global City Indicators Program, designed by the World Bank; The Cities Data Book, developed by the Asian Development Bank; and Global Urban Indicators and Urban Governance Index, both created by UN-Habitat (Box 8.1).

Box 8.1 International urban indicator sets of the second generation

The Global City Indicators Program (GCIP) is a decentralized, city-led initiative that enables cities to measure, report on, and improve their performance and quality of life, facilitate capacity building, and share best practices through an easy-to-use web portal. The GCIP aims to help cities monitor performance and quality of life by providing a framework to facilitate consistent and comparative collection of city indicators. The GCIP also aims to enhance city government accountability to the public and has a strong focus on the performance of cities’ public services, including those for water supply, wastewater, and solid waste. The World Bank initiated the GCIP in 2008 and is now run by the Global City Indicators Facility, based at the University of Toronto, which oversees the development of indicators and helps cities to join the program. As of 2015, 255 cities across 82 countries were participating in the program, up from some 125 just four years earlier.

The Cities Data Book (CDB) is a comprehensive set of urban indicators formulated in 2001 by the Asian Development Bank to improve urban management and performance measurement. The broad categories of the environment-related indicators are the same as those found in other indicator sets (water, wastewater, solid waste, noise, and so forth), but the CDB’s indicators go into greater detail on specific concerns addressed by this institution (for example, the wide range of methods of sewage disposal in Asian cities).

The Global Urban Indicators (GUI) database was established to monitor progress on the implementation of the UN-Habitat Agenda. The database covers 236 cities across the globe, including those from the OECD countries. As a whole, however, the indicators focus strongly on the concerns of cities in developing countries. In 1996 and 2001, the program produced two main databases, GUI Databases I and II, containing data for 1993 and 1998, respectively; these were presented at the Habitat II and Istanbul +5 conferences. The next Global Urban Indicators database (III) will continue to address the key Habitat Agenda issues, with a specific focus on the MDGs and, particularly, Target 11 on the improvement of slum dwellings. Altogether, there are 42 key and complementary indicators in the GUI dataset in total.

Websites:

Source: OECD (2012: 85–86), citing OECD (2011), “Urban Environmental Indicators for Green Cities: A Tentative Indicator Set,” paper presented to the Working Party on Environmental Information, internal working document.
8.6 Third Generation of Urban Indicators

Since the 2030 Development Agenda launched in September 2015, a strong commitment to achieving a more holistic form of urban prosperity and development emerged among the majority of nations around the world (Wong Reference Wong2014). A shift in the paradigms of development, subjective well-being, and city prosperity towards a broader, multidimensional understanding of these aspects led to the arrival of a third generation of urban indicators. The publication of the State of the World’s Cities 2012/2013: Prosperity of Cities (UN-Habitat 2013) marked an inflection point between the second and third generations. It triggered significant discussion among the international community that translated into the introduction of a new, multidimensional conceptualization of city prosperity, materialized in the City Prosperity Index, or CPI.

The conception of the CPI comes with a strong assertion of the vitality and transformative dynamics of cities, and thus their importance in what is now the urban age (UN-Habitat 2013, cited in Wong Reference Wong2014), for new types of cities that achieve a sustainable path of development. In this regard, SDG 11 recognizes urbanization as a transformative force for development which, if effectively steered and deployed, can help the world to overcome many of its major global challenges (UN-Habitat 2015). City prosperity is currently understood in terms of a more integrated and holistic approach than in the past, which seeks to promote collective well-being, public goods, and overcoming the dangers posed to cities in a context of rapid urbanization. The CPI estimates prosperity through different interlinked dimensions: productivity, infrastructure development, quality of life, equity and social inclusiveness, environmental sustainability, and governance. Arriving at a third generation of urban indicators such as the CPI meant

a fresh approach to prosperity, one that is holistic and integrated and which is essential for the promotion of a collective well-being and fulfillment of all. This new approach does not only respond to the crises by providing safeguards against new risks, but it also helps cities to steer the world towards economically, socially, politically and environmentally prosperous urban futures.

(Clos, quoted in UN-Habitat 2013: iv)

The introduction of a third generation of urban indicators also meant the emergence and immersion of new actors and stakeholders in the difficult task of designing and developing innovative, holistic, and integral sets of indicators to measure and assess urban dynamics. Such diversification of actors implied a fundamental change in the structure of the conventional architecture of the global monitoring framework of our century (see Box 8.2). An example that clearly illustrates the emergence of this trend is the appearance of the World Council on City Data (WCCD) an independent international organization that hosts a network of innovative cities committed to improving services and quality of life using open-city data. It also provides a consistent and comprehensive platform for standardized urban metrics (WCCD 2016). Currently, the WCCD offers a new set of 100 urban indicators that comprise 17 dimensions of urban dynamics based on the first international standard on city data, ISO 37120.

Box 8.2 The experience of Jalisco in designing comprehensive urban dictators

MIDE Jalisco (MIDE stands for “to measure” in Spanish) is a comrehensive monitoring system of the Jalisco State Government, Mexico, that includes over 300 indicators of results and performance; this allows citizens to follow the state’s evolution in real time. Through MIDE Jalisco, the press, academics, decision-makers, and the general public have access to all of the indicators as open-source data. MIDE Jalisco is being unfolded into different subsystems, both sectoral and territorial, to monitor specific policy and geographic areas in depth. MIDE Guadalajara Metropolitana is an initiative to create the first subsystem designed for the city level, powered by Jalisco State Government together with the nine metropolitan municipalities that comprise Guadalajara Metropolitan Area, with the technical support of UN-Habitat and the WCCD. MIDE Guadalajara Metropolitana will be the first urban and metropolitan indicators platform in Mexico and Latin America to integrate the latest generation of indicators.

The recent adoption of the Social Progress Index at the local level among some cities around the world is another example that clearly demonstrates the diversification of sources of urban data as well as the broadening of the dimensions measured during the current generation of urban indicators. The Social Progress Index is a framework designed to measure the diverse elements of social progress, to document progress, and to encourage interventions to enhance human well-being (Social Progress Index 2015).

8.7 Towards a Fourth Generation of Urban Indicators

Despite efforts to measure and assess urban dynamics through more holistic indicators, our understanding of cities is still limited in four different ways: most reports tend to have partial global geographical coverage of specific regions; many tend to focus on measurement at the national level; they often provide a small depiction of a particular aspect of urban dynamics (Wong Reference Wong2014); and most lack a territorial, “geo-localized” approach.

Although we have witnessed huge progress in the development of urban data, as of 2017, there is no single set of indicators or monitoring frameworks that covers the full range of issues included in the broad agenda of urban dynamics. In fact, despite progress in many Western countries, even the economic output of cities remains elusive, as data collection for this information is lacking in most countries. These limits to our current measurement tools affect our ability to assess trade-offs among alternative policy choices accurately (OECD 2000). For this reason, the increasing necessity of relying on more robust, coherent, and flexible frameworks of indicators to analyze the performance of cities has been placed at the core of the global agenda. The current version of the CPI is a useful starting point (Sands Reference Sands2014), but it is not enough. For instance, even though the CPI theoretically accepts the importance of governance, there is no clear definition of what CPI means with regards to urban and land governance, or how to measure it. The prevailing limitations of currently available sets of urban indicators remind us that we need to keep moving forward towards a fourth generation. As Wong says, “There are still significant knowledge gaps in the framing and operationalization of prosperity” (Reference Wong2014).

A fourth generation of urban indicators should provide a broader, people-centered approach; alongside the existing monitoring frameworks, this generation of indicators should also include a strong territorial dimension into city analysis as a key factor that could enhance the accuracy in estimating urban governance. This means the adoption of a more localized approach of development at the city level, in order to provide a more contextualized interpretation of urban dynamics.

8.8 What We Have Learned from Monitoring Cities

A significant lesson we have learned is that most governments and stakeholders involved in the design of monitoring frameworks for urban dynamics adopt a citywide approach by finding synergies among indicators. The implementation of “isolated targets without a comprehensive approach to the city may undermine the very basic principle of sustainability” (UN-Habitat 2015: 5). Given that cities are immensely diverse, measuring accurately and, even more so, using data comparatively in the contexts of global indicators and indices, is extremely difficult. The challenges – and burdens – of data collection and reporting are also greater in smaller cities and towns than in their larger counterparts. Therefore, urban indicators need to be scale- and context-sensitive to accommodate smaller urban areas, not just large cities and metropolises.

Experience has shown us the importance of paying special attention to the local level, which is closest to the population. Local governments and administrations are “essential institutional building blocks … mechanisms, and process, through which public goods and services are delivered to citizens and through which citizens can articulate their interests and needs, mediate their differences, and exercise their rights and obligations” (UNDP 2009: 5). Thus, building and strengthening institutional capabilities at international, national, and local levels are crucial requirements for contemporary societies. Meeting these needs should be addressed with greater impetus since “decentralized governance, carefully planned, effectively implemented and appropriate managed, can lead to significant improvement in the welfare of people at the local level, the cumulative effect of which can lead to enhanced human development” (UNDP 2004: 2).

In the context of the 2030 Development Agenda, cities and metropolises play a key role since urbanization and city growth have been recognized internationally as transformative forces for development. Thus, the empowerment of local and regional authorities becomes essential for meeting SDG 11. The implementation of the urban SDG should lead to greater coordination among national and local stakeholders, providing higher levels of participation for local authorities in the difficult task of collecting, analyzing, and validating data and information for better urban governance.

8.9 Localizing the 2030 Development Agenda: The Empowerment of Local and Regional GovernmentsFootnote 1

Alongside communities and private sector actors, the essential role that local and regional governments (LRGs) play in delivering the 2030 Development Agenda has been recognized during a number of official events throughout the recent transition from the MDGs to the SDGs. It has been noted on several occasions that the achievement of the SDGs depends heavily on coordination among local governments and other stakeholders involved; global challenges have to be met with local responses (Wong Reference Wong2014; Simon et al. Reference Simon, Arfvidsson, Anand, Bazaaz, Fenna and Foster2016). The localization of the 2030 Development Agenda should not be seen solely as a technical agenda of implementation at the local level, but also as a political agenda that empowers local actors and puts decision-making, data production, and analysis and solutions provision at levels closer to the citizens. This would imply not only gathering different types of data, but also doing things differently, providing diverse sets of competences and resources to different actors and administrations.

This agenda is most clearly embodied in SDG 11, which is local by design – that is, meant to be embraced and delivered by subnational urban governments. The inclusion of an explicitly urban goal in the SDGs is an important achievement and is a testament to the successful advocacy, throughout 2013–2014 of, among others, the Global Taskforce of Local and Regional Governments and its partners, which is a coordination mechanism bringing together the major international networks of local governments to undertake joint advocacy relating to international policy processes.Footnote 2 As argued during the #Urban SDG Campaign, an urban goal should mobilize and empower LRGs and urban actors, contribute to integrating the different dimensions of sustainable development (economic, social, environmental) and the spatial design of cities, strengthening the linkages between urban and rural areas, and transforming urban challenges into opportunities. However, SDG 11 does not take a holistic approach to urban development. Key urban concerns, including local governance, are not addressed, while other key urban responsibilities are partially included under other goals.

More generally, to be achievable, a majority of the goals and targets will need strong involvement of LRGs in both urban and rural areas (see Simon et al. Reference Simon, Arfvidsson, Anand, Bazaaz, Fenna and Foster2016). This is why it is important to discuss what we mean by “localization.” Localizing the 2030 Development Agenda often refers to at least two dimensions: 1) the definition and implementation of the targets and indicators at the local level and 2) the monitoring and evaluation process.

With respect to the first dimension, it is obvious that subnational governments have responsibilities (either direct responsibilities or those shared with central government or in partnership with other stakeholders) for achieving targets and service provision in the majority of the areas related to the SDGs (Cities Alliance 2015; González et al. Reference González, Donnelly, Jones, Klostermann, Groot and Breil2011; UCLG 2014). The scope of subnational governments’ work is clearly linked to alleviating poverty; securing nutrition; ensuring health and education; promoting gender equality; managing water, sanitation, urban planning, public transport, waste, and energy resources; promoting local economic development and decent jobs; fighting climate change; and increasing communities’ resilience.

However, localizing the Post-2015 Agenda can also refer to monitoring progress at the subnational level (irrespective of whether LRGs have competency in that specific area). This can help to assess inequalities within countries and support better decision-making and resource allocation at all levels, as well as enabling local communities and civil society organizations to hold their governments accountable. In this spirit, the UN’s Inter-Agency and Expert Group (IAEG) reports out of the UN made suggestions for geographical disaggregation of data for most outcome-based targets (United Nations 2013). This should include, for example, urban/rural and regional breakdowns and, where possible disaggregation at lower levels, such as municipalities, urban agglomerations, or marginal areas, such as slums.

These two approaches to localization are complementary. Ideally, subnational governments should define a specific subset of goals and targets where they have direct responsibilities and set up the level of indicators, contributing to their delivery and achievement. But this will also require stronger coordination and partnership between different levels of government, as is required for effective, multilevel governance. National governments should encourage local authorities to identify and adopt concrete commitments that might help to achieve the SDGs. When it comes to monitoring progress at subnational levels, local and regional governments could focus on monitoring for vulnerable areas and communities. They could even focus on the gaps in performance within their respective areas of jurisdiction – for example, in slums versus in the local average – to clearly identify spatial inequalities. However, data constraints are generally more pronounced at local levels than at the national level. In many cases, where data are based on survey information, it is difficult to disaggregate indicators beyond rural/urban and regional breakdowns. It is particularly difficult to have adequate source data for vulnerable populations (such as slum dwellers). This has obvious resource and capacity implications in terms of data collection, and would require the support of national statistics offices.

There is consensus that local and regional governments should play a crucial role in implementing and monitoring most of Agenda 2030. Localizing the SDGs means providing adequate targets and indicators to measure their impact at the territorial level, and proposing strategies and tools to facilitate the efficient involvement of LRGs in the implementation process. However, besides the need to improve mechanisms to obtain reliable local data, the implementation process needs strong and empowered local and regional governments. Thus, processes oriented to facilitate enabling environments for LRGs should be prioritized. Supporting decentralization processes, both political and fiscal, through strengthening institutional and operational capacities to deliver basic services and sound public policies; developing new forms of governance that enable multilevel partnerships; and insisting on multi-stakeholder approaches, are important conditions for allowing the localization of the development agenda.

8.10 Conclusions

Our analysis demonstrates that as the world moves into the urban age, new challenges and opportunities regarding the current monitoring frameworks for cities have emerged (UN-Habitat 2013). For instance, urban indicators offer a useful tool that contributes in several ways to mitigating the negative effects of urbanization on contemporary societies. We have also demonstrated the evolution of attempts to develop better urban indicators and monitoring frameworks. The elastic nature of the main characteristics and sets of indicators that comprise each generation illustrates that urban indicators have evolved in parallel with conceptualizations of development, well-being, and prosperity. Empirical evidence over the years has demonstrated that classical economic metrics are insufficient standards with which to measure and understand current urban dynamics.

However, we have not yet reached the finishing line; at present, we are undergoing a transitional process towards a fourth generation of more comprehensive and holistic sets of urban indicators in which several stakeholders are involved. The emerging monitoring frameworks do somehow respond to the urgent need to fill the urban information vacuum through a broader and multidimensional understanding of city prosperity. Yet, important limitations still prevail among such attempts to measure and understand urban dynamics. Cities need to keep moving forward in the difficult task of designing better measurement instruments. In the context of increasing urbanization, it is crucial to incur the costs of developing such measurement instruments as an investment in better understanding cities, and hence becoming capable of mitigating the problems and challenges that harm our planet. In this regard, the development of better and new urban indicators should be at the core of the urban agenda. This effort must include a focus on how data to support such indicators will be collected to build global datasets and by whom – city networks, researchers, or others – particularly in light of shifting political realities or other barriers that might complicate such efforts, thereby creating gaps in the process.

Building and strengthening institutional capabilities of cities is also an essential task that must be addressed in every single society. Local and regional authorities have a central role to play in meeting the 2030 Development Agenda and in “contributing to national and global recovery” (Ban Ki-moon, quoted in UN-Habitat 2013: iii). A fourth generation of more people-centered and territorialized indicators will provide the necessary means to creating better-informed policies and designing sound development plans for the future.

References
Cities Alliance, 2015. Sustainable Development Goals and Habitat III: Opportunities for a Successful New Urban Agenda. Discussion Paper No. 3. www.citiesalliance.org/sites/citiesalliance.org/files/Opportunities%20for%20the%20New%20Urban%20Agenda.pdf.
Global Taskforce, 2014. How to Localize Targets and Indicators of the Post-2015 Agenda, November 14, www.uclg.org/sites/default/files/localisation_targets_indicator_web.pdf.
González, A., Donnelly, A., Jones, M., Klostermann, J., Groot, A., and Breil, M. 2011. Community of Practice Approach to Developing Urban Sustainability Indicators. Journal of Environmental Assessment Policy and Management 13 (4): 591617.
Lucci, P. 2015. Localising’ the Post-2015 Agenda: What Does It Mean in Practice? ODI, January. www.odi.org/publications/8992-localising-post-2015-agenda-does-mean-practice.
Muhammad, Z.B. 2001, Development of Urban Indicators: A Malaysian Initiative, in J. J. Pereira, and I. Komoo (eds.) Geoindicators for Sustainable Development. Kuala Lumpur: Institute for Environment and Development: Universiti Kebangsaan Malaysia, pp. 1732.
OECD, 2012. Compact City Policies: A Comparative Assessment, OECD Green Growth Studies, OECD Green Growth Studies. Paris: OECD Publishing.
OECD, 2000. Frameworks to Measure Sustainable Development. Paris: OECD Publishing.
Sands, G. 2014. Measuring the Prosperity of Cities. Habitat International, 45 (1): 12.
Social Progress Index. 2015. Social Progress Index 2015. www.socialprogressimperative.org/data/spi.
Simon, D., Arfvidsson, H., Anand, G., Bazaaz, A., Fenna, G., and K., Foster, et al. 2016. Developing and Testing the Urban Sustainable Development Goal’s Targets and Indicators – A Five-City Study. Environment and Urbanization 28: 4963.
Thomson S., 2016. GDP a Poor Measure of Progress, say Davos Economists, World Economic Forum, last modified January 23, www.weforum.org/agenda/2016/01/gdp
UCLG, 2014. Basic Services for All in an Urbanizing World, 3rd Global Report on Local Democracy and Decentralization. Oxon; New York: Routledge.
UNDP, 2016. A New Sustainable Development Agenda, www.undp.org/content/undp/en/home/sdgoverview.html
UNDP, 2009. A User’s Guide to Measuring Local Governance. Oslo, Norway: UNDP Oslo Governance Center.
UN-Habitat, 2015. Sustainale Cities and Communities: SDG GOAL 11 Monitoring Framework. New York: UN-Habitat.
UN-Habitat, 2013. State of the World’s Cities 2012/2013 Prosperity of Cities. Nairobi: United Nations Human Settlements Programme.
United Nations, 2013, A New Global Partnership: Eradicate Poverty and Transform Economies Through Sustainable Development. The Report of the High-Level Panel of Eminent Persons on the Post-2015 Development Agenda, New York: United Nations Publications. www.un.org/sg/management/pdf/HLP_P2015_Report.pdf.
WCCD, 2016. World Council on City Data, www.dataforcities.org/
Wong, C. 2014. A Framework for ‘City Prosperity Index’: Linking Indicators, Analysis and Policy. Habitat International, 45: 39.
Wong, C. 2006. Quantitative Indicators for Urban and Regional Planning: The Interplay of Policy and Methods. London: Routledge.
World Bank, 2016. World Development Reports: Digital Dividends, Washington, DC: International Bank for Reconstruction and Development/The World Bank. www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2016/01/13/090224b08405ea05/2_0/Rendered/PDF/World0developm0000digital0dividends.pdf.

1 The following note is extracted and slightly modified from Global Taskforce (2014). See also Lucci (Reference Lucci2015).

2 The Global Taskforce of Local and Regional Governments is a coordination mechanism set up in 2013 at the initiative of UCLG President and Mayor of Istanbul Kadir Topbaş. It brings together the major international networks of local governments (22) to undertake joint advocacy relating to international policy processes, particularly the climate change agenda, the Sustainable Development Goals and Habitat III. See www.gtf2016.org/

Chapter 9: The UN, the Urban Sustainable Development Goal, and the New Urban Agenda

Andrew Rudd , David Simon , Maruxa Cardama , Eugénie L. Birch , and Aromar Revi
9.1 Evolving International Conceptions of the Urban

Since its establishment 70 years ago in the ashes of World War II, the international multilateral system’s conception of “the urban” has evolved significantly. This reflects both the maturation of the original United Nations (UN) and Bretton Woods institutions and the subsequent establishment of new, more specialized institutions in the 1970s to respond to the rise of environmental and human settlements challenges on international agendas and priorities. Of particular relevance in this context are the UN Environment Programme, or UNEP, and the UN Human Settlements Programme, or UN-Habitat (formerly the United Nations Centre for Human Settlements, or UNCHS). Both of these programs are symbolically headquartered in Nairobi as part of an initiative to give the UN a more global physical footprint.

The importance of having a UN agency devoted entirely to human settlements issues, albeit focused on what the UN vocabulary still resolutely refers to as “developing countries,” should not be underestimated. UN-Habitat’s orientation was expanded to include the transitional economies of Eastern and Central Europe after the end of the Cold War, and though its governing council and reporting cover all five UN regions, its policy advice and capacity development are only now becoming more global. Initially, its effectiveness was hampered by its classification as a “Centre” – without the status of a UN implementing agency, it had to work through UNEP for strategic and budgetary purposes. This constraint was eased when it achieved programme status in 2002 (UN-Habitat 2015). Nevertheless, rather than leading such innovations, the UN’s urban conceptions and approaches to tackling the principal problems of fast-growing cities in poor countries have generally lagged behind changes fomented on the ground, in NGO thinking, and in the research literature.

To wit, notwithstanding numerous dramatic demographic shocks with important and often long-term urban consequences, such as the mass displacements of World War II and the partition of India and Pakistan in 1947, as well as accelerating rural-urban migration and growing refugee settlements in decolonizing and newly independent states during the 1950s and 1960s, the dominant conception of urbanization by governments and international agencies was as a temporary, largely negative phenomenon. This perspective was strongly influenced by erstwhile colonial policy in late nineteenth- and early twentieth-century European settlement colonies, which maintained that indigenous populations had been predominantly rural before the European conquest, and where urban areas were established to serve the settler populations and imperial purposes rather than indigenous needs. The reality of longstanding, large-scale, and sophisticated indigenous urban cultures in many previously conquered indigenous polities from Meso-America through North and West Africa and the Middle East to South and Southeast Asia was somehow erased from such constructs.

The policy response to this perception comprised concerted efforts to keep rural dwellers in rural areas and agriculturally productive, while passively seeking to lessen cities’ impact on the environment. This proved ineffective almost everywhere, and rapid net migration continued. The conventional solution of state-funded mass housing in high-density apartment blocks in Latin America and a mixture of single-sex worker “hostels” and small “matchbox” family houses in East and southern Africa became increasingly unaffordable to city authorities and national governments, many of which ceased such practices after independence.Footnote 1 Moreover, residents found them alienating (and often alien) social environments, with many sociocultural problems and considerable un- and underemployment where industrialization was not occurring or was expanding only slowly. This resulted in a widespread spatial mismatch between need and availability of housing, services, and employment (Gilbert and Gugler Reference 195Gilbert and Gugler1992).Footnote 2

Innovative research, pioneered by Walter Mangin and John Turner in Latin American cities in the 1960s, demonstrated that working with the urban poor to address their housing and livelihood needs was far more effective in facilitating urban integration than large-scale, top-down public sector housing delivery. Despite opposition from many quarters, especially among governments and national elites, such work spawned a sea change in attitudes, with the first World Bank-funded site-and-service scheme launched in Dakar, Senegal, in 1970, and a veritable flourishing of various self-help and aided self-help experiments and programs through the 1970s and 1980s (see Turner Reference 196Turner1980; Moser and Peake Reference Moser and Peake1987; Rodwin Reference Rodwin1987; Amis and Lloyd Reference Amis and Lloyd1990; Gilbert and Gugler Reference 195Gilbert and Gugler1992; Aldrich and Sandhu Reference Aldrich and Sandhu1995). In many cases, these schemes were peripherally located and poorly integrated into the overall urban fabric – though, in retrospect, they were surprisingly resilient to changing urban environments. Despite their varied success, they ultimately did little to address the ongoing urbanization pressures, which became increasingly differentiated in space and time at different scales – both subnational and regional – in accordance with economic cycles and official policies.

Reflecting the changing perceptions, Habitat I, the first global summit on the topic in Vancouver in 1976, was far more positive about urbanization. Its outcome document is often even bullish on the prospects of human settlements. Nevertheless, it states that “[r]ural backwardness … contribute[s] to uncontrolled urban growth,” leading ultimately to “intolerable psychological tensions due to overcrowding and chaos.” As a consequence, it urges the UN to “give priority to improving the rural habitat.” This was said to “enable the greatest possible number of scattered and dispersed rural settlements to derive the benefit from basic services” which would “help to reduce the migration to urban areas” (United Nations 1976).

In 1996, Habitat II, the second major global housing and shelter convention, held in Istanbul, posed participatory planning and management as a solution to these persistent processes and failed official policies (UN-Habitat 1996). That it took over 25 years from the first World Bank site-and-service scheme to gain prime position in the global agenda demonstrates the duration of policy lag. Nevertheless, this, too, was a limited response that failed to get to grips with rapid urban growth and the turmoil caused by the financial crisis just two years later. This change in the economy saw rising unemployment and government fiscal deficits, which in turn precipitated reduced subsidies for housing and other basic needs and social provisions (see, for example, Satterthwaite Reference Satterthwaite1997).

As evidence of the human cost and development reverses of the economic crisis mounted, world leaders adopted the eight Millennium Development Goals, or MDGs, at a special UN summit in late 2000. Heralded as another landmark by recognizing poverty as the principal impediment to development and committing resources to tackling it via a series of annually reportable targets and indicators, they applied only to poor countries. Although no MDG addressed urban issues directly, a few targets and indicators on slums and water and sanitation had urban relevance and implications. However, the underlying framing of urbanization amounted to a reversion to mid-twentieth century perspectives, in terms of which it is defined principally as a housing crisis, and the UN’s role is thus restricted to treating its primary symptom: the slum.

UN-Habitat (2010a: 16) defines slums as comprising households “lacking one or more of the following: improved water; improved sanitation; sufficient living area; durable housing; and secure tenure.” Hence, the proportion of an urban area’s population living in slums constitutes the proportion of such slum households. This definition has been widely criticized as too limiting, pejorative, and prone to statistical misrepresentation. This critique arises because when one or more of the “urban deprivations” is relieved, the house(hold) in question is recorded as having been lifted out of slum conditions – which is often not the case, despite the improvements. Nor does such an improvement address the actual drivers of slum formation. However, the human rights-based definition of “adequate housing” is broader, and adds the key dimension of location (vis-à-vis employment, hence mobility) and cultural adequacy.

The recent adoption of the 2030 Agenda for Sustainable Development thus represents a decisive shift in approach, from reactive to ambitiously proactive. The New Urban Agenda was adopted by the UN heads of government at Habitat III in Quito, Ecuador, in October 2016, symbolizing the UN’s recognition of urbanization as a permanent driver of development with potentially positive impacts on people and the planet. How the 2030 Agenda is ultimately linked to the New Urban Agenda – particularly in terms of monitoring and indicators – during their simultaneous implementation remains to be seen, since the two documents have no appreciable formal connection.

It is worth pointing out that, amid the inevitable focus on evolving institutional perspectives, the examples cited above of Turner and Mangin in relation to low-income housing policy remind us that the roles of key individuals in shaping international institutions and their agendas should not be overlooked (compare with Weiss et al. Reference Weiss, Carayannis, Emmerij and Jolly2005; Parnell Reference Parnell2016).

In September 2015, after an unprecedented consultative process geared towards designing the successor to the MDGsFootnote 3, the 193 nations of the UN unanimously adopted the 2030 Agenda for Sustainable Development (Figure 9.1)Footnote 4. At its core are 17 global Sustainable Development Goals, or SDGs, and their 169 targets. The SDGs are much more ambitious than the MDGs in that they address the challenges of the entire world, not just low- and middle-income countries. The inclusion of SDG 11 represents broad international consensus to legitimize sustainable urban development as a transformational driver for human development.

Figure 9.1 UN Summit Adopts Post-2015 Development Agenda. A view of the General Assembly Hall following the adoption of the post-2015 development agenda by the UN summit convened for that purpose.

Source: UN Photo/Cia Pak, New York, 2015

SDG 11 is no minor victory for urban sustainability stakeholders – including practitioners, local and regional governments, and their networks, as well as national governments, science and academia, philanthropy, and the private sector – that actively engaged in the three-year intergovernmental process that produced the Agenda. Throughout this time, they confronted the possibility that the urban dimension might be merged with other goal areas, such as infrastructure or sustainable consumption and production, or simply become mainstreamed across other SDGs (with the likely diminution or disappearance of its spatial aspect). It is worth highlighting that 2015 saw the adoption not only of the 2030 Agenda, but also of the Sendai Framework for Disaster Risk Reduction 2015–2030,Footnote 5 the Addis Ababa Action Agenda on financing for development,Footnote 6 and the Paris Agreement on Climate ChangeFootnote 7; these three acknowledge the potential, consequences, and responsibilities, respectively, that are inherent in urban development.

With its fate now secure, SDG 11 has renewed the MDG imperative of ensuring basic living conditions for human dignity (Target 11.1) but has also raised a host of new, twenty-first-century issues. Target 11.2 is a call to action on urban transport provision, which has major implications for access to economic opportunities, household expenditures, greenhouse gas emissions, and health. SDG 11 also addresses air pollution and waste as key challenges to be tackled at the urban scale (11.6) and emphasizes the improvement of community resilience to disaster (11.5). Moreover, cities and human settlements are recognized as worthy of cultural and natural heritage safeguarding. Among the targets that address means of implementation for SDG 11, we find a clarion call for the use of integrated policy and planning (11.b), as well as a focus on building sustainable and resilient buildings in least-developed countries (11.c).

Three other targets under SDG 11 merit special attention. The unprecedented focus of SDG 11 on urban planning and land use (Target 11.3), public and green space (Target 11.7), and national and regional development planning (11.a) make SDG 11 uniquely spatial compared to all other SDGs. These three essential enablers of development are largely unaddressed in the other, predominantly space-blind SDGs. By contrast, the focus of SDG 11 on the wider built environment gives long-overdue attention to the preeminently path-determinant role of physical configuration.

Target 11.3 represents broad international consensus that spontaneous, unplanned urban expansion too often yields inefficiency, increased emissions, and segregation. Nevertheless, it is still difficult for governments to fully apprehend the far-reaching impacts of spatial planning and its numerous benefits and co-benefits, including higher-level outcomes such as efficiency, productivity, amenity, and resilience. Favorable settlement patterns enable these; unfavorable ones not only do not enable them, but ultimately lock a city into rigid, inefficient patterns that are often very expensive and difficult to retrofit. Good spatial planning will likely have positive spillover effects outside of SDG 11, including strengthened food systems and expanded access to services and utilities. Target 11.3 also qualifies planning as a discipline that must be participatory. It can help governments and citizens alike understand the far-reaching impacts of urban form, so that they can engage in the planning process more meaningfully (Rudd et al. Reference Rudd, Malone, Bartlett, Russ and Krasny2017). In so doing, they can address a number of critical questions: Where should development be located? Which pattern(s) will it embody? How will it balance process and outcome to yield both social and environmental sustainability?

Target 11.7 responds to research that shows public and green space disappearing in unplanned cities. At the same time, existing public space in planned cities is being commercialized, exacerbating socioeconomic fragmentation (UN-Habitat 2013, 2015). Both situations are weakening cities’ capacities to provide basic services equitably and efficiently, suggesting the need for both a qualitative and quantitative approach: cities, particularly fast-growing ones, should first secure an adequate proportion of public space; additionally, cities can take measures to improve the amenities, accessibility, greenness, and safety of existing public space. Scholars and practitioners are left with crucial open questions, such as: How can policy-makers optimally use the information provided by geospatial technology? How to best influence the norms that regulate the private ownership of land?

SDG 11 also acknowledges cities as developmental drivers beyond their administrative boundaries. The goal’s promotion of urban-rural linkages (Target 11.a) signals a reinvigorated desire from the international community to move from a dichotomous conception of urban and rural development to one of mutually reinforcing, synergistic development across the rural-urban continuum. However, such a concept remains quite difficult to translate into tangible policies at all levels of government. Cities still require concrete legislative, spatial, and financing solutions that extend beyond the provision of agricultural goods to urban centers and the control of urban expansion into rural areas.

The 2030 Agenda pledges that no one should be left behind in any nation. This universality leaves us with the corollary challenge of being sufficiently specific for relevance and impact in diverse local contexts. Significantly different levels of development, governance structures, and capacities among the world’s cities mean that some SDG 11 targets appear to be much more applicable to certain urban contexts than others. A “locally relevant” policy-science interface may help translate the universal SDG 11 targets into national and subnational action programs (Simon et al. Reference Simon, Arfvidsson, Anand, Bazaaz, Fenna and Foster2016).

The universality of the 2030 Agenda, achieved through intergovernmental negotiations, has meant a trade-off with ambition as well as some glaring omissions. SDG 11 does not even pay lip service to cities’ status as engines of economic development, innovation, and job creation. It also avoids the issue of governance, including decentralization and access to finance at subnational levels. Achieving sustainable cities will surely require strategic frameworks and plans that are integrated into all levels of government and policy-making. UN language speaks of the integrated character of the 2030 Agenda, particularly the way it targets the social, economic, and environmental dimensions of sustainability on equal footing. If the implementation of SDG 11 succeeds in integrating all three dimensions, it can accelerate the pace of achievement of many other SDGs. Conversely, if SDG 11 implementation is interlinked with other urban-critical SDGs – especially poverty (SDG 1), health (SDG 3), and inequality (SDG 10); water and sanitation (SDG6) and energy (SDG7); employment and economic growth (SDG8) and infrastructure (SDG9); sustainable consumption and production (SDG12) and climate change (SDG13); and accountable and inclusive institutions (SDG16) – their achievement can help overcome some of the omissions within SDG 11 itself.

Maximizing balanced gains across all three dimensions of sustainability will depend on effective interlinkages. This notion is familiar to urbanists and many local and regional governments that are accountable to the public and accustomed to integrated planning and management, but governments have not put it into practice widely, nor have developing institutional frameworks commonly embedded it into their thinking. This is why national urban policies are a twenty-first century “must-have” (UN-Habitat 2014; Parnell and Simon Reference Parnell, Simon, Parnell and Pieterse2014). Such policies can integrate long-term visions with strategic approaches, and, when crafted in collaboration with all levels of government, can reflect the needs and assets of a country, its regions, and its cities. Progress has been slow: only nine countries have implemented national urban policies to date (UN-Habitat 2016). Nevertheless, SDG 11 and the New Urban Agenda offer unparalleled opportunities for countries to adopt them.

In multilateralism, technical rigor is not immune to political negotiation, but that should not tarnish the historic milestone that is the adoption of SDG 11. It is a powerful plan of action that will certainly promote and incentivize urban sustainability all over the world. Undoubtedly, the task ahead is complex and the solutions are not always clear. Nonetheless, that which three years ago was little more than the dream of a few fringe urbanists is now an undeniable victory that must be leveraged to create a global implementation plan across stakeholders and disciplines. The SDGs represent a common denominator, but one that is a floor for urban action, not a ceiling.

9.2 Metrics and the Impact of the Urban SDG

Determining the impact of SDG 11 and the urban dimension of other SDGs relies heavily on the choice of metrics to assess their implementation. Experts generally adopt a conceptual framework to guide and anchor the choices underlying a set of performance metrics. Such a framework helps define and refine a common vision, encourages the creation and regular updating of information, underlines and reinforces progress (or demonstrates the weaknesses, failings, and false assumptions) of a given policy or program, and supports a wider public understanding of the enterprise under consideration (Hak et al. Reference Hak, Moldan and Dahl2007). Although many evaluation techniques exist (such as quasi-randomized studies, case studies, benchmarks, surveys, and questionnaires), the use of indicators has become the commonly accepted approach in assessing sustainable development (Hak et al. Reference Hak, Moldan and Dahl2007; Bell and Morse Reference Bell and Morse2008; Chapter 8, this volume).

To review: An indicator is a simple measure that signals whether a policy or program is on target to reach a predetermined goal. By contrast, benchmarks, while related, are predetermined milestoness. Many types of indicators exist. They range from a single figures derived from several inputs (as in the broadly accepted gross national product, or GDP) to systems of multiple indicators (as in the approach employed by the MDGs, which associated 48 indicators with its 8 goals and 18 targets). The monitoring of the SDGs will implicitly use the goals and their targets as a conceptual framework and will take the multiple indicator system approach, such that there are indicators under consideration.

Figure 9.2 illustrates the place of indicators in public policy. Employed correctly, indicators not only serve to gauge progress, but are valuable tools with which to communicate to the public. While indicators have limitations, scholars and practitioners in policy areas continue to advance the work of testing selected indicators against policy goals and actual behavior, consulting users about indicator improvement, and sharpening the data that underlie indicators to achieve uniformity and comparability (Birch et al. Reference Birch, Lynch, Andreason, Eisenman, Robinson and Steif2011).

Figure 9.2 The place of indicators in public policy

In the case of SDG 11, the agreed upon conceptual framework holds that cities are systems of systems (for example, housing, transportation, and environment), places of agglomeration (that is, clustering of people and their activities), and nexuses of sustainable development. The underlying assumption is that the transformational potential of cities lies in the equitable and efficient planning and managing of land to foster the provision of urban systems that maximize the benefits and minimize the costs of agglomeration. Current knowledge holds that certain techniques tend to support this approach. They include mixing land uses, adaptively reusing buildings, crafting walkable neighborhoods linked to each other and beyond with public transportation, and reinforcing ecosystem services with green and blue patches and corridors.

According to the conceptual framework of SDG 11, achieving sustainable urban development suggests the use of a series of indicators premised on the advantages of agglomeration (United Nations, Economic and Social Council 2015). Such a series starts with a base figure that measures the alignment of land consumption with population growth to mark necessary and sufficient conditions for equitable and efficient service provision and to support agglomeration. This land efficiency indicator, or LES, is most simply expressed as a ratio: the rate of land consumption to the rate of population growth. While the LES is a new type of indicator that calls for the use of geographic information systems in tandem with traditional demographic data collection methods, the technology is now sufficiently developed to be employed widely.

A land-use efficiency ratio is diagnostic rather than prescriptive; desirable ratios should be determined locally, based on the cost of services, customs, and land availability. However, a baseline of 1:1 would indicate that the growth rates for land use and population are in equilibrium. A baseline of 2:1 would signal that a place is becoming less dense because land consumption would have occurred at twice the rate of population increase. Conversely, a 1:2 ratio would indicate more dense land development with less land being used to accommodate a growing population. Notably, the corrective in places where land is viewed as a seemingly limitless resource would be to address uncontrolled, fragmented, and/or sprawling development patterns; the remedy in places where land supply is constrained would be to release, allocate, and/or prepare sufficient land to accommodate growth (see Atlas of Urban Expansion 2016). Thus, this indicator is a gross measure that “takes the temperature” of a place, showing an overall trend. It warns decision-makers of potential issues – issues that would require more nuanced analysis to inform policy-making. Nevertheless, global trends all point to a general decline in land-use efficiency – that is, a movement towards sprawl – which tends, overall, to correlate with undesirable socioeconomic and environmental effects.

At a minimum, then, the LES alerts decision-makers to the general nature of growth in their communities, which can guide deeper probes to explore the location, direction, and character of land consumption. These issues include ascertaining whether developments are on disaster-prone or vulnerable land; whether they are contiguous or fragmented; whether they are moving towards existing nearby centers; and whether metropolitan mobility is increasing or decreasing. Answers to these and other questions will enable decision-makers to craft policies to affect the place and timing of future development. Such answers might also help urban residents better understand the short- and long-term trade-offs involved in configuration-based planning and contribute to more educated decision-making (Rudd et al. Reference Rudd, Malone, Bartlett, Russ and Krasny2017).

The LES also works with other indicators associated with the SDG 11 targets to expose interrelated policy choices, especially those addressing housing (proportion of people living in slums), transportation (proportion of people having access to public transportation), public space (the average share of the built-up area of cities that is open space for public use), and the environment (percentage of urban solid waste regularly collected). Working in tandem with related policy choices is useful because of the thresholds of socioeconomic viability that urban agglomeration can help other sectors meet. If, for example, the LES demonstrates less dense settlement patterns, instituting a citywide, technologically advanced waste management system may be economically unfeasible until the municipality employs land-use policies to promote the required density for such a management system to work. Conversely, if the LES shows excessive density, then looking into instituting corrective policy for public space provisions would likely be in order.

Finally, decision-makers can employ the LES and the other indicators for SDG 11 to assist in the achievement of the total suite of SDGs. For example, with its focus on the provision of public transport infrastructure, the indicator for Target 11.2 will almost certainly result in lower per capita rates of energy use and emissions production, thus accelerating the achievement of SDG 7 and SDG 13 on energy and climate. Likewise, the indicator for Target 11.1, which addresses slums, indirectly calls for dwellings composed of durable materials and with access to water and sanitation, which will contribute to the achievement of SDG 3 on health. Similarly, the land-use efficiency measure adds to an understanding of land-use patterns and thus could serve efforts to protect peri-urban agriculture and habitat, consequently supporting SDGs 2 and 15, which are concerned with food and biodiversity.

While a clear conceptual framework must underlie the metrics of any effective indicator system, such a framework is critical to the measurement of equitable and efficient planning and managing of land. This is particularly the case if cities aim to maximize the benefits and minimize the costs of agglomeration. Urban spatial configuration plays a highly deterministic role and portends many spillover effects in the economic, social, and environmental dimensions of urban sustainability. In connection with this the LES is the fundamental indicator because it gauges the relationships between land consumption and population. The LES and other associated SDG 11 indicators on housing, transportation, resilience, cultural and environmental heritage, environment, and public space form a holistic approach to implementing SDG 11 and are ultimately supportive of other SDGs in important ways.

9.3 Implementation and the Future

Much of the world is currently underprepared to implement SDG 11, be it at the city, provincial, national, or global scale. This is a serious challenge facing the global urban community. Except for a handful of countries and a somewhat larger cohort of cities, the constitutional and legal mandates; institutional capacities; and human and financial resources required to implement these universal goals are at best weak, and – at worst – confused and contradictory. Moreover, such parameters are often missing at the city level. These shortcomings will need to be addressed by the early 2020s if the SDGs are to be delivered by 2030.

Even more challenging for many countries is the prospect of having to implement all the SDGs in urban areas, from poverty; health and education; basic services; employment; and prosperity to safety; rule of law and institutional strengthening; and partnerships (Kanuri et al. Reference Kanuri, Revi, Espey and Kuhle2016). The first step in enabling the achievement of the SDGS is the recognition that most countries – and almost all cities, even in high-income countries or countries scoring highly on the Human Development Index – are “developing,” in that they are far from achieving many of the universal economic, social, and environmental targets agreed in the 2030 Agenda (Sachs et al. Reference Sachs, Schmidt-Traub, Kroll, Durand-Delacre and Teksoz2016; Revi Reference Revi2016). There is much to be done over the next few years to improve the coverage and quality of the SDG goals, targets, and indicators through an iterative process of innovation and testing, capacity building, financing, monitoring, and evaluation. Once this process is undertaken, rapid, flexible, and multi-stakeholder problem solving will ultimately be required to implement them (Kanuri et al. Reference Kanuri, Revi, Espey and Kuhle2016; Simon et al. Reference Simon, Arfvidsson, Anand, Bazaaz, Fenna and Foster2016). In short, this will be an interlinked local, national, and global effort.

However, sectorally organized national governments are generally not only unwilling to share power and resources with cities, but even struggle simply to imagine integrated, cross-sectoral planning and delivery (Parnell Reference Parnell2016). In stark contrast, joint planning and delivery are parts of the daily lives of most mayors, as well as local and regional urban leaders, who are naturally able to see the value of the SDGs clearly (New School 2015). A local-to-national convergence along these lines will require active dialogue between cities, a partnership among various levels of government, and the recognition that citizens lie at the heart of the implementation agenda. The New Urban Agenda outlines the need to address integrated action across all the SDGs, sectors, and levels of governance if we are to ensure that no one and no place is left behind (Revi Reference Revi2016; UN-Habitat 2016). The reality of the Habitat III process – and that it happens only once every two decades – has provided a fillip to a clear agreement on these foundational questions (United Nations 2016).

Since the answers to these questions have political implications, they require high-level approval by UN member states, similar to that required for the SDGs; this approval occurred in December 2017, when the General Assembly endorsed the New Urban Agenda after its adoption in QuitoFootnote 8. Its implementation will proceed in a series of processes that will extend to 2018 and beyond. The New Urban Agenda confirms the linkages between its implementation and that of the SDGs.Footnote 9 On the international stage, important next steps for the SDGs are (1) agreeing on national and subnational monitoring systems that will ultimately move through the High-level Political Forum, thereby providing a formal role for local and regional governments, (2) committing to a reimagined global, regional, and national architecture for financing urban infrastructure, (3) delineating a clear operational division of labor among key UN agencies and stakeholders – including UN-Habitat, other UN and multilateral agencies, development finance institutions, bilateral aid agencies, and new private sector and other nongovernmental players, (4) continuing the mobilization of local and regional governments – in partnership with the enterprise sector; universities and knowledge institutions; movements; and trade unions – towards the implementation of SDG 11, and (5) engaging citizens (especially youth) so that they take charge of key choices and actions (Kanuri et al. Reference Kanuri, Revi, Espey and Kuhle2016).

Effective SDG implementation depends on a set of five minimum enabling conditions (Kanuri et al. Reference Kanuri, Revi, Espey and Kuhle2016). First, a facilitatory constitutional, legal, and regulatory environment must exist to enable local and regional governmental stakeholders to contribute to implementation. Second, a multilevel national urban and settlements policy framework must be in place to permit planning, implementation, and monitoring at multiple levels (see Section 9.1). Third, the institutional capacities of stakeholders – and of agents of change at the appropriate levels of subsidiarity to the country and regional context – must be commensurate to the task. Fourth, appropriate mechanisms of local and domestic financing (linked to regulatory and institutional capacities) must be available to direct financial flows into infrastructure, services, housing, and buildings at both regional and city levels. Fifth, an open and flexible institutional environment must exist to enable key stakeholders from community groups, private enterprises, media, and research organizations to interact, focus on problem solving and implementation, and learn from one another.

These five minimum conditions will require nurturing in a variety of contexts related to history, culture, political economy, and the spatial specificity of urban systems. A clear definition and partitioning across the rural-urban continuum may help provide clarity on roles, institutional jurisdictions, policy frameworks, and financing, so that implementation can take center stage. Subsidiarity may not be possible until city, regional, and national governments and other stakeholders build a culture of trust and partnership. This is a complex and often contentious process of political and economic discovery, as new institutional structures, interest groups, and blocks of winners and losers will emerge. Addressing both horizontal (that is, across sectors) and vertical (that is, across levels) governance could have constitutional, legal, and regulatory implications, depending on the national context.

In many contexts, implementation will also hinge on strengthening and developing urban economic systems. This will likely include reducing the risk of lending to cities, increasing municipal authorities’ local revenue generation capacities, and addressing employment, informality, worker skills, and productivity. Preemptively addressing land and labor market concerns and building integrative and participatory planning processes will pay off over the medium- and long run. All the same, the capacity to address emergent shocks – ranging from conflict and economic cycles to disasters and climate change – remains low, and this will require a concerted effort to build resilience. Ultimately, the monitoring and evaluation frameworks for both the SDGs and New Urban Agenda will need to enable the localization of action, the tracking of impact using citizen participation and open big data, and the aggregation of results for reporting at the national level.

In spite of the considerable enthusiasm that the SDG, COP 21, and Habitat III processes have generated, it is important to remember that the global urban community is still in its adolescence in terms of local and collective action (Parnell Reference Parnell2016). It would do well to learn from the experience of more mature global constituencies, such as those of health, education, and agriculture, to avoid disciplinary fragmentation and enable the localization of the entire 2030 Agenda. Indeed, localization concerns more SDGs than SDG 11. But the inverse is also true: urbanization is also about more than localization in two key ways. First, as the 20 years between Habitat II and Habitat III have taught us, urbanization is more than governance. Space- and place-based strategies must underpin all of our efforts to shape cities and human settlements. Second, urbanization is wider than the local scale. A focus on the subnational and national scales – as units of spatial inquiry and as levels of governmental intervention – are as important as the local in delivering urban outcomes.

That the 2030 Agenda, Sendai Framework, Addis Ababa Action Agenda, Paris Agreement, and now the New Urban Agenda have happened under UN auspices represents a noteworthy breakthrough. These agreements indicate a validation by the UN of a more universal, proactive approach to sustainable development in general, and urban development in particular. While this approach and the various frameworks and agendas supporting it implicate a much wider range of actors than the UN itself, a full discussion of those actors is beyond the scope of this chapter. Suffice it to say that for these agendas’ aims to be realized, the UN will increasingly have to embrace this full range of actors. As the UN is inherently constrained by its accountability to national governments – and, thus, by competing national interests – this expanded configuration is particularly important. Promisingly, the unprecedented level of consultation with non-UN entities in the formulation of the 2030 Agenda suggests a major shift in modality.

As the world implements the 2030 Agenda, immediate results may be rare and difficult to sustain. However, there are positive signs from some countries – and a moderate number of cities and towns – that are ready to take the plunge to test and further SDG implementation (GLTF et al. 2016; Simon et al. Reference Simon, Arfvidsson, Anand, Bazaaz, Fenna and Foster2016). Building trust, sharing, resources and experiences sharing, and deepening the sense of solidarity and common purpose of key actors and stakeholders at local, regional, national, and global scales will be essential.

References
Aldrich, B., and Sandhu, R. (eds.) (1995) Housing the Urban Poor. London: Zed Books.
Amis, P., and Lloyd, P. (eds.) (1990) Housing Africa’s Urban Poor. Manchester and New York: Manchester University Press for the International African Institute.
Atlas of Urban Expansion (2016) http://atlasofurbanexpansion.org/cities.
Bell, S., and S. Morse (2008) Sustainability Indicators, Measuring the Immeasurable? 2nd Edition. London: Earthscan.
Birch, E. A. Lynch, A., Andreason, S., Eisenman, T., Robinson, J. and Steif, K. 2011. Measuring U.S. Sustainable Urban Development. Penn IUR White Paper on Sustainable Urban Development. http://penniur.upenn.edu/uploads/media/measuring-u-s-sustainable-urban-development.original.pdf.
Gilbert, A. and Gugler, J. (1992) Cities, Poverty and Development: Urbanization in the Third World. Oxford and New York: Oxford University Press.
GLTF, UN Habitat and UNDP (2016) Roadmap for localizing the SDGs: Implementation and Monitoring at subnational level. https://unhabitat.org/roadmap-for-localizing-the-sdgs-implementation-and-monitoring-at-subnational-level/.
Hak, T., Moldan, B., and Dahl, A. (2007) Sustainability Indicators; A Scientific Assessment. Washington, DC: Island Press.
Kanuri, C., Revi, A., Espey, J. and Kuhle, H. (2016) Getting Started with the SDGs in Cities: A Guide for Stakeholders, Sustainable Development Solutions Network (SDSN). http://unsdsn.org/wp-content/uploads/2016/07/9.1.8.-Cities-SDG-Guide.pdf.
Moser, C.O.N., and Peake, L. (eds.) (1987) Women, Human Settlements and Housing. London and New York: Tavistock.
New School (2015) Cities Deliver Sustainable Development. http://livestream.com/TheNewSchool/cities-deliver-sustainable-development
Parnell, S., (2016) Defining a Global Urban Development Agenda, World Development 78: 529540.http://dx.doi.org/10.1016/j.worlddev.2015.10.028.
Parnell, S. and Simon, D. (2014) National Urbanization and Urban Strategies: Necessary But Absent Policy Instruments in Africa, in Parnell, S., and Pieterse, E. (eds.) Africa’s Urban Revolution. London: Zed Books, pp. 237256.
Revi, A. (2016) The New Urban Agenda as an implementation scaffolding for the 2030 Development Agenda in Proc. German Habitat Forum. www.german-habitat-forum.de/assets/bmz_german-habitat_160808.pdf.
Rodwin, L. (ed.) (1987) Shelter, Settlement and Development. London: Allen and Unwin.
Rudd, A., Malone, K., and Bartlett, M. (2017) Participatory Urban Planning in Russ, A. and Krasny, M. (eds.), Urban Environmental Education Review. Ithaca: Cornell University Press.
Sachs, J., Schmidt-Traub, G., Kroll, C., Durand-Delacre, D. and Teksoz, K. (2016) An SDG Index and Dashboard. New York: Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN). www.sdgindex.org.
Satterthwaite, D. (1997) Can U.N. Conferences Promote Poverty Reduction? A Review of the Istanbul Declaration and the Habitat Agenda. Comparative Urban Studies Occasional Paper 14. Washington, DC: Woodrow Wilson International Center for Scholars.
Sendai Framework for Disaster Risk Reduction 2015–2030, www.unisdr.org/files/43291_sendaiframeworkfordrren.pdf.
Shane, D.G. (2011) Urban Design Since 1945: A Global Perspective. Hoboken and Chichester: John Wiley & Sons.
Simon, D., Arfvidsson, H., Anand, G., Bazaaz, A., Fenna, G., K. Foster, et al. (2016) Developing and Testing the Urban Sustainable Development Goal’s Targets and Indicators – A Five-City Study. Environment and Urbanization, 28(1): 4963.
Transforming our World – The 2030 Agenda for Sustainable Development www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E.
Turner, A. (1980) (ed.) The Cities of the Poor. London: Croom Helm.
UN-Habitat (1996) The Habitat Agenda: Istanbul Declaration on Human Settlements http://unhabitat.org/wp-content/uploads/2014/07/The-Habitat-Agenda-Istanbul-Declaration-on-Human-Settlements-2006.pdf.
UN-Habitat (2010a) Chapter 1: Development Context and the Millennium Agenda, in The Challenge of Slums: Global Report on Human Settlements 2003 – Revised and updated version. Nairobi: UN-Habitat. http://unhabitat.org/wp-content/uploads/2003/07/GRHS_2003_Chapter_01_Revised_2010.pdf.
UN-Habitat (2010b) State of the World’s Cities: Bridging the Urban Divide. Nairobi: UN-Habitat.
UN-Habitat (2013) Streets as Public Spaces and Drivers of Urban Prosperity. Nairobi: UN-Habitat.
UN-Habitat (2014) The Evolution of National Urban Policies. Nairobi: UN-Habitat.
UN-Habitat (2015) History, Mandate and Role in the UN System. http://unhabitat.org/about-us/history-mandate-role-in-the-un-system/.
UN-Habitat (2016) Global State of National Urban Policies Report. Nairobi: UN-Habitat.
UN Conference on Housing and Sustainable Urban Development Habitat III (2015) Issues Paper #11 – Public Space, Habitat III, New York. www.habitat3.org/the-new-urban-agenda/issue-papers.
Weiss, T., Carayannis, T., Emmerij, L. and Jolly, R. (2005) UN Voices: The Struggle for Development and Social Justice. Bloomington and Indianapolis: Indiana University Press.
United Nations, Economic and Social Council (2015) Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators. E/CN.3/2016/2/Rev.1 (TBC), http://unstats.un.org/unsd/statcom/47th-session/documents/2016–2-IAEG-SDGs-E.pdf.

1 Later, governments experimented with other urban housing models, including tenant-purchase and site-and-service schemes, often through development cooperation funding. Some of these were strategically located close to business and industry (and have more recently experienced revitalization through public-private partnerships). While some governments were experimenting, however, the private sector took over the lion’s share of housing provision without the benefit of much planning guidance from public authorities.

2 A signal exception has been the very high-density high-rise apartment blocks in Singapore and Hong Kong, in particular, where such social “pathologies” have not emerged and these urban designs appear to have been quite readily assimilated. This has never been adequately explained but cultural acceptability is likely to be important. Shane (Reference Shane2011) provides fuller coverage.

9 See New Urban Agenda, paragraph 164. We stress that the follow-up to and review of the New Urban Agenda must have effective linkages with the follow-up to and review of the 2030 Agenda for Sustainable Development to ensure coordination and coherence in their implementation.

Chapter 10: Utilizing Urban Living Laboratories for Social Innovation

Sandra Naumann , McKenna Davis , Michele-Lee Moore , and Kes McCormick
10.1 Introduction

Cities have long been recognized as potential hubs of knowledge, social and cultural diversity, jobs, education, public services, and infrastructure (see Scott Reference Scott1997; Kong Reference Kong2007; Sassen Reference Sassen2011). Alongside these opportunities, however, cities also face a changing climate, reduced availability of raw materials and natural resources, and dwindling physical space for the built environment. These challenges are accompanied by increasing disparities in income and resultant social inequalities; mounting threats to human health, well-being, and food security; growing refugee and migration influxes; and demographic changes (for example, Coutard et al. Reference Coutard, Finnveden, Kabisch, Kitchin, Matos and Nijkamp2014; Zhou Reference Zhou2000). These concerns and associated governance challenges increase the urgency for new socially, ecologically, and culturally sensitive approaches to urban development. Such approaches need not only to reduce human vulnerability and environmental footprints, but also to build social cohesion and support ecological sustainability, cultural integration, and the establishment of a shared identity between citizens within a just system of distribution and access to urban resources and wealth (Duxbury et al. Reference Duxbury, Hosagrahar and Pascual2016).

Conventional public sector models for urban governance are often unexpected or too overstretched to adequately respond to the severity, urgency, and complexity of the outlined challenges (Kieboom Reference Kieboom2014). Against this framework and a growing movement for citizen participation in governance processes (for example, Lowndes et al. Reference Lowndes, Pratchett and Stoker2001; Bai et al. Reference Bai, McAllister, Beaty and Taylor2010; Rosol Reference Rosol2010), many actors are working to transform urban governance to ensure that a greater diversity of voices are accounted for in decision-making processes and urban initiatives. One of the many ways in which urban actors have begun to (re)organize is via the creation of “urban living laboratories,” or simply “urban living labs.” Such labs exist across North and South America, Africa, Asia, Oceania, and Europe, many of which are connected through an open network organized by the European Network of Living Labs, or ENoLL (see http://openlivinglabs.eu/).

While a shared definition of urban living labs has not yet been agreed upon, they are generally understood to involve collaborative research and urban development activities undertaken alongside the intended end users, exploiting experimental platforms and/or approaches in real time. This both fosters the generation of social and technical innovations and allows for ongoing, continuous analysis to take place so that the lessons learned throughout can be applied to the relevant initiative, as well as to other urban contexts (Voytenko et al. Reference Voytenko, McCormick, Evans and Schliwa2016; Mulder Reference Mulder2012; Schliwa and McCormick Reference 217Schliwa, McCormick, Evans, Karvonen and Raven2016). In the urban context and in relation to this chapter, urban living labs enable citizens and urban actors to create experimental spaces and arenas outside the prevailing governance system as a means to generate novel solutions and engage new actors, collaborations, ideas, and funds.

This chapter explores the role of urban living labs in supporting social and governance innovations that are the subject of social innovation scholarship. That is, this exploration considers how well the practice of creating urban governance innovation aligns with the surrounding theory on the topic. Although different strands of literature have emerged around the concept of social innovation and have varying perspectives and definitions of the term, we draw on a definition rooted in complex systems thinking (see, for example, Westley et al. Reference Westley, Zimmerman and Patton2006; Westley Reference Westley2013). We understand social innovation to be any initiative (including products, processes, programs, projects, policies, or platforms) that challenges and – ultimately – fundamentally alters the defining routines, resource and authority flows, or beliefs of the broader social system in which it was introduced (Westley and Antadze Reference Westley and Antadze2010). In the urban governance sphere, social innovations could entail, for example, innovative social-ecological programs or policies, social finance models, new governance modes, and/or novel forms of cooperation, participation, and partnerships that alter the distribution of authority or knowledge and resource flows (Gonzaléz and Healey Reference González and Healey2005; Geobey et al. Reference Geobey, Westley and Weber2012; Klievnik and Jannsen Reference 216Klievink and Janssen2014). Despite urban living labs being intended as an experimental space and a platform for generating social and governance innovation, theoretical examinations and practical analysis of the intersection of social innovation theory and urban living lab practices are limited.

This chapter contributes to this discussion by introducing a brief history of urban living labs and the governance challenges they are intended to address, and subsequently exploring whether urban living labs hold potential as a new forum for urban governance innovation experiments to support positive transformative change. We begin by reflecting on two recent cases, a living lab in Malmö, Sweden, and the Helle Oase lab in Berlin, Germany, building on current literature to deepen our discussion. Recognizing that urban living labs are a relatively new phenomenon and social innovation processes take many decades, this discussion aims to provide a starting point to improve understanding of how different forms of urban living labs are emerging to address current urban challenges and to explore whether these can serve as a platform for social innovations that are likely to lead to systemic change. Such an analysis can contribute to the development of new research questions and hypotheses. Finally, the potential approaches for integrating new social arrangements that emerge from urban living labs within existing urban governance structures are discussed.

10.2 Limitations of Existing Governance Approaches to Cope with Emerging Urban Challenges

Cities often experience governance challenges similar to those faced at the international, national, and regional levels. Consequently, urban areas are forced to grapple with growing inequality and structural injustices and the restructuring of governing agencies and economies underpinned by neoliberal, market-based approaches (Jessop Reference Jessop2002) that largely fail to deliver “the promised efficiency, voice and service integration gains” for city dwellers (Warner Reference Warner2012). Further challenges include short-term political leadership cycles, competing priorities, budgetary concerns, and an often aging infrastructure that is ill-suited to a changing climate (Birkmann et al. Reference Birkmann, Garschagen, Kraas and Quang2010). In parallel, as Bishop and Davis (Reference Bishop and Davis2002) argue, discontent among citizens about these types of issues has created a strong pressure for all levels of government to adopt participatory processes that ensure a fair and democratic inclusion of previously marginalized voices, enhance transparency and accountability, and improve the management of public services (Grindle Reference Grindle2007). However, participation processes themselves are rife with challenges and may still leave citizen expectations unmet (Bishop and Davis Reference Bishop and Davis2002; Irvin and Stansbury Reference Irvin and Stansbury2004).

This combination of factors has led to both a practical and political need for cities to transform their governance frameworks. While opinions and approaches for how best to accomplish this goal are diverse, it is widely acknowledged that such changes require significant shifts in mindsets, partnership constellations, and approaches to governing urban spaces and relationships (for example, Bos et al. Reference Bos, Brown and Farrelly2015; Seitzinger et al. Reference Seitzinger, Svedin, Crumley, Steffen, Abdullah and Alfsen2012). Resultant governance structures would thus need to be able to contend with complex socioecological systems, the demands and needs of the respective urban populations, and the multiscale issues and interests contained therein.

While some cities have emerged as leaders for creating new and adaptive governance structures and processes which move beyond interests at the local government level, these cases remain limited (examples include the Cities for Climate Change Protection Programme and the Covenant of Mayors for Climate and Energy in the European Union). Where these initiatives of strong leadership and action by cities do exist, they are often undertaken in the absence of, or in direct conflict with, the respective national governments (see Parker and Rowlands Reference Parker and Rowlands2007).

Although governance transitions face a high risk of failure and require innovation and experimentation to be successful, their potential to address current environmental and societal shortcomings can be significant. In this context, some cities have exhibited an openness to becoming arenas for experimentation and social innovation (Bulkeley and Castán Broto Reference 215Bulkeley and Castán-Broto2013) and serve as a reference for generating knowledge about the emergence, development, and institutionalization of innovation for sustainable urban development (Schneidewind and Scheck Reference Schneidewind, Scheck and Rückert-John2013; Evans and Karvonen Reference Evans and Karvonen2014). Urban living labs have emerged as one form of experimental space for social innovation.

10.3 Innovation Pathways for Cities and the Role of Urban Living Labs

Starting mostly as research and development spaces for information and communications technology, the concept of living labs has been credited to William J. Mitchell of MIT (Quak et al. Reference Quak, Lindholm, Tavasszy and Browne2016). The concept gradually expanded and drew on interactive processes with diverse actors to address a range of sustainability issues. While literature on the subject is beginning to flourish alongside the growing prevalence of cities being described as laboratories for social innovation, further in-depth exploration of living labs remains limited (Evans and Karvonen Reference Evans, Karvonen, Bulkeley, Castán Broto, Hodson and Marvin2011, Reference Kieboom2014; König Reference König and König2013; Nevens et al. Reference Nevens, Frantzeskaki, Gorissen and Loorbach2013; Schneidewind and Scheck Reference Schneidewind, Scheck and Rückert-John2013; McCormick et al. Reference McCormick, Anderberg, Coenen and Neij2013).

Urban living labs have continued to evolve; they are now appearing all over the world and are taking on a new scope (see Box 10.1). More recently, living labs have been used as a tool to reinterpret, challenge, and improve urban governance to better address issues of sustainability. Recent initiatives involve, for example, urban stakeholders developing and testing new technologies, governance arrangements, and ways of living (Bulkeley and Castán Broto Reference 215Bulkeley and Castán-Broto2013). Although urban living labs’ physical manifestation may be attached to a defined space, the concept relates more to an approach: intentional collaborative experimentation between researchers, citizens, companies, and local governments (Schliwa and McCormick Reference 217Schliwa, McCormick, Evans, Karvonen and Raven2016).

Box 10.1 Global examples of urban living labs

The Siyakhula Living Lab in South Africa aims to develop and field-test a prototype of a simple, cost-effective, robust telecommunications platform to reach out to marginalized and semi-marginalized communities. Beyond technology and infrastructure provisioning, the lab provides information and communications technology skills development and training, as well as advice and blueprints for networking and software service provisioning (see http://siyakhulall.org/).

The Lots of Green program in Youngstown, Ohio, United States, aims to support and empower local citizens to improve vacant lots and design green spaces to mitigate high rates of violent crime and low property values. Lab members successfully tested two types of vacant lot interventions on crime: a cleaning and greening “stabilization” action and a “community reuse” action mostly involving community gardens (Kondo et al. Reference Kondo, Hohl, Han and Branas2016).

The LivingLab Shanghai, China, is an educational platform promoting innovation for generating societal construction of knowledge that bridges top-down and bottom-up social innovation processes in a real-world context by involving relevant stakeholders. The lab also develops alternative approaches and solutions to complex problems for sustainability in an environment that includes both megacity challenges and nearby rural areas that are resource limited (see www.openlivinglabs.eu/livinglab/livinglab-shanghai).

The Adelaide Living Laboratory, Australia, comprises three property development sites and engages stakeholders to provide pathways for low-carbon living in Adelaide with both local and national significance. The lab focuses on (1) cocreation; (2) integrated energy, water, waste, and transport precinct modeling; (3) energy demand management solutions; and (4) the value proposition for investment in low-carbon development (Berry and Davidson Reference Berry and Davidson2015).

Five key attributes characterize urban living labs (Voytenko et al. Reference Voytenko, McCormick, Evans and Schliwa2016; Quak et al. Reference Quak, Lindholm, Tavasszy and Browne2016; Evans and Karvonen Reference Evans and Karvonen2014). First, geographical embeddedness implies that the labs are embedded in the urban context. Experimentation and learning mean that they involve testing, experimenting, and reflexive learning processes, while participation and user involvement outline the involvement of multiple partners from different sectors and engagement of users and citizens. Fourth, leadership and ownership refer to the labs having a leader or coordinator that shapes the design of the activities. Finally, evaluation and refinement refer to continuous evaluation or assessment that feeds back into improvements, refinements, and learning within the labs.

Researchers are increasingly categorizing urban living labs within frameworks and typologies based on their use of a variety of methods and metrics to support the generation of innovation and learning. For example, Leminen et al. (Reference Leminen, Westerlund and Nyström2012) proposed four types of living labs to capture the range of approaches being employed in cities around the world: utilizer-driven, enabler-driven, provider-driven, and user-driven living labs. These types are defined by the dominant actor in the initial phase of the lab or by the principal promoter of innovation activities later on. They differ in terms of activities, structure, organization, and coordination. Utilizers are often companies applying the living labs approach for product-service system development, enablers are often but not exclusively local governments representing the public sector, providers are mainly research institutions and universities that in some cases host living labs on university campuses (for example, Robinson et al. Reference Robinson, Berkhout, Cayuela, Campbell and König2013), and, finally, users are people or grassroots organizations that often initiate living labs. This basic framework draws attention to the key role played by the leading actor or coordinator in designing and implementing urban living labs.

In the following sections, we investigate two different urban living labs and draw on the literature to complement these findings and frame them within wider theoretical discussions. Our first case is an enabler-driven platform in Malmö, Sweden that focuses primarily on improving the energy efficiency and liveability of existing apartment buildings, reducing greenhouse gas emissions, and increasing social well-being. The second case represents a user-driven initiative utilizing collaborative urban gardening to improve social cohesion in a socially deprived neighborhood in Berlin, Germany. We analyze aspects such as the motivations, existing social perceptions and understandings, as well as the aims, objectives, and approaches for each initiative. This also includes a discussion of the actors involved and institutional structures, impacts, benefits and limitations, and future outlooks. The two examples provide contrasting approaches of urban living labs, with the Malmö case being platform-based and city-led and the Berlin case being project-based and citizen-led (see Table 10.1). Given their small-scale spheres of activity and early stages of development, the case study findings are, to some degree limited in their ability to clarify the connection and interlinkages mentioned; nevertheless, they serve to highlight indicative trends and conclusions for further research and actions at the city level.

Table 10.1 Characteristics of the selected urban living labs

NameLocationChallenges addressedFocusType of urban labActors involved
Malmö Innovation PlatformMalmö, SwedenRejuvenating southeast Malmö (area shaped by former shipping industry)Improving the energy efficiency and livability of existing apartment buildingsPlatform-based, city-led, enabler-drivenCity of Malmö, Region Skåne, universities, entrepreneurs, building owners, residents, schools, and so forth
Helle OaseBerlin, GermanyLack of common green space in a low strata and densely populated areaUrban gardening and social cohesionInitiative-based, community-led, user-drivenLocal residents; supporters, including: district office, local youth group, nature protection association, medicinal school

Case Study 1 Malmö Innovation Platform – Improving the Energy Efficiency and Liveability of Existing Apartment Buildings

A coastal city in the south of Sweden, Malmö, struggled economically in the early post-industrialization years following the collapse of the ship building industry in the 1980s, which led to a range of other social challenges. Recently, however, the City of Malmö has actively worked to address major societal challenges and to increase the sustainability of the city (McCormick and Kiss Reference McCormick and Kiss2015) by supporting a diverse range of innovative projects initiated by the city, citizens, businesses, associations, and academia.

One of these initiatives involves the Malmö Innovation Platform. The City of Malmö assumes the main leadership role in the platform, but is supported by a partnership-based steering group when making major decisions. The steering group consists of the City of Malmö, Region Skåne, Lund University, Malmö University, the Swedish University for Agricultural Sciences, Media Evolution, EoN (an energy company), and MKB (a housing company). Sixteen business organizations participate in the platform, including representatives of the real estate, construction and design, energy services and information technology, and consultancy and innovation sectors.

The platform currently focuses on the renovation of existing apartment buildings in low-medium income areas in the southeast of Malmö as part of the city’s larger efforts towards sustainable development (McCormick and Kiss Reference McCormick and Kiss2015). The area faces a multitude of cultural, social, and economic challenges, including the need to renovate many homes originally constructed as part of Sweden’s “Million Homes Program” in the 1960s. The infrastructure no longer meets efficiency standards, and the overall liveability of these places has become a concern. The initiative pilots and develops new technologies, services, business concepts, and local jobs while also experimenting with different organizational and collaborative setups between businesses, the municipality, and academia for supporting the renovation of buildings (McCormick and Kiss Reference McCormick and Kiss2015).

The platform brings together diverse actors, creates space for discussion on urban (re)development, and supports the creation and implementation of urban experiments, which aim to break away from the “business as usual” paradigm. Initiatives are designed to reorganize and restructure relationships inside Malmö and between the key actors in the platform (see Table 10.2). The platform does not carry out projects or innovations itself, but instead supports their initiation and implementation by bringing together individuals from different organizations and providing starter funds for idea development. Participants share experiences and knowledge gained from the supported projects via the platform, where those experiences are evaluated and, ideally, utilized in new projects (McCormick and Kiss Reference McCormick and Kiss2015). Platform participants are also attempting to embed technical experiments in a broader discussion about the social organization of the city and the flows of authority and resources.

Table 10.2 Examples of projects supported by the Malmö Innovation Platform

ProjectsDescription
District heatingEoN (an energy company) performs renovations to district heating systems in existing apartment buildings to test if significant improvements can be made and what benefits for residents might be achieved
Every dropMKB (a housing company) aims to reduce hot-water usage in apartments by influencing behavior; MKB transfers saved funds into local schools, thereby strengthening the local community and the schools
Recycling centers with maker-spacesVA Syd (a waste management company) and Malmö University test the potential to combine local recycling centers by reusing materials and “waste” in shared maker-spaces
Local jobsTrianon (a building owner) puts demands on building companies by including a “social clause” in their building contracts requiring the employment of local people in renovation and building projects

Ownership of the initiatives is shared by the companies participating in the platform. A key motivation for companies to engage is the enabling of new partnerships and opportunities. All companies invest time and resources into the activities. At the project level, participation goes beyond the partners in the platform and encompasses residents and local organizations, such as schools, community groups, and housing associations.

Impacts, Benefits, and Limitations

The Malmö Innovation Platform initially focused less on results and more on identifying the key questions for socioeconomic development in the city, and on developing and enabling collaborative processes, which are challenging to evaluate. To date, the main impact of the platform is the creation of a meeting space for diverse urban stakeholders in which they can share perspectives on challenges, understand the problems from different perspectives, and feed this new knowledge into the process of developing innovative solutions. The platform also serves to integrate projects or experiments which were previously considered as discrete units, by highlighting the lessons learned and using these to inform the development of new initiatives. The convening and coordinating function is necessary, but is in itself is not a governance innovation that transforms the existing urban governance regime. Thus, questions remain whether this is sufficient to lead to a governance innovation.

The Malmö Innovation Platform has initiated over 50 projects since its inception. While its ambitions are clear, a need remains to better structure evaluation processes to ensure that the platform meets its own objectives. Although companies clearly use the platform to test creative solutions and learn from successes and failures, the transferability of the initiatives is difficult to assess. Moreover, it is challenging to determine if this platform supports a step away from “business as usual” or whether it reinforces a pattern of creative elite experimentation which has often led to challenges associated with gentrification (Peck Reference Peck2005). A key aspect going forward will be to continue to develop the platform so it remains relevant and useful for participating partners and for marginalized communities who are currently not represented by the partnership in the long term.

Outlook and Future Directions

The second phase of the Malmö Innovation Platform began in 2016 and will broaden the geographic scope of the lab across the entire city. It will attempt to tackle many of the barriers identified in the first phase, such as financing new projects (through the provision of some funding for pilot projects) and better connecting citywide visions with experiments and collaborative activities cutting across the government, businesses, community, and academia.

As part of this development, the Sustainable City Accelerator has been established to support innovative players from all sectors in the application of new sustainable urban development solutions. The accelerator will purportedly support the analysis of challenges around Malmö, establish partnerships with the key stakeholders, owners, and clients; develop ideas and solutions of a technical, social, digital, and organizational character; and test and implement solutions in the physical urban development in the city. Innovators from the private, public, and voluntary sectors as well as academia will be able to use the accelerator as an arena for the development of ideas and collaborations. Thus far, however, the discussions have utilized a positive framing about “diversity” and “collaboration” without widely acknowledging the power asymmetries and ways in which such lab processes may disadvantage those without technical knowledge about building construction or about technological innovation.

Case Study 2 Helle Oase, Berlin, Germany – Creating Social Cohesion through Collective Gardening

Helle Oase is a 4,000-square-meter urban permaculture garden for local residents initiated in 2012 in Berlin, Germany. It is the only urban garden in the city and is located in a prefabricated housing (Plattenbau) estate in Berlin-Hellersdorf, which is a densely populated and highly developed area. The area is also known for its low social strata, high unemployment (particularly among young people), and low incomes. The initiative provides an opportunity for collective gardening, creates an open and positive space for the community, and acts as a meeting point for residents. The citizen garden is a multifunctional space containing not only cultivated plots and fruit trees, but also a sitting area for gardeners, a playground, hammocks, a soccer field, and walkable pathways.

Berlin-Hellersdorf is characterized by large and monotonous prefabricated housing estates, resulting in a comparably dense residential area. As is often the case in urban areas, this community is disconnected from food production processes and nature and lacks agricultural land. A centrally located area of fallow land offered a great opportunity to create a place where residents could stay and spend time with their previously unknown neighbors, thereby also gaining a sense of stability and calm to counteract their often troubled daily lives (Albrecht and Lohr Reference Albrecht and Lohr2015).

Inspired by British urban gardening projects, Helle Oase was initiated by a single individual with support from a core group of other local residents. In order to build a sense of community and to strengthen social cohesion among the residents in the area, these founders emphasized stimulating and maintaining social interactions. Albrecht and Lohr (Reference Albrecht and Lohr2015) found that there is a very high level of cooperation through shared norms and values within the project. These repeated social interactions have helped to build trust and enable participants to build a shared identity.

The garden is open to everyone, regardless of an individual’s socioeconomic background or ability to participate regularly. Participants are, however, asked to abide by some basic common principles. For example, the burden of work and harvest is to be shared equally. Moreover, any occurring problems are encouraged to be solved in a conflict-free manner.

Helle Oase is supported by a vital network, which is spread across different bureaucratic levels and types of institutions and organizations, including the district office, a local youth group and a nature protection association, a medicinal school, the larger neighborhood, and the core group of residents. The physical area is formally owned by a state-owned real estate agency (Berlin Liegenschaftsfond), but Helle Oase holds the user management rights on a temporary basis. Communication between the gardeners is managed via weekly face-to-face meetings, time spent working together in the garden, and a website. Moreover, the Helle Oase core group interacts with the neighboring community via online and personal invitations to garden parties, informal talks with passers-by, workshops, and employee-friendly gardening hours. The initial funding for Helle Oase was provided by a national European Social Fund program, which ended in 2014, creating the need for alternative financing via a donation platform.

Impacts, Benefits, and Limitations

Although from the outside it may appear to be a simple urban gardening initiative, the Helle Oase is an urban living lab because of its creation of a garden that aims to serve as an experimental space to reveal and test new paths and means for creating social cohesion within a socially deprived area. It also enforces reflexive learning processes by applying simple but common principles in the newly created, common green space.

In addition to the production of low-value physical goods (food, flowers, and herbs), the Helle Oase provides social and educational benefits. For example, the garden serves as a vital and attractive community space; creates a sense of community and group spirit; evokes a high level of identification with the project; increases social cohesion and earned social capital through an open and constructive process to solve problems and make joint decisions; and enhances the process of mutual learning. Finally, the garden creates a high level of cooperation and trust among the participants and serves as an educational tool for spreading knowledge about sustainable gardening. Further, Helle Oase contributes to ecological sustainability and has a positive impact on biodiversity. It is worth noting that these benefits might be restricted to some individuals, or may not be able to be fully explored due to the limited number of actively participating gardeners, or potential conflicts in sharing or stealing the harvest, or vandalism in the relaxation area (Albrecht and Lohr Reference Albrecht and Lohr2015).

The user-driven Helle Oase lab may not have the capacity to change established routines and enable broader societal transformation to the political or authoritative system, but it is nevertheless noteworthy given its emphasis on trust and cooperation building. These processes often require long periods to progress. However, larger transformation processes to improve social cohesion and build social capital (particularly in socially deprived areas) require political support throughout the city. Such action could significantly contribute to the development of new urban community models that are driven by local residents and local interest groups. For these reasons, the Helle Oase case is highly relevant within social innovation discourse, as it represents a valuable example of the many grassroots initiatives appearing in cities across the world.

Outlook and Future Directions

Initiatives such as Helle Oase can provide cost-efficient and viable socioecological solutions to problems associated with densely populated built areas, such as low social strata, unemployment, lack of social cohesion and community sensibility, heterogeneity of citizens, and high crime rates. Conversely, such labs require a relatively high level of social commitment by motivated local residents and the ongoing support of local and regional actors. Regular financial support as well as long-term management (or even property) rights to use open spaces in the community are also key to ensure its sustainability.

This initiative has the potential to be replicated or transferred to other densely populated built areas. Helle Oase has not yet produced follow-up initiatives within Berlin, in part because of the established, vital urban gardening scene which already exists in Berlin. Key challenges looking towards the future include the temporary nature of the contract with the district office, insecure financial support (European funding for Helle Oase ended in 2014; the organization has since relied mainly on donations), and the need for more engaged participants across which the workload associated with the initiative can be better distributed.

10.4 Bridging the Gap between Public Policy, Governance, Urban Living Labs, and Social Innovation

These two illustrative and distinct cases demonstrate that urban living labs can provide a protected space for experimentation and for forming creative collaborations that can, in turn, foster different approaches to resolving societal problems. While these developments potentially lay the foundation on which social innovation processes can emerge, our analysis demonstrates their failure to propel true systemic change in ways coherent with the provided definition of social innovation. In this regard, neither of the case studies has led to any fundamental changes in the defining resource and authority flows or beliefs of the broader social system in which they were introduced. Reasons for these failures may link to the infancy of these initiatives, the lack of political support, and insufficient integration into existing structures (in the Berlin case), or the lack of connecting technical innovations to create new social opportunities (in the Malmö case).

We therefore highlight the need for additional research on the relationship of urban living lab initiatives to overall urban governance. In particular, the following aspects are suggested to be pursued: whether the existing lab forms are truly fostering governance innovations that will create large-scale systemic change, and what the critical success factors and realistic timespan entail. More specifically, there remains a pressing need to answer the questions: How can newly created social arrangements be integrated within existing (political) governance structures to maximize effectiveness in responding to current urban challenges and turn into social innovations that enable true changes within existing governance systems? Can such successful experimental initiatives developed in urban labs move from small-scale, niche positions to a broader scale? What conditions would be required to facilitate such a move? Although the evidence from the case studies and available literature has provided only insufficient answers to these multifaceted issues to date, an array of interesting insights can be discussed in light of existing literature and pursued further in future research in this field.

For social innovations to emerge, develop, and stabilize, a set of coalition-building opportunities for actors and certain framework parameters must be present (such as the institutional context, welfare regime context, and local political culture) (Cattacin and Zimmer Reference Cattacin, Zimmer, Brandsen, Cattacin, Evers and Zimmer2016). In this context, urban living labs may offer a platform and a flexible approach to start building such coalitions and to increase connectivity among different actors within the urban area, which will be necessary for more systemic transformative changes (see Westley et al. Reference Westley, Zimmerman and Patton2006; Westley Reference Westley2013). Those innovations that do emerge may be integrated into existing governance systems with various degrees of difficulty. While the Helle Oase still requires strong support and political will at the municipal level, the Malmö Innovation Platform has already been promoted by the local government, demonstrating that different organizational configurations may create better access to the political will that can inevitably be necessary for addressing complex challenges. However, this hypothesis requires further testing with additional cases.

Moreover, existing urban governance scholarship has determined that governance regimes embedded in a federal system or in systems applying the subsidiarity principle are likely to facilitate the greatest emergence and sustainability of social innovations because the local level is in a position to address social challenges independently.Footnote 1 Cattacin and Zimmer (Reference Cattacin, Zimmer, Brandsen, Cattacin, Evers and Zimmer2016) found that local self-government and cooperation with nonstate actors such as civil society organizations show a higher level of openness and likelihood for social innovations. In this context, it is promising to see that urban governance increasingly involves nongovernmental actors from civil society and private businesses – a practice in line with the core features of urban living labs (Gerometta et al. Reference Gerometta, Häussermann and Longo2005). The Malmö Innovation Platform represents, for example, a new interface and form of cooperation between the city and nonstate actors, and is actively engaging with partners to enable sustainability interventions. Such new partnerships and modes of governance can also facilitate significant sharing of knowledge and cultivation of learning processes. In this context, both cases from Malmö and Berlin reveal that urban living labs do not necessarily challenge the existing governance structures. Rather, the experiments act as learning platforms for new urban knowledge, which may eventually inform systemic governance change.

In European cities, Brandsen et al (Reference Brandsen, Cattacin, Evers, Zimmer, Brandsen, Cattacin, Evers and Zimmer2016). found that initiatives that remain separate from or insufficiently integrated into urban policies are potentially limited in their expected impacts and ability to address current societal challenges. Social innovations that both complement existing urban development strategies and can contribute to making the respective cities more dynamic and attractive are more likely to be accepted, supported by local governments, and integrated into local welfare administrations securing their sustainability (García-Sánchez and Prado-Lorenzo Reference García-Sánchez and Prado-Lorenzo2009). However, even in these cases, it is not guaranteed that true impacts on the system will occur.

Innovative initiatives focusing on vulnerable groups living on the fringes of urban society and dealing with social inequities are unfortunately accorded less attention under urban development strategies and political agendas, and are commonly affected by budget cuts. In the specific case of Helle Oase – and as revealed by Ewert (Reference Ewert, Brandsen, Cattacin, Evers and Zimmer2016) – public funding for innovative capital may diminish in the near future for social innovations, emphasizing the need to develop and establish a new system to enable cooperation between the political administrative system and social innovations. These conditions may also weaken the capacity of cities to integrate such new developments thoroughly into public policies, thereby diminishing their potential to transform into social innovations. Research on urban living labs needs to continue to track whether urban living lab initiatives continue to rely on existing governance mechanisms, such as funding from local governments, or whether they turn to using their platforms themselves to create innovative approaches to financing their initiatives. A host of critiques could emerge from either of those approaches, and the risk is that neither leads to transformative changes responding to identified needs.

Overall, there seems to be a trend of shifting from a hierarchical model of governance to a heterarchical, more participatory structure in cities (Hohn and Neuer Reference Hohn and Neuer2006). This progression may enable a better horizontal integration of new, nonpublic actors that can provide services for urban society at a large scale. In this context, it is essential that the involved actors recognize each other’s roles in the creation of a workable urban society (Cattacin and Zimmer Reference Cattacin, Zimmer, Brandsen, Cattacin, Evers and Zimmer2016) by creating respect, trust, and even responsibilities and power. Gerometta et al. (Reference Gerometta, Häussermann and Longo2005) go further and suggest that the state should instead adopt an enabling and stimulating role, maintaining responsibility for central problems of societal welfare while promoting an environment for civil society organizations and the private sector to fuel social innovations and contribute to sustainable urban development. The Malmö Innovation Platform illustrates how such a vision can be achieved, given its strong support from the local city government and its function as a connector of entrepreneurs, property owners, and local residents who want to pursue sustainable urban transformation processes. However, this approach can neglect to confront the potential asymmetrical power dynamics existing in urban areas, requiring that we be more specific when talking about how this represents system transformation, not just a perpetuation of governing approaches that have created inequalities in the first place. Therefore, further research is needed to assess the potential of government-led urban living labs.

The integration of emerging social innovative initiatives and arrangements into existing governance structures to respond effectively to current urban problems remains a challenging endeavor. Nevertheless, we can highlight a few promising outcomes. The capacity of civil society and its networks to develop and establish solutions to current societal challenges and to contribute to more sustainable, liveable, and cohesive cities – as well as to the urban governance arrangements that promote them – should be acknowledged by state and city governments. Making explicit use of self-organization and civil society initiatives (Gerometta et al. Reference Gerometta, Häussermann and Longo2005) as part of the official urban development agenda and respective action plans, as well as providing room for experimentation, such as through urban living labs, can not only enrich the urban development agenda, but can also contribute to its achievement.

Further actions to enable social innovations and their integration into existing structures may entail a transfer of responsibilities and power to non-state actors and enable a thorough and equal participation of civil organizations across all social strata (for example, ensuring everyone is equipped with voting rights) in local policy processes. The examples of initiatives in Malmö and Berlin do not suggest a transfer of power, but rather attempts to better engage local communities. There is, however, an underlying question of power dynamics. Overall, frequent dialogue and exchange between private companies and business, civil society, and city government should take place (for example, via round tables) to inform public and legal decision-making and strategic decisions at the state and city levels. Urban living labs are a platform for such dialogue and collaborative activities that can span multiple organizations and sectors. Still, urban living labs should try to embed their practices in the systems that they seek to change, should rethink current modes of governing in urban systems, and should approach public authorities to discuss the integration and uptake of their activities (Kieboom Reference Kieboom2014).

10.5 Outlook

The outlined case studies offer a small taste of the wide variety of urban living labs and their potential to tackle various societal challenges, including environmental, economic, cultural, and social issues. There remains a clear need to consider how localized, discrete initiatives such as urban living labs amount to larger, system-level change or to transformations in urban governance arrangements (that is, social innovations) and what the critical success factors behind them are. Although urban living labs have proliferated across the world in recent years and have proven to be a valuable and innovative approach to developing new products and platforms for convening and coordinating, it remains too early to determine whether the additive effects of the diversity of technical innovations and collaborative approaches will equate to the change necessary to achieve urban sustainability. However, the examples and literature presented in this chapter suggest considerable potential for urban living labs to contribute to the development of more sustainable cities, increased social justice, and the development of a system which is better prepared to handle future societal and environmental challenges.

References
Albrecht, S., and Lohr, K. 2015. Taking Elinor to the Gardens. Analysing Collective Action Variations in Urban Gardening. www.youtube.com/watch?v=3YhBpQoyZ3M
Bai, X., McAllister, R.R., Beaty, R.M., and Taylor, B. 2010. Urban Policy and Governance in a Global Environment: Complex Systems, Scale Mismatches and Public Participation. Current Opinion in Environmental Sustainability, 2(3): 129135.
Berry, S., and Davidson, K. 2015. Adelaide Living Laboratory Value Proposition: Literature Review. University of South Australia. Report for CRC Low Carbon Living
Birkmann, J., Garschagen, M., Kraas, F., and Quang, N. 2010. Adaptive Urban Governance: New Challenges for the Second Generation of Urban Adaptation Strategies to Climate Change. Sustainability Science, 5(2): 185206.
Bishop, P., and Davis, G. 2002. Mapping Public Participation in Policy Choices. Australian Journal of Public Administration, 61(1): 1429.
Bos, J.J., Brown, R.R., and Farrelly, M. 2015. Building Networks and Coalitions to Promote Transformational Change: Insights from an Australian Urban Water Planning Case Study, Environmental Innovation and Societal Transitions, 15: 1125.
Brandsen, T., Cattacin, S., Evers, A., and Zimmer, A. 2016. Introduction in Brandsen, T., S. Cattacin, A. Evers, and A. Zimmer (eds.), Social Innovations in the Urban Context. Cham, Heidelberg, New York, Dordrecht, London: Springer Open, pp. 320.
Bulkeley, H., and Castán-Broto, V.C. 2013. Government by Experiment? Global Cities and the Governing of Climate Change. Transactions. Institute of British Geographers, 38: 361375.
Cattacin, S., and Zimmer, A. 2016. Urban Governance and Social Innovations in Brandsen, T., S. Cattacin, A. Evers, and A. Zimmer (eds.), Social Innovations in the Urban Context. Cham, Heidelberg, New York, Dordrecht, London: Springer Open, pp. 2130.
Coutard, O., Finnveden, G., Kabisch, S., Kitchin, R., Matos, R., Nijkamp, P., et al. 2014. Urban Megatrends: Towards a European Research Agenda: A Report by the Scientific Advisory Board of the Joint Programming Initiative Urban Europe. www.arrs.gov.si/sl/medn/urbana/inc/JPI-Urban-Europe-Megatrends-Report.pdf
Duxbury, N., Hosagrahar, J., and Pascual, J. 2016. Why Must Culture Be at the Heart of Sustainable Urban Development? UCLG. www.acpculturesplus.eu/sites/default/files/2016/02/19/agenda_21_for_culture_why_must_culture_be_at_the_heart_of_sustainable_urban_development.pdf
Evans, J., and Karvonen, A. 2011. Living Laboratories for Sustainability: Exploring the Politics and Epistemology of Urban Transition in H. Bulkeley, V. Castán Broto, M. Hodson, and S. Marvin (eds.), Cities and Low Carbon Transitions. Routledge, London: 126141.
Evans, J., and Karvonen, A. 2014. “Give Me a Laboratory and I Will Lower Your Carbon Footprint!” – Urban Laboratories and the Pursuit of Low Carbon Futures. International Journal of Urban and Regional Research, 38 (2): 413430
Ewert, B. 2016. Poor But Sexy? Berlin as a Context for Social Innovation in Brandsen, T., S. Cattacin, A. Evers, and A. Zimmer (eds.), Social Innovations in the Urban Context. Cham, Heidelberg, New York, Dordrecht, London: Springer Open, pp. 143160.
García-Sánchez, I. and Prado-Lorenzo, J. 2009. Decisive Factors in the Creation and Execution of Municipal Action Plans in the Field of Sustainable Development in the European Union. Journal of Cleaner Production, 17(11): 10391051.
Gerometta, J., Häussermann, H., and Longo, G. 2005. Social Innovation and Civil Society in Urban Governance: Strategies for an Inclusive City. Urban Studies, 42( 11): 20072021.
Geobey, S., Westley, F. R., and Weber, O. 2012. Enabling Social Innovation through Developmental Social Finance. Journal of Social Entrepreneurship, 3(2): 151165.
González, S., and Healey, P. 2005. A Sociological Institutionalist Approach to the Study of Innovation in Governance Capacity. Urban Studies, 42 (11): 20552069
Grindle, M.S. 2007. Going Local. Decentralization, Democratization, and the Promise of Good Governance. Princeton: Princeton University Press.
Hohn, U., and Neuer, B. 2006. New Urban Governance: Institutional Change and Consequences for Urban Development. European Planning Studies, 14(3): 291298.
Irvin, R.A., and Stansbury, J. 2004. Citizen Participation in Decision Making: Is It Worth the Effort?. Public Administration Review, 64(1): 5565.
Jessop, B. 2002. Liberalism, Neoliberalism, and Urban Governance: A State–Theoretical Perspective. Antipode, 34(3): 452472.
Kieboom, M. 2014. Lab Matters: Challenging the Practice of Social Innovation Laboratories. Amsterdam: Kennisland. Licensed under CC-BY.
Klievink, B., and Janssen, M. 2014. Developing Multi-Layer Information Infrastructures: Advancing Social Innovation through Public-Private Governance. Information Systems Management 31: 240249
Kondo, M., Hohl, B., Han, SH., and Branas, C. 2016. Effects of Greening and Community Reuse of Vacant Lots on Crime. Urban Studies, 53(15): 32793295, DOI: 10.1177/0042098015608058
Kong, L., 2007. Cultural Icons and Urban Development in Asia: Economic Imperative, National Identity, and Global City Status. Political Geography, 26(4): 383404.
König, A. 2013. Conclusion: A Cross-Cultural Exploration of the Co-Creation of Knowledge in Living Laboratories for Societal Transformation across Four Continents, in König, A. (ed.) Regenerative Sustainable Development of Universities and Cities – The Role of Living Laboratories. Cheltenham: Edward Elgar.
Leminen, S., Westerlund, M., and Nyström, A.G. 2012. Living Labs as Open-Innovation Networks. Technology Innovation Management Review, September: 611.
Lowndes, V., Pratchett, L. and Stoker, G. 2001. Trends in Public Participation: Part 1–Local Government Perspectives. Public Administration, 79(1): 205222.
McCormick, K., Anderberg, S., Coenen, L., and Neij, L. 2013. Advancing Sustainable Urban Transformation. Journal of Cleaner Production, 50: 111. doi:10.1016/j.jclepro.2013.01.003
McCormick, K. and Kiss, B. 2015. Learning through Renovations for Urban Sustainability: The Case of the Malmö Innovation Platform. Current Opinion in Environmental Sustainability, 16: 4450.
Mulder, I., 2012. Living Labbing the Rotterdam Way: Co-Creation as an Enabler for Urban Innovation. Technology Innovation Management Review, 2(9): 39.
Nevens, F., Frantzeskaki, N., Gorissen, L., and Loorbach, D. 2013. Urban Transition Labs: Co-Creating Transformative Action for Sustainable Cities. Journal of Cleaner Production, 50: 111122. doi:10.1016/j.jclepro.2012.12.001
Parker, P., and Rowlands, I. H. 2007. City Partners Maintain Climate Change Action Despite National Cuts: Residential Energy Efficiency Programme Valued at Local Level. Local Environment 12.5: 505517.
Peck, J. 2005. Struggling with the Creative Class. International Journal of Urban and Regional Research, 29(4):740770.
Quak, H., Lindholm, M., Tavasszy, L. and Browne, M. 2016. From Freight Partnerships to City Logistics Living Labs–Giving Meaning To The Elusive Concept Of Living Labs. Transportation Research Procedia, 12: 461473.
Robinson, J., Berkhout, T., Cayuela, A., and Campbell, A. 2013. Next Generation Sustainability at the University of British Columbia: The University as Societal Test-Bed for Sustainability, in König, A. (ed.) Regenerative Sustainable Development of Universities and Cities: The Role of Living Laboratories, Cheltenham: Edward Elgar, pp. 2748. DOI 10.4337/9781781003640.00009
Rosol, M. 2010. Public Participation in Post-Fordist Urban Green Space Governance: The Case of Community Gardens in Berlin. International Journal of Urban and Regional Research, 34(3): 548563.
Sassen, S. 2011. Cities in a World Economy. Washington, DC: Sage Publications.
Schliwa, G., and McCormick, K. 2016. Living Labs: Users, Citizens and Transitions, in Evans, J., Karvonen, A. and Raven, R. (eds.), The Experimental City, London: Routledge, pp. 163178.
Schneidewind, U., and Scheck, H. 2013. Die Stadt als ”Reallabor” für Systeminnovationen, in Rückert-John, J. (ed.), Soziale Innovation und Nachhaltigkeit. Wiesbaden: Springer Fachmedien., pp. 229248. http://dx.doi.org/10.1007/978–3-531–18974-1_12
Scott, A.J. 1997. The Cultural Economy of Cities. International Journal of Urban and Regional Research, 21(2): 323339.
Seitzinger, S.P., Svedin, U., Crumley, C.L., Steffen, W., Abdullah, S.A., Alfsen, C., et al. 2012. Planetary Stewardship in an Urbanizing World: Beyond City Limits. Ambio, 41(8): 787794
Voytenko, Y., McCormick, K., Evans, J., and Schliwa, G. 2016. Urban Living Labs for Sustainability and Low Carbon Cities in Europe: Towards a Research Agenda. Journal of Cleaner Production, 123 (2016): 4554
Warner, M.E. 2012. Privatization and Urban Governance: The Continuing Challenges of Efficiency, Voice and Integration. Cities, 29: S38S43.
Westley, F.R., and Antadze, N. 2010. Making a Difference: Strategies for Scaling Social Innovation for Greater Impact. The Innovation Journal: The Public Sector Innovation Journal, 15(2): 2.
Westley, F.R., Zimmerman, B., and Patton, M.Q. 2006. Getting to Maybe: How the World Is Changed. Toronto: Vintage Canada.
Westley, F.R. 2013. Social Innovation and Resilience: How One Enhances the Other. Stanford Social Innovation Review, 11(3): 68.
Zhou, X. 2000. Economic Transformation and Income Inequality in Urban China: Evidence from Panel Data. American Journal of Sociology, 105(4): 11351174.

1 Through cross-national comparative research (77 social innovation cases in 20 European cities), the WILCO (Welfare Innovations at the Local Level in Favour of Cohesion) project examined how local welfare systems affect social inequalities and favor social cohesion with a special focus on the missing link between innovations at the local level and their successful transfer and implementation to other settings. See http://www.wilcoproject.eu

Chapter 11: Can Big Data Make a Difference for Urban Management?Footnote 1

Ulrich Mans , Sarah Giest , and Thomas Baar
11.1 Introduction

The term “big data” has emerged as a powerful technology trend affecting many aspects of life. Since the early days of big data applications in science and various commercial sectors, the term has come to refer to the exponential increase in the volume and variety of data available, as well as the availability of new tools and approaches to process ever more complex data. Reflecting its global impact on societies, the United Nations speaks of a “Data Revolution” (UN IAEG 2014). Within several domains, big data are already being applied with success. The increased availability of consumer data, for example, provides new opportunities for business and commercial enterprises to develop targeted advertisements and increase revenues (Mayer-Schönberger and Cukier Reference 237Mayer-Schönberger and Cukier2013). Big data have facilitated major scientific breakthroughs in various academic disciplines including healthcare, environmental studies, and physics (Krumholz Reference Krumholz2014; Bryant et al. Reference Bryant, Katz and Lazowska2008). In the public policy realm, the collection and processing of personal data has already transformed intelligence and surveillance practices (Lyon Reference Lyon2014). Law enforcement is another field that has experienced a growing number of experiments in data-driven innovations, such as fraud detection, crime fighting, and violence (Technopolis et al. 2015).

Given the above-average connectivity in urban areas, cities lie at the heart of the trend towards data-driven approaches for confronting societal challenges (Barber Reference Barber2013; Thakuriah et al. Reference Thakuriah, Tilahun and Zellner2015). With more than half of the world’s population residing in cities and more than 90 percent of the population growth through 2050 expected to occur in urban areas, there is increased pressure to look for data-driven solutions in the urban context (Pfeffer et al. Reference Pfeffer, Verrest and Poorthuis2015). This holds particularly true for cities in the Global South, where urban sprawl represents a major impediment to sustainable development. Since the 1970s, low-income cities have experienced a 325 percent population increase. In Latin America alone, 110 million people out of 558 million urbanites live in slums, or so-called no-go areas, where basic municipal utility and service delivery remain scarce (de Boer Reference de Boer2015; Muggah Reference Muggah2015; see also Chapters 7, 8, and 9). In this context, recent studies emphasize that “cities … are unable to respond to the needs of their growing populations faced with rising violence, crime, and poverty” (Mancini and Súilleabháin Reference Mancini and Súilleabháin2016: III). Urban scholars argue that many cities are set to struggle with income and social inequality; youth unemployment; homicide and criminal violence; poor access to key services; high concentrations of, or preexisting, violence; and exposure to environmental threats (Muggah and Diniz Reference Muggah and Diniz2013).

To date, most big data applications in the urban context have centered on the quick wins of managerial practices. For example, data analytics are being used in a variety of urban policy sectors, such as public health or infrastructure improvements. These schemes are often driven by cost-saving considerations (Batty Reference Batty2013), while there is much less movement vis-à-vis the underlying dynamics of urban life and policies aimed at improving social cohesion. Applications are also mostly occurring in OECD countries, where data generation to date is still much more meaningful than in data-poor regions: Using mobile phone records to improve public transport, for example, is only viable once a certain threshold of mobile phone users and representation across the population has been reached. Such an effort makes sense in affluent cities, but not (yet) in urban agglomerations where the digital infrastructure and connectivity are more nascent. At the same time, there is an increasing number of experiments in the developing world, where new data sources are being collected and analyzed for the public good (Bellagio Big Data Workshop Participants 2014).

This chapter aims to contribute to this emerging discourse about how big data can improve urban policy-making, and focuses on the role that this technology can play in building more inclusive cities in the Global South. The authors highlight the need for urban authorities to invest in additional resources as well as meaningful knowledge transfer mechanisms that are in line with the concept of “mobile urbanism.” This is particularly important in low-income cities, where policy-makers are driven by the desire to address urban violence and to build more inclusive cities across different constituencies.

11.2 Managing the City in a Digital Age

Data in the urban context can be used in various ways and are applicable to diverse settings. An analysis of 58 initiatives worldwide, performed by Technopolis, the Oxford Internet Institute, and Centre for European Policy Studies in 2015, shows that the most widespread use of data relates to agenda setting and/or problem analysis. The same study found that open data were commonly used for transparency, accountability, and increasing participation, whereas administrative and statistical data were used for implementation and monitoring purposes (Technopolis et al. 2015). To understand these applications, we clustered them into three dimensions: data, processes, and community.

11.2.1 Dimensions of Big Data in the Urban Context

First, big data are about the availability of data as a source of information and, ultimately, knowledge. The proliferation of information and communication technologies has led to a data surge. Datasets have become so large and complex that traditional tools and approaches are often inadequate for processing them. While the volume of data that is becoming available is an issue, three additional challenging characteristics of the new complexities of digital data streams are velocity (speed of data streams); variety (unstructured versus structured data streams); and veracity (quality of data) (Soubra Reference 238Soubra2012). Some have added a number of other Vs, such as viability, for contexts in which reliable data collection is extremely difficult (Mans and Baar Reference Mans and Baar2014).

Second, big data relate to the development of new tools and practices in order to collect, analyze, and work with this digital information (Mayer-Schönberger and Cukier Reference 237Mayer-Schönberger and Cukier2013). King (Reference King2013) argues that big data are about the processes through which we can generate knowledge. Challenges include capturing, verifying, cleaning, storing, sharing, searching, analyzing, visualizing, and presenting the data. In order to infer information and knowledge from data, new disciplines and practices have started to emerge. Such data sciences are producing highly automated approaches, such as machine learning and pattern recognition. In many instances, however, the interpretation of data is unlikely to be taken over by automatic processes; there are growing concerns about the limitations to technically mediated solutions (see, for example, Latonero et al. Reference Latonero, Kleinman and Hiatt2017). Instead, there is a need for hybrid sets of skills that combine human and machine intelligence for supporting policy decisions.

Third, the growing interest in big data has created a new community around digital pioneers, which represents a paradigmatic shift in how a diverse set of stakeholders interacts (Letouzé et al. Reference Letouze, Vinck and Kammourieh2015). In a hyper-connected world, the design and implementation of data-driven innovations are incredibly complex and lead to a shift of existing power balances: data sources are becoming more decentralized and analytical tools more accessible to the wider public. As a result, there are limits to the level of “control” that public authorities have over what happens within local policy networks. At the national level, we already see a myriad of citizen networks starting to engage in decision-making processes through data-driven innovations.Footnote 2 We also observe a growing number of professionals in the public policy domain that are warming up to the possibilities that data can bring for improving service delivery to citizens (see Chapter 10). In other words, policy-making in a digital age calls for a more active involvement of new (often loosely connected) stakeholders – such as civil society, private enterprises, or private citizens that hold or produce relevant data (WEF 2015a) – which are able to collect, process, validate, and interpret these newly available types of data.

Big data should therefore be understood as a phenomenon bringing together a large variety of stakeholders that individually or collectively engage in the processes that determine how data are collected and used for, among other things, policy goals. Here, it is important to differentiate between data-driven and data-informed policy. Rather than relying on data alone, the term “data-informed policy” refers to decisions that include data as just one factor, coupled with more qualitative judgments about context and potential risks.

The following section presents the academic discourse on knowledge management in cities that applies in the context of data-driven innovation. The subsequent sections look at the different data types that shape the Data Revolution landscape and reflect on their potential benefits. We base this reflection on two case studies that highlight the intricacies of knowledge transfer for effective integration of data-driven innovation into urban policy development: data-informed policy.

11.2.2 Addressing the Urban Knowledge Gap

With the emergence of a large variety of data streams that offer (real time) information on what happens in the city, urban authorities around the world have started to explore new opportunities for improving traffic oversight, service delivery, or crime fighting. At the same time, there are limitations to data-driven innovation. Major barriers are the lack of capacity to apply the insights derived from big data and the inability to effectively inform decision-making using big data in specific cases. To date, many local governments are not equipped for using big data; therefore, capacity-building is considered a pressing challenge (van Edwijk et al. Reference van Edwijk, Baud, Bontenbal, Hordijk, van Lindert, Nijenhuis and van Westen2015; Giest Reference Giest2017).

Recent literature offers various models for gaining knowledge on urban dynamics, and how to operationalize these for improved and better-informed decision-making. On the one hand, knowledge management is discussed as a city-specific issue; on the other, there is a discourse on knowledge transfer between cities. Both play a crucial role in understanding the dynamics of data use for urban policy-making.

The Learning City 1: Policy Transfer versus Mobile Urbanism

For city-to-city knowledge transfer, there are two slightly different conceptual models of how knowledge is transferred. First, there is the political science understanding of “policy transfer,” which describes an unstructured market of policy ideas that are adopted, transferred, or emulated to maximize reform goals (Peck and Theodore Reference Peck and Theodore2010). Put differently, policy transfer is a process in which “knowledge about how policies, administrative arrangements, institutions and ideas in one political setting (past or present) is used in the development of policies, administrative arrangements, institutions and ideas in another political setting” (Dolowitz and Marsh, Reference Dolowitz and Marsh2000: 5). The idea of policy transfer has increasingly been paired with the concept of learning in order to understand better how the information that is being transferred is shaped and used in the local context. This, in turn, has led to a discussion about different forms of learning, depending on the political pressure on, as well as the capacity of, policy-makers to adopt new ideas (Giest Reference Giest2016). Cohen and Levinthal (Reference Cohen and Levinthal1990) highlight that “learning capabilities involve the development of the capacity to assimilate existing knowledge” (quoted in Giest Reference Giest2016: 130). Learning also plays a role in related policy transfer models, such as Municipal International Cooperation (MIC) and city twinning. These are collaboration schemes among two or more cities aiming to transfer knowledge based on a formal relationship. By definition, MIC takes the form of a collaborative effort between local governments to stimulate knowledge exchange between their staff members, often on previously identified topics (van Edwijk et al. Reference van Edwijk, Baud, Bontenbal, Hordijk, van Lindert, Nijenhuis and van Westen2015). MIC tends to serve broader political goals, such as strengthening democracy and enabling city diplomacy relations, than city twinning. The idea of city twinning builds on a similar idea. Here, cities in distinct geographical and political areas are paired, mainly between North American or European cities and African or South American cities (Muggah Reference Muggah2014).

Next to policy transfer, there is a more recent approach referred to as “policy mobility” or “mobile urbanism.” This approach highlights the translational, networked, and multiscalar nature of urban policy (McCann and Ward Reference McCann and Ward2011). The main difference vis-à-vis policy transfer is that mobile urbanism includes a broader set of actors, going beyond policy-makers and bureaucrats to include players who can come from anywhere inside or outside the city. Examples include local policy-makers who use best practice cases from other places and global communities that are adapted to the local context. Here, practitioners emphasize the need to balance local impacts on the one hand and global flows of knowledge on the other (Dicken et al. Reference Dicken, Kelly, Olds and Wai-Chung Yeung2001; McCann and Ward Reference McCann and Ward2010).

When discussing urban policies in a digital age, the high degree of “mobility” of ideas is particularly relevant to data-driven innovation. Technology advances are fast paced, and if innovative solutions in a given city have proven successful, these can travel quickly to inspire policy-makers in other cities that face similar challenges. At the same time, this knowledge/policy transfer is often a highly political one, as there are struggles related to which policies are being framed as successes, thus empowering certain cities at the expense of others (Robinson Reference Robinson2006; McCann and Ward Reference McCann and Ward2010).

The Learning City 2: Knowledge Management within Cities

Before policies can travel between cities, the research and practice communities within a city play a crucial role in developing successful measures when it comes to introducing new routines and innovative practices (Mans and Meerow Reference Mans and Meerow2012). For big data applications, in particular, policy-makers are largely dependent on external advice and input from scientific institutions, technology companies, or related sets of experts to inform or guide decision-making. Knowledge or information management can thereby take various forms. In the urban context, researchers highlight the role of local citizens and their participatory role in the process of developing localized types of knowledge (Hordijk and Baud Reference Hordijk and Baud2006; Mancini and Súilleabháin Reference Mancini and Súilleabháin2016). With respect to big data applications in policy development, local governments have often relied on data collected by other actors in the city, or even at the national level. “The result,” they note, “is a highly fragmented and dispersed set of local level data” (Hordijk and Baud Reference Hordijk and Baud2006: 675). In addition, local knowledge is crucial for understanding how to account for biases in big data (that is, representativeness of the local community) and how to provide the required context for analysis (Taylor Reference Taylor, Gupta, Pfeffer, Verrest and Ros-Tonen2015). These necessities lead to an emphasis on building networks that connect the relevant stakeholders to enable a more critical reflection and improved understanding of the data, informed by local and contextual knowledge. As a report by the Aspen Institute (2012: 11) points out,

[The integration of data-driven innovation in policy development] will require training a cadre of individuals and intermediary organizations to understand neighborhoods as well as statistics and using “data coaches” to community groups. To be effective data coaches, individuals and organizations must be responsive to communities and their priorities, get better at “translation work” that allows them to interpret data and present it in forms that are useful to practitioners, and develop tools and strategies that make it easier for practitioners to use data for self-evaluation and decision-making.

It is not enough to develop an infrastructure for transferring information and data. Cities need to invest proactively in a strategy that connects citizens and policy-makers to foster data-driven innovation. City authorities need to put in place a new type of digital communications environment and adequate mechanisms when integrating data-driven innovation as part of their operations and policy-making. Such changes can take the form of individuals, institutions, and/or technologies, as well as through importing models from other cities (Komninos Reference Komninos2002; Fuggetta Reference 236Fuggetta2012). In this process, it is important to account for the speed of innovation in data-related technology: it is increasingly difficult to keep a sufficiently up-to-date overview of all relevant developments, even if there are enough resources for a dedicated team of experts. Instead, city authorities increasingly have to rely on hybrid, international networks of experts that share best practices as these emerge from pilot projects around the globe (Verhulst Reference Verhulst2016).

11.3 Towards More Inclusive Cities? Tackling Inequality and Violence with Data

How can big data help policy-makers build more inclusive cities in the Global South? There are many ways to approach this question; for the purposes of this chapter, we focus on the possibilities that are emerging for tackling inequality and violence. We first present five categories of data streams, and then present the possible impact these could have on both challenges. Even though using big data to accomplish inclusivity goals is a relatively nascent field, we present some insights from published case studies on reducing violence in cities within Colombia and South Africa to highlight recent developments in the use of data and the knowledge transfer mechanisms involved.

11.3.1 (New) Types of Data Streams

When looking at the opportunities and challenges that come with the Data Revolution, it is useful to distinguish between various categories of additions to the data landscape that have entered (or are likely to enter) the city’s policy realm. It is important to note that much of the big data discourse addresses the emerging possibilities of data analytics and new computational methodologies to handle increasingly large databases. For example, technology advances in the fields of real-time dashboards, automated visualizations, machine learning, and artificial intelligence have generated much interest in this regard. However, it is useful to move beyond the analytics, and instead to define the new types of data streams that are likely to shape the way decision-making is undertaken.

Many of the more radical, data-driven innovations are inspired by new types of data that have thus far not been collected by city authorities. In this context, Rigobon (Reference Rigobon2016) refers to “designed” and “organic” data streams, which emphasize that what data will be collected has traditionally been decided beforehand and has subsequently been collected according to a predefined scheme (through surveys, questionnaires, and/or administrative records, for example). The main difference between these traditional data collection regimes and big data collection is that new data streams increasingly come in the form of unstructured data. In the following, we introduce five types of data streams that can help to navigate today’s data landscape: public datasets, citizen reporting, open web data, digital breadcrumbs, and remote sensing.

Public Datasets

Although public datasets do not necessarily constitute a new type of data stream, digitization and the availability of new analytical capacities lead to an increased uptake of these data in policy-making processes. Data sources for policymaking now include, a.o. “real-time sensor data, public administration data (including open data), data from statistical offices, commercially traded data and several types of targeted or ad-hoc data” (Technopolis et al. 2015: n.p.). In addition, we observe the promotion of open data in the public sector and among NGOs, which leads to increased free availability of these datasets in machine-readable formats. The digital divide is still a major limiting factor in this form of data collection. Governments in non-OECD countries are generally much more reluctant – and less able – to make datasets publicly available.Footnote 3 Questions remain regarding the extent to which digital technologies can improve the collection of data in the developing world, and how much of this additional data will be made available for urban authorities (or other third parties) as a consequence.Footnote 4

Citizen Reporting

With access to mobile devices and the Internet on the rise, connecting to citizens is becoming cheaper, faster, and more reliable. This connectivity can be used for survey techniques based on Short Message Service (SMS), online feedback forms, and so forth. Collecting data in this way is often conducted through digital platforms, which can be run by public entities, private or community organizations, or as a joint effort. In various Kenyan cities for example, the NGO Sisi ni Amani applied SMS-based citizen reporting in order to reduce ethnic tensions across communities (Parker Reference Parker2011; Trujillo et al. Reference Trujillo, Elam, Shapiro and Clayton2013); other examples include violence monitoring at several protest sites in Bangkok throughout 2014, “in order to better understand the situation and track relevant developments” (Elva 2014: n.p.). Further, the Nairobi police have been experimenting with the use of cell phones to reach out to slum inhabitants in Mathare (Frilander et al. Reference Frilander, Lundine, Kutalek and Likaka2014). Even in such underserved areas of the city, mobile phone ownership is nearly universal, and approximately 50 percent of these devices are Internet enabled, which makes direct, real-time communication with citizens a possibility (whether by police or other public services agencies). Still, particular challenges can arise with regard to the validity and representativeness of the information provided by respondents in this style of big data collection (van der Windt, Reference Van der Windt, Livingstone and Walter-Drop2012).

Open Web Data

Online content has long been readily available in the form of websites, news archives, event reporting, and blog posts. This includes online platforms such as Global Dataset of Events, Language, and Tone (GDELT) or Armed Conflict Location & Event Data Project (ACLED) that provide event data,Footnote 5 or simply search engine tools that are available to any online reader.Footnote 6 New developments include a) an increasing number of methodologies making it possible to “scrape” the content of websites automatically without human oversight and b) the emergence of social media as an additional form of open web data. Popular platforms including Facebook, Twitter, Instagram, YouTube, and LinkedIn, as well as many other social platforms, offer various degrees of access to their customers’ data.

To be clear, the latter is a peculiar form of “open” data. Many of these sources are available to the general public, yet access to them is controlled by private entities. Depending on the aims and privacy restrictions that come with the use of this type of data stream, it is possible to derive relevant insights from what is posted online. These insights can be used for assessments of political preferences and social topics of interest extrapolated from Twitter messages (UN Global Pulse 2014), to verify flood damage across urban settlements using multiple social media platforms (Quaggiotto Reference Quaggiotto2014), or to analyze social patterns in relation to security/crime issues in the context of cities (Pfeffer et al. Reference Pfeffer, Verrest and Poorthuis2015). It is also to possible establish knowledge of social and political networks based on this data (O’Callaghan et al. Reference O’Callaghan, Prucha, Greene, Conway, Carthy and Cunningham2014; Bozdag et al. Reference 235Bozdag, Gao, Houben and Warnier2014). It is likely that many of today’s possibilities will evolve in the coming years. The key question is which open online data streams can be employed to gain relevant insights for users, and to what extent machine-readable is access granted?

Digital Breadcrumbs

The more people are connected to or work with digital technologies, the more they leave traces of what they do in their daily lives (Pentland Reference Pentland2012). This includes any type of consumption in digital form (supermarket purchases, cell phone airtime vouchers, or financial transfers). Even though this type of data is not necessarily representative, it can reach far beyond the middle class. For example, refugees receive vouchers in the form of e-cards that register what, when, and where people buy goods (WFP 2017; Flaemig et al. Reference Flaemig, Sandstrom, Caccavale, Bauer, Husain, Halma and Poldermans2017). To date, the most powerful form of these “breadcrumbs” are mobile phone data. There are a number of interesting experiments with cell phone data, for example, to detect crime hotspots in London (Bogomolov et al. Reference Bogomolov, Lepri, Staiano, Letouze, Oliver, Pianesi and Pentland2015) and understanding social ties across different communities in the Ivory Coast (Bucicovschi et al. Reference Bucicovschi, Douglass, Meyer, Ram, Rideout, Song, Blondel, de Cordes, Decuyper, Devlisse, Raguenez and Smoreda2013). Also, mobile phone data have been used in Afghanistan to determine changes in movement patterns after micro-violence, such as improvised explosive device (IED) explosions (World Bank 2014), and to develop new poverty monitoring methodologies in Senegal (Pokhriyal et al. Reference Pokhriyal, Dong and Govindaraju2015). However, digital breadcrumbs come with major caveats.On the one hand, these types of data streams are often proprietary and not accessible without prior negotiations with a commercial party, such as telecom providers or financial service providers. Second, the clients of these services do not generally know about (or consent to) their data being used (this is different, for example, than social media content, for which a certain degree of consent can be assumed). Even though analysis of digital breadcrumbs is generally done on an aggregated level without substantial risks of privacy infringements, full privacy does not exist: Most datasets that include personal data carry the risk that individuals can be reidentified (Berens et al. Reference Berens, Mans and Verhulst2016; OCHA 2016). Currently, standards for data sharing and data use simply do not exist to a degree that makes all stakeholders comfortable with experimentation with these types of datasets. However, sector-specific data use guidelines and related frameworks that help create trust and form new data collaboratives are likely to emerge over time (WEF 2015b; IDRG 2015; GovLab 2016).

Remote Sensing Data

Satellite images are a well-known source of data that are usually expensive, but are increasingly accessible, even for smaller organizations. This technology is based on sensors that have been placed in orbit, made possible only via monetary investments. The affordability of remote sensing has risen in part because common sensors are being placed nearly everywhere, from closed circuit television cameras to air quality sensors, track-and-trace devices in vehicles, and sensors required for the Internet of Things (for example, sensors in refrigerators, street lights, and so forth). An interesting example is the ability, through remote sensing, to “measure the quantity, timing, and locations of gunfire incidents with greater accuracy than do reported crime or 911 call data through sensors” (Carr and Doleac Reference Carr and Doleac2016: 4). This technology, called “Shotspotter,” is currently applied in the United States (ibid.). Shotspotter’s physical manifestation is a connected system of audio sensors on top of buildings that detects the sounds of gunfire and analyzes them for accuracy. If Shotspotter confirms the sound of gunfire, the program responds by sending a message to local police with the location of the shots fired. The data produced by Shotspotter – date, time, location, single/multiple gunshots – are publicly available.

Likewise, in the geospatial arena, the emergence of drones as a new type of cheap sensor increasingly impacts the way environmental data can be collected or verified. In disaster areas, for example, drones are already being used for quick damage assessments, and a growing number of experiments are underway to use drone-mounted cameras in the fields of agriculture or environmental protection in urban areas (see, for example, Meier Reference Meier2014). Affordable, high-resolution satellite imagery enables people to retrieve information about hard-to-reach places and conflict areas. For example, “Amnesty International requested the assistance of the Geospatial Technologies and Human Rights Project of the American Association for the Advancement of Science to investigate the veracity of reports of human rights violations stemming from the escalating conflict in Aleppo, Syria” (Amnesty International n.d.: n.p.).

These five types of data streams can have different applications in different contexts. Looking at the innovation landscape today, we see a number of cases that address aspects of urban violence, that is, policing, law and order, and related challenges. Examples of more structural approaches that use data-driven innovations to reduce inequality throughout the city are less common.Footnote 7 This is not a surprise, as many questions remain about the extent to which new data streams can complement classical data sources, especially in a developing country. Data are generally biased towards the digital haves and have-nots; we need to develop methodologies that make new data streams both representative and reliable. Table 11.1 gives an overview of the possible uses of these five new types of data streams for both the reduction of violence and inequality in urban contexts.

Table 11.1 Possible uses for data in creating more inclusive cities

Examples of data application
Type of data streamReducing violenceReducing inequality
Public datasets
(Census and administrative data on policing, education, healthcare, and so forth)Data from police reports can be matched with other data streams such as SMS-based surveys.Census data can be used in combination with social media content to understand public perceptions among youth, for example, on unemployment.
Citizen reporting
(SMS-based surveys, online reporting platforms, and so forth)Police departments can collect information from citizens on crime-related incidents in a given area.Local perceptions of major issues in a given area can be collected by public authorities and/or local community-based organizations.
Open web data
(Online content, social media, and so forth)Social media can be used to identify hate speech towards a given group; it can also be used for outreach purposes to encourage citizens to avoid certain areas or not to engage in violence.Social media content can be collected and analyzed in order to determine major problems in certain areas or to encourage civic engagement.
Digital breadcrumbs
(Consumer data, mobile phone data, and so forth)Aggregated mobile phone data can show where people move at night, giving clues about relative safety in certain urban areas.Aggregated consumer data (for example, airtime vouchers) can reveal major changes in the socioeconomic situation of certain areas.
Remote sensing
(Satellite imagery, sensor networks, Internet of Things, and so forth)Audio sensors can detect gunshots in real time and provide clues about the deterioration of security in a given area.Air- or water-quality sensors can detect problems with the quality of public goods.

As discussed in the previous section, any of these applications requires a meaningful dialogue between those who work with the technology and those with contextual expertise regarding the location in which it will be applied. We are at the very beginning of the Data Revolution – much remains unexplored and untested; indeed, the use of new data streams in formulating city policies is far from mainstream. City authorities tend to start with existing data rather than tapping into new data streams. Moving forward, we need to improve our understanding of the underlying dynamics of knowledge transfers insofar as they relate to data-driven innovation. While still evolving, two examples, from Cali and Cape Town, highlight some of the lessons learned about knowledge transfer mechanisms that support data-informed policy.

11.3.2 Reducing Violence with Data Knowledge: Cali and Cape Town

Cali – Colombia, and Cape Town – South Africa are two cities that have shifted towards data-informed policy in connection to reducing violence. We identify some of the opportunities and challenges that are connected to this shift. Generally speaking, the availability of additional data has led some cities to take a more evidence- and/or data-based approach towards violence; Colombia has become an especially popular research example (see Gaviria Reference Gaviria2000; Bourguignon et al. Reference Bourguignon, Nunes and Sanchez2002; Cotte Poveda Reference Cotte Poveda2012).

In Latin America, several cities – including Bogotá, Cali, Medellín, San Pablo, and Recife – have been able to reduce violent incidents dramatically using policies that harness big data. The programs stem from a mixture of models used in the United States and evidence for what works in the targeted cities in Latin America (Ojea Reference Ojea2014). This has also led to new revelations about the root causes of violence. For example, for a long time, the US lens on crime, in combination with substantial media coverage of drug-related crimes, led officials in Cali to believe that drug dealers were the biggest cause of homicides in the city (Velasco Reference Velasco2015). Using recent and local statistics, however, officials learned that “homicide victims and aggressors were predominantly young, unemployed males who had low levels of education, came from the poorer sectors of the city and were frequently involved in gang fights” (Velasco Reference Velasco2015: 3). In other words, drug traffic was still part of the equation, but was only indirectly responsible for violence. The crime figures in this case largely came from an online platform called “The Monitor,” which interactively maps the distribution of murder by country, year, age of victim and, where available, gender, and type of weapon. The online database draws on statistics from the United Nations Office for Drugs and Crime, government offices, health institutes, and policy records, as well as a detailed, city-level breakdown for Latin America. However, streamlining such information is challenging, since Latin American countries have different ways of defining crime and differ in the way they collect information. The Inter-American Development Bank is currently in the process of standardizing violence indicators (Velasco Reference Velasco2015).

Cape Town has also moved towards a more comprehensive approach for tackling violence based on quantitative and qualitative data. This shift was facilitated by the Violence Prevention through Urban Upgrading (VPUU) not-for-profit initiative, which works with local and national governments and includes international groups with stakeholder expertise in developing such measures. The VPUU applied a combination of high-quality, research-based documentations, monitoring, and evaluation surveys, as well as databases of police-reported robberies over a ten-year period (Cassidy et al. Reference Cassidy, Ntshingwa, Galuszka and Matzopoulos2015), as well as incorporating census data and information from the South African Index of Multiple Deprivation. The researchers subsequently geolocated the data to specific areas through the use of mobile phones that were distributed to the community (Cassidy et al. Reference Cassidy, Ntshingwa, Galuszka and Matzopoulos2015). In this way, citizen reporting, digital breadcrumbs, secondary databases, and qualitative information were gathered to inform potential policy changes. These changes have led officials to focus increasingly on infrastructural causes for violence, such as lighting, improved public spaces, and safer public transportation, after-school activities, and an improved education system (WCG 2011; Cassidy et al. Reference Cassidy, Ntshingwa, Galuszka and Matzopoulos2015).

In both cities, a diverse set of stakeholders initiated policy changes to incorporate big data. Cali’s mayor, Dr. Rodrigo Guerrero, introduced weekly meetings of the heads of all departments connected with law enforcement (Rosenberg Reference Rosenberg2014). Those meetings involved officials from “the police, judiciary and forensic authorities, members of the Institute for Research and Development in Violence Prevention and Promotion of Social Coexistence (CISALVA) at the University of Valle, cabinet members responsible for public safety, and the municipal statistics agency” (Velasco Reference Velasco2015: 6). The meetings were an attempt to pool contextual knowledge on violence in combination with the data to make sense of the status quo and to discover possible improvements to initiatives. In Cape Town, as in Cali, the goal was a more comprehensive approach to violence. Here, changes involved the inclusion of stakeholders in public health, criminal justice, education, and social development sectors, and active participation and partnership of citizens and civil society more broadly (WCG 2013; Cassidy et al. Reference Cassidy, Ntshingwa, Galuszka and Matzopoulos2015).

Both cities also faced political obstacles, including changes in local government, funding, and knowledge sharing among local stakeholders. For Cali, these challenges were twofold: first, the national government was unwilling to provide additional financial support to data-driven innovation. The city needed money to support more policing in risk-prone areas, during holidays and paydays, as well as after 2 a.m. – days and times during which violence had been shown to increase. In addition, because Colombian mayors can serve only one term, newly implemented measures could be, and were, overturned by the new mayor. After Mayor Guerrero’s term (1992–1995), the murder rate rose again (Rosenberg Reference Rosenberg2014). In Cape Town, measures suggested by VPUU were unpopular with the government because they targeted areas where the political opposition was in charge. According to Cassidy et al. (Reference Cassidy, Ntshingwa, Galuszka and Matzopoulos2015), this not only resulted in limited implementation, it further posed a threat to the research process, since it compromised the availability and validity of evaluative data from community stakeholders and drove an overreliance on administrative data. Ultimately, crime data can also be uncomfortable for mayors and governments, especially before elections, since better recording and more accurate data often lead to higher reported crime rates that might hurt political ambitions.

Overall, both cities are increasingly incorporating data-informed policies into their measures against violence and have, over the course of establishing these initiatives, involved a range of stakeholders who can provide more contextual perspectives. In the years to come, additional data tools could lead to more accurate and complete data on crime and violence trends in cities. However, as the examples have also shown, there is a political component that can slow down or even hinder the use of big data.

11.3.3 Discussion

Our examples from South Africa and Colombia show that data-informed policy is largely shaped through joint efforts of national and local governments as well as local communities and law enforcement agencies. These case studies also indicate that data are only one piece of the larger puzzle when targeting violence in cities; issues remain surrounding political and collaborative aspects. To guide future paths for data use in the context of urban policy in the Global South, we believe there are two overarching lessons summarized by these cases.

Data-Informed Policy-Making

First, using big data is accompanied by risks of drawing misleading conclusions, such as assumptions about causes of violence that are drawn from public datasets, but do not apply to a specific region. Data analytics cannot simulate the complex picture of potential interactions of different policy domains, such as crime and infrastructure, or the dynamics among social groups in certain neighborhoods (Bollier Reference Bollier2010). The research community is skeptical of claims of universal urban experiences, stressing that contextual particularities and local experiences within places are important (Brenner and Schmid Reference Brenner and Schmid2015; Thakuriah et al. Reference Thakuriah, Tilahun and Zellner2015). It follows that conclusions drawn in cities with high crime rates do not automatically apply to other cities with similar statistics, but different local contexts. The example of Cali has shown that officials were too quick to assume that drug-related crime was driving up the homicide numbers when drug trafficking had only an indirect effect. However, the challenge is to strike an appropriate balance between automated analysis and contextual interpretation now that data are becoming more widely used.

The Politics of Data-informed Policy

Second, data can be political. When utilizing the information gained from data, political obstacles emerge in two ways. Data can bring to the surface insights that are uncomfortable to political stakeholders. Cape Town exemplifies a city uncooperative in data collection efforts, either because proposed data collection efforts were connected to regions in the hands of the political opposition or because data collection initiatives were branded as campaigns against the government (Consortium on Crime and Violence Prevention 2015). Furthermore, collaboration across political constituencies might prove difficult. Based on the insights from Cali and Cape Town, cross-stakeholder engagement emerges as a key dimension for deploying data-based initiatives in cities. Such engagement has been achieved in the form of regular meetings of heads of departments (Cali) or by involving citizens in data collection (Cape Town). Underlying this collaboration is the notion of trust – trusting that the data are put to good use by government, as well as trust in local stakeholders by the government. Moving towards more data-informed policies, city stakeholders will have to find meaningful ways to create mutual trust.

The elements discussed in this chapter call for a more thorough understanding of how advances in data-driven innovation could translate into new forms of urban policy-making – and how collaboration between various stakeholders and actors can be supported from the beginning to avoid inappropriate technology and policy designs. Much remains to be done to support decisions about which policies to adopt and when to be cautious in applying data-informed policy. From a research perspective, future studies should give clues about the interplay of additional, more detailed data being collected and the political repercussions this might have. If new data streams enable more accurate, but also more problematic, numbers for certain issues such as violence and poverty, the political opposition might outweigh the societal benefits that data-driven innovations provide. Overcoming these obstacles requires alignment between different stakeholders within the city, as well as paying attention to the timing and circumstances within which data-informed policies are developed.

References
Amnesty International (n.d.) Satellite Imagery Analysis for Urban Conflict Documentation: Aleppo, Syria, AAAS. www.aaas.org/aleppo.
Aspen Institute (2012) Developing and Using Data and Evidence to Improve Place-Based Work. Proceedings from a meeting convened by the Aspen Institute Roundtable on Community Change with support from The Annie E. Casey Foundation, New York, September 8–9, 2011. https://assets.aspeninstitute.org/content/uploads/files/content/images/rcc/Sept%202011%20Data%20Meeting%20Proceedings%20FINAL%206%206%2012.pdf
Barber, B. (2013) If Mayors Ruled the World: Dysfunctional Nations, Rising Cities. New Haven, CT: Yale University Press.
Batty, M. (2013) Big Data, Smart Cities and City Planning. Dialogues in Human Geography, 3(3): 274279.
Bellagio Big Data Workshop Participants (2014) Big Data and Positive Social Change in the Developing World: A White Paper for Practitioners and Researchers, Oxford: Oxford Internet Institute. www.rockefellerfoundation.org/uploads/files/c220f1f3-2e9a-4fc6-be6 c-45d42849b897-big-data-and.pdf.
Berens, J.B., Mans, U., and Verhulst, S. (2016) Comparing and Mapping Responsible Data Approaches. TheGovLab and Center for Innovation, Leiden University.
de Boer, J. (2015) Resilience and the Fragile City. Stability: International Journal of Security and Development. 4(1): p.Art. 17. doi: http://DOI.org/10.5334/sta.fk.
Bogomolov, A. Lepri, B., Staiano, J., Letouze E., Oliver, N., Pianesi, F., and Pentland, A. (2015) Moves on the Street: Classifying Crime Hotspots Using Aggregated Anonymized Data on People Dynamics. Big Data, 3(3): 148158.
Bollier, D. (2010) The promise and peril of Big Data, Aspen Institute, available online: www.emc.com/collateral/analyst-reports/10334-ar-promise-peril-of-big-data.pdf.
Bourguignon, F., Nunes, J., and Sanchez, F. (2002) What Part of the Income Distribution Matter for Explaining Crime? The case of Colombia. Working Paper, DELTA ENS.
Bozdag, E., Gao, Q., Houben, G.J., and Warnier, M. (2014) Does Offline Political Segregation Affect the Filter Bubble? An Empirical Analysis of Information Diversity for Dutch and Turkish Twitter Users. Computers in Human Behavior, 41: 405415.
Bryant, R., Katz, R.H., and Lazowska, E.D. (2008) Big-Data Computing: Creating Revolutionary Breakthroughs in Commerce, Science and Society. http://cra.org/ccc/wp-content/uploads/sites/2/2015/05/Big_Data.pdf.
Bucicovschi, O., Douglass, R.W., Meyer, D.A., Ram, M., Rideout, D., and Song, D. (2013) Analyzing Social Divisions Using Cell Phone Data, in Blondel, V., de Cordes, N., Decuyper, A., Devlisse, P., Raguenez, J. and Smoreda, Z. (eds.), Mobile Phone Data for Development. Cambridge, MA: Netmob, pp. 4254.
Brenner N. and Schmid C. (2015) Towards a New Epistemology of the Urban City 1(2–3): 151182.
Cohen, W.M. and Levinthal, D.A. (1990) Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35(1): 128152.
Carr, J. and Doleac, J. (2016) The Geography, Incidence, and Underreporting of Gun Violence: New Evidence Using ShotSpotter Data. Brookings Research Paper, April 2016.
Cassidy, T., Ntshingwa, M., Galuszka, J., and Matzopoulos, R. (2015) Evaluation of a Cape Town Safety Intervention as a Model for Good Practice: A Partnership between Researchers, Community and Implementing Agency. Stability: International Journal of Security and Development. 4(1): p.Art. 27. doi: http://doi.org/10.5334/sta.fi.
Consortium on Crime and Violence Prevention (2015) Dialogue on Safety and Security: Insights from Cape Town. Key Points from the Third International Dialogue on Safety and Security Cape Town, February 25–27, 2015. https://igarape.org.br/wp-content/uploads/2015/10/SafetySecurityDialoguesReport.pdf.
Cotte Poveda, A. (2012) Violence and Economic Development in Colombian Cities: A Dynamic Panel Data Analysis. Journal of International Development, 24: 809827.
Dicken, P., Kelly, P.F., Olds, K., and Wai-Chung Yeung, H. (2001) Chains and Networks, Territories and Scales: Towards a relational framework for analysing the global economy. Global Networks, 1: 89112. doi:10.1111/1471–0374.00007.
Dolowitz, D., and Marsh D. (2000) Learning From Abroad: The Role of Policy Transfer in Contemporary Policy Making. Governance, 13 (1): 524.
van Edwijk, E., Baud, I., Bontenbal, M., Hordijk, M., van Lindert, P., Nijenhuis, G., and van Westen, G. (2015) Capacity Development or New Learning Spaces through Municipal International Cooperation: Policy Mobility at Work? Urban Studies, 52 (4): 756774.
Elva Community Engagement [Elva] (2014) Monitoring Violence in Bangkok. https://elva.org/case-studies.
Flaemig, T., Sandstrom, S., Caccavale, O. M., Bauer, J-M., Husain, A., Halma, A., and Poldermans, J. (2017) Using Big Data to Analyse WFP’s Digital Cash Programme in Lebanon. Humanitarian Practice Network. http://odihpn.org/blog/using-big-data-to-analyse-wfps-digital-cash-programme-in-lebanon.
Frilander, M., Lundine, J., Kutalek, D., and Likaka, L. (2014) New Technologies for Improving Old Public Security Challenges in Nairobi. Igarapé Institute. http://issat.dcaf.ch/mkd/content/download/49277/782313/file/NE-15_New-technologies-in-Nairobi_4th_june.pdf.
Fuggetta, A. (2012) 3+1 Challenges for the Future of Universities, The Journal of Systems and Software, 85: 24172424.
Gaviria, A. (2000) Increasing Returns and the Economic Evolution of Violent Crime: The Case of Colombia. Journal of Development Economics, 61: 125.
Giest, S. (2016) Overcoming the Failure of ‘Silicon Somewheres’: Collective Learning in Innovation Networks. Policy and Politics. 45(1): 3954 doi.org/10.1332/030557316X14779412013740.
Giest, S. (2017) Big Data Analytics for Mitigating Carbon Emissions in Smart Cities: Opportunities and Challenges. European Planning Studies, 25(6): 941957 (doi: 10.1080/09654313.2017.1294149).
GovLab (2016) Data Collaboratives: Exchanging Data to Improve People’s Lives, GovLab (blog). http://thegovlab.org/datacollaboratives.
Hordijk, M. and I. Baud. (2006) The Role of Research and Knowledge Generation in Collective Action and Urban Governance: How Can Researchers Act as Catalysts? Habitat International, 30: 668689.
International Data Responsibility Group [IDRG] (2015) International Data Responsibility Group: Putting People First in a Digital Age. www.responsible-data.org.
King, G. (2013) Big Data is Not About The Data! Talk at the New England AI Meetup, 5/14/2013. http://gking.harvard.edu/files/gking/files/evbase-neai_0.pdf.
Komninos, N. (2002) Intelligent Cities: Innovation, Knowledge Systems, and Digital Spaces. London and New York: Routledge.
Krumholz, H.M. (2014) Big Data and New Knowledge in Medicine: The Thinking, Training, and Tools Needed for a Learning Health System. Health Affairs, 33 (7): 11631170.
Latonero, M., Kleinman, M., and Hiatt, K. (2017) Tech Folk: ‘Move Fast and Break Things’ Doesn’t Work When Lives Are at Stake, The Guardian, February 2017. www.theguardian.com/global-development-professionals-network/2017/feb/02/technology-human-rights.
Letouze, E., Vinck, P., and Kammourieh, L. (2015) The Law, Politics and Ethics of Cell Phone Data Analytics. Data-Pop Alliance publication. http://datapopalliance.org/wp-content/uploads/2015/04/WPS_LawPoliticsEthicsCellPhoneDataAnalytics.pdf.
Lyon, D. (2014) Surveillance, Snowden, and Big Data: Capacities, Consequences, Critique. Big Data & Society, July–December: 113.
Mans, U., and Baar, T.J. (2014) Defining Peace Informatics. www.peaceinformaticslab.org/learn-more.html.
Mans, U. and Meerow, S. (2012) Role of Local Governments in Promoting Renewable Energy Businesses. ICLEI Policy Paper.
Mancini F. and Súilleabháin A.Ó. (eds.) (2016) Building Resilience in Cities under Stress. New York: International Peace Institute.
McCann, E. and Ward, K. (2010) Relationality / Territoriality: Toward a Conceptualization of Cities in the World. Geoforum 41 (2), 175184.
McCann, E. and Ward, K. (2011) Mobile Urbanism. Minneapolis: University of Minnesota Press.
Meier, P. (2014). Digital Humanitarians: How Big Data is Changing the Face of Humanitarian Response. Boca Raton: CRC Press.
Mayer-Schönberger, V. and Cukier, K. (2013) Big Data: A Revolution That Will Transform How We Live, Work, and Think. Boston: Houghton Mifflin Harcourt.
Muggah, R. (2014) How Are Some Fragile Cities Tackling Their Worst Problems? [TED Talk]. www.npr.org/2016/01/08/462282897/how-are-some-fragile-cities-tackling-their-worst-problems.
Muggah, R. (2015) A Manifesto for the Fragile City. Journal of International Affairs, 68 (2): 1936.
Muggah, R. and Diniz, G.M. (2013) Digitally Enhanced Violence Prevention in the Americas. Stability: International Journal of Security and Development. 2(3): p.Art. 57. doi: http://doi.org/10.5334/sta.cq.
O’Callaghan, D., Prucha, N., Greene, D., Conway, M., Carthy, J., and Cunningham, P. (2014) Online Social Media in the Syria Conflict: Encompassing the Extremes and the In-Betweens, Proceedings of the 2014 International Conference on Advances in Social Network Analysis and Mining (ASONAM 2014).
OCHA Think Brief [OCHA] (2016) Building Data Responsibility into Humanitarian Action. United Nations Office for the Coordination of Humanitarian Affairs. www.unocha.org/sites/unocha/files/Building%20data%20responsibility%20into%20humanitarian%20action.pdf
Ojea, V. (2014) Latin America Accounts for More than 30% of the World’s Homicides. The World Bank, March 5. www.worldbank.org/en/news/feature/2014/02/11/en-america-latina-sufre-mas-del-30-de-los-homicidios-mundiales
Open Knowledge International [OKI] (2014) Tracking the State of Government Open Data. http://index.okfn.org.
Parker, P. (2011) Sisi Ni Amani ‘Peacemapping’ in Kenya. www.insightonconflict.org/blog/2011/09/kenya-peacemapping.
Peck, J. and Theodore, N. (2010) Mobilizing Policy: Models, Methods, and Mutations. Geoforum, 41(2): 169174.
Pentland, A. (2012) Reinventing Society in the Wake of Big Data. Edge, August 30. www.edge.org/conversation/reinventing-society-in-the-wake-of-big-data.
Pokhriyal, N., Dong, W., and Govindaraju, V. (2015) Virtual Networks and Poverty Analysis in Senegal. D4D Netmob, Conference Paper.
Pfeffer, K., Verrest, H. and Poorthuis, A. (2015) Big Data for Better Urban Life? – An Exploratory Study of Critical Urban Issues in Two Caribbean Cities: Paramaribo (Suriname) and Port of Spain (Trinidad and Tobago). The European Journal of Development Research, 27(4): 505522.
Quaggiotto, G. (2014) Using Twitter to Get Ground Truth on Floods: An Interview with Floodtags Founder Jurjen Wagemaker, UN Global Pulse Blog, November 19. www.unglobalpulse.org/blog/using-twitter-get-ground-truth-floods-interview-floodtags-founder-jurjen-wagemaker.
Rigobon, R. (2016) Keynote Speech at the Annual Bank Conference on Development Economics 2016: Data and Development Economics, June 20, 2016, Washington, DC.
Robinson, J. (2006) Ordinary Cities: Between Modernity and Development. Abingdon and New York: Routledge.
Rosenberg, T. (2014) Colombia’s Data-Driven Fight against Crime. New York Times. https://opinionator.blogs.nytimes.com/2014/11/20/colombias-data-driven-fight-against-crime/
Soubra, D. (2012) The 3 Vs that Define Big Data. Data Science Central, July 5, 2012. www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data.
Taylor, L. (2015) Big Data and Urban Governance, in Gupta, J., Pfeffer, K., Verrest, H., and Ros-Tonen, M. (eds.) Geographies of Urban Governance. Cham: Springer International.
Technopolis, Oxford Internet Institute and Centre for European Policy Studies (2015) Data for Policy: A Study of Big Data and Other Innovative Data-Driven Approaches for Evidence-Informed Policymaking. www.technopolis-group.com/data-policy-innovative-data-driven-approaches-evidence-informed-policymaking/.
Thakuriah, P., Tilahun, N., and Zellner, M. (2015) Big Data and Urban Informatics: Innovations and Challenges to Urban Planning and Knowledge Discovery. In Proceedings of NSF Workshop on Big Data and Urban Informatics, 432. https://urbanbigdata.uic.edu/proceedings/
Trujillo, H.R., Elam, D., Shapiro, G., and Clayton, M. (2013) The Role of Information and Communication Technology in Preventing Election-Related Violence in Kenya, 2013. Perspectives on Global Development and Technology, 13(1–2):, 111128.
UN Global Pulse (2014) Using Twitter to Understand the Post-2015 Global Conversation, Global Pulse Project Series, no.6, 2014. www.unglobalpulse.org/sites/default/files/UNGP_ProjectSeries_Post2015_Priorities_2014_0.pdf.
UN IAEG (2014) A world That Counts: Mobilizing the Data Revolution for Sustainable Development. www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf.
Van der Windt, P. (2012) From Crowdsourcing to Crowdseeding: The Cutting Edge of Empowerment, in Livingstone, S. and Walter-Drop, G. (eds.). Bits and Atoms: Information and Communication Technology in Areas of Limited Statehood, Oxford: Oxford University Press, pp. 144155.
Velasco, R. (2015) Big Data Are Reducing Homicides in Cities across the Americas. Scientific American, October 1, 2015.
Verhulst, S. (2016) Corporate Social Responsibility for a Data Age, Stanford Social Innovation Review (February). https://ssir.org/articles/entry/corporate_social_responsibility_for_a_data_age?platform=hootsuite.
Western Cape Government [WCG] (2011) Western Cape’s Draft Strategic Plan. South Africa: WCG.
Western Cape Government [WCG] (2013), Integrated Violence Prevention Policy Framework. South Africa: WCG.
World Bank (2014) Big Data in Action for Development: World Bank Publication 2014. http://live.worldbank.org/sites/default/files/Big%20Data%20for%20Development%20Report_final%20version.pdf.
World Economic Forum [WEF] (2015) Global Agenda Council on Data-driven development. WEF Publication (webpage). www.weforum.org/communities/global-agenda-council-on-data-driven-development.
World Economic Forum [WEF] (2015B) Data-Driven Development : Pathways for Progress (January 2015). http://digitalprinciples.org/wp-content/uploads/2015/05/WEFUSA_DataDrivenDevelopment_Report2015.pdf.
World Food Programme [WFP] (2017) Cash-Based Transfer. http://www1.wfp.org/cash-based-transfers.

1 An earlier version of this chapter was presented at the International Studies Association Annual Conference in March 2016, in Atlanta, Georgia, United States.

2 Examples include the Kenyan citizen engagement platform, Ushahidi (see: https://www.ushahidi.com/), or Latin American initiatives such as Chequeado (see: http://chequeado.com).

3 As part of its Global Open Data Index, Open Knowledge International provides an overview and comparative ranking on open government data (OKI 2014).

4 In January 2017, the first UN World Data Forum took place in Cape Town, South Africa. At the meeting, national statistics officials and data and technology experts held numerous meetings to discuss how to apply new data technologies to monitor progress on the Sustainable Development Goals.

Chapter 12: Collaborative and Equitable Urban Citizen Science

Karen MacClune , Kanmani Venkateswaran , Bolanle Wahab , Sascha Petersen , Nivedita Mani , Bijay Kumar Singh , and Ajay Kumar Singh
12.1 Introduction

Conventional science is usually conducted in a remote location, abstracted from day-to-day conditions and needs. Even when it produces useful outputs, those outputs are rarely effectively communicated to those who could put them to best use. “Citizen science” is increasingly providing powerful alternatives to this approach.

Though citizen science often evokes images of, for example, school children measuring rainfall, we see it as a much larger field. Citizen science can range from crowd-sourcing information to participatory monitoring and action research, to collaboration between the general public and professional scientists, and to highly informed public science interests funded by citizens.

The common threads of citizen science are:

  1. 1. Citizen science functions as a check and balance on information. In places where information is controlled by governments or the private sector and there is limited access or manipulation, citizen science can increase access to information or provide alternative information.

  2. 2. Citizen science operates at different scales. It is often granular and/or collected by hundreds or thousands of people and can, therefore, provide very different information from what is available through conventional channels, allowing for investigations that have not previously been possible.

  3. 3. Citizen science is grounded locally and relates to issues that people see and/or experience on a daily basis. This relevancy aids in community ownership of the results and makes them more actionable.

  4. 4. Citizen science cultivates an informed and engaged citizenship. Participants understand the value of science and see themselves as an integral part of that science. Ideally, this translates to a more informed public and greater citizen engagement in influencing science-policy decisions.

These differences between citizen science and conventional science mean that citizen science can generate unexpected – and sometimes very different – knowledge. That knowledge can lead to transformative change in how processes are undertaken and in how people act.

Citizen science is supporting the growth of new scientific endeavors in powerful ways, particularly as technology has progressed and virtual networks have expanded, increasing scientific literacy and inclusivity (Bonney et al. Reference Bonney, Cooper, Dickinson, Kelling, Phillips, Rosenberg and Shirk2009; Connors et al. Reference Connors, Lei and Kelly2012). Yet, it is not clear that citizen science is being used to its fullest potential. Indeed, Mueller and Tippins (Reference Mueller and Tippins2012: 3) argue that citizen science has largely been top-down:

The key point is that it does not matter whether or not individuals engage in citizen science projects focused on mammals, birds, weather, climate change, flora, or invasive species. The participants primarily serve to collect data for scientists rather than to collaborate with scientists, democratize protocol and equipment, assess ideas, and work in relation to others.

For this reason, we are encouraged to see the emergence of a new type of citizen science, one based on equitable collaboration. In this citizen science, citizens are engaged as equal players in the scientific process, contributing their local, grounded perspectives, knowledges, understandings, needs, and aspirations in an ongoing and iterative process. This is related to but different from action research, which is either initiated by researchers to solve an immediate problem or is an iterative learning and doing process. Action research doesn’t necessarily engage citizens. Citizen science empowers citizens to act, and makes science directly responsive to their needs and interests. Therefore, citizen science is especially important for urban-focused science, in which a multitude of diverse perspectives and knowledges need to be captured. This chapter explores several case studies from urban areas in which citizens were engaged in equitable collaboration, and how this led to new learning and action.

12.2 Types of Citizen Science

There are two types of commonly practiced citizen science; one is focused on data collection, while the other both collects data and conducts its own analysis of that data.

12.2.1 Citizen Science as a Data Collection Mechanism

This type of citizen science involves large groups of citizens, often distributed over wide geographical areas, to collect data. This structure allows for collection of information at a geographic scale and at a level of detail that has never previously been possible. For example, in the United States, the Community Collaborative Rain, Hail and Snow Network, or CoCoRaHS, is a national project that enlists a community-based network of volunteers to measure and record precipitation data. Project staff map, analyze, and disseminate the resulting information. These results are ultimately used by a wide variety of organizations and individuals, ranging from scientists to city utilities, from emergency managers to students. CoCoRaHS’s goals are to generate and disseminate accurate precipitation data with substantially greater granularity than traditional methods have permitted, to increase community awareness about weather, to build collective awareness of climate, and to develop citizens’ skills in scientific data collection (see www.cocorahs.org).

However, this project largely perpetuates a one-way flow of data. Citizens provide data to scientists, who then undertake the analysis and dissemination. There is no direct tie back to the citizen data collectors in ways that impacts their lives. Such a structure is fairly typical of crowd-sourced data projects. Still, this form of crowd-sourcing data does combine the capacities of traditional science with the capacities of communities to collect extensive data while raising citizen awareness about science.

12.2.2 Citizen Science as a Citizen Scientific Analysis

A less common form of citizen science involves citizens in the analysis of the data they collect and, therefore, establishes a more direct interface with scientists. Citizen science of this form frequently arises either due to a lack of information and data that citizens want to address, or over questions about the validity of existing scientific knowledge. While this method allows citizens to engage more with the analysis of data and advocate for themselves and their needs, they do not have control over how the data are ultimately used in decision-making processes.

Communities in Thailand, for example, began research of this type in the early 2000s in response to the controversial Pak Mun Dam on the Mun River, the largest tributary of the Mekong River. The Pak Mun Dam was built in 1994 by the Thai government and the World Bank and had immediate adverse impacts on the environment, including fisheries, as well as the livelihoods of local residents who depended upon them. The Assembly of the Poor, a strong people’s movement, formed to protest dam operations and impacts. In response, the Thai government agreed to open the dam’s gates to restore natural flows, and to conduct studies on impacts to fisheries and communities. To ensure that people’s concerns were heard, Living River Siam, a nongovernmental organization, developed a research method for communities to conduct their own scientific studies. In what has become known as “Thai Baan” research, Pak Mun villagers systematically documented how the dam had affected their lives and the fisheries on which they depended (Herbertson Reference Herbertson2012).

Although both the conventional and citizen science studies clearly documented highly damaging impacts on ecosystems and livelihoods, the Thai government chose to continue dam operations. Dramatic declines in fisheries have continued. Nevertheless, the network of Thai communities and NGOs emerged strong and unified after the experience; the Assembly of the Poor continues to support people who were affected by development projects; and interest in Thai Baan research continues to grow. In 2004, a similar effort by villagers combining Thai Baan research and political pressure convinced the Thai government to preserve the Khon Pi Luang rapids on the Mekong River. This illustrates how citizen science can help citizens to understand the sociopolitical environment and players involved in an issue and to take action in ways that will achieve change.

12.2.3 The Limitations of These Two Models

Both citizen science as data collection mechanism and citizen science as analysis have favorable attributes for citizens and the environment and, in many cases, encourage more locally grounded actions. However, they are also top-down – the citizens involved do not have control over how the data are used, nor are they included in associated decision-making and/or planning processes. This is problematic for a number of reasons.

First, top-down science does not necessarily produce scientific knowledge that is “usable” in the local context. Usable science is knowledge that is produced through integrated processes that meet constituent needs (Lemos and Morehouse Reference Lemos and Morehouse2005). One of the most effective and powerful ways to produce usable science is through the coproduction of knowledge. This refers to an iterative process (Dilling and Lemos Reference Dilling and Lemos2011), involving both scientists and citizens, where different values, experiences, and information – which are all partial, imperfect, and situated in their local contexts (Haraway Reference Haraway1988; Harding Reference Harding2011) – are brought together to produce a common knowledge or solution to a local problem. This situated, common knowledge accounts for the range of needs and capacities that should be considered when producing and using science (Dilling and Lemos Reference Dilling and Lemos2011).

Second, scientist-driven citizen science projects do not necessarily engage meaningful public participation. Such projects tend to focus on one frame (for example, an ecological frame) and “[draw] participants into thinking they are doing something scientific when what they are doing does not nearly capture the integrated nature of science, culture, and consequences” (Mueller and Tippins Reference Mueller and Tippins2012: 6). Citizens are unlikely to gain an understanding or see the value of science – or to function as checks and balances for traditional scientific knowledge – if they are not engaging with the myriad factors (social, cultural, political, economic, technological, physical) that influence the results of science and its associated actions.

Third, the exclusion of citizens from processes that determine how citizen science data are used can dis-incentivize citizen ownership of local solutions. Citizen ownership of initiatives is important, particularly if those initiatives are aimed at responding to local problems and/or generating local outcomes. Citizen ownership can incentivize communities to sustain action over the long term and, eventually, to institutionalize the changes needed to achieve initiative goals within their communities (Shediac-Rizkallah and Bone Reference Shediac-Rizkallah and Bone1998; Simpson et al. Reference Simpson, Wood and Daws2003;). Such ownership can create real transformation. Mueller and Tippins (Reference Mueller and Tippins2012) suggest that participation in science needs to be democratized to ensure that diverse voices are engaged in dialogue based on mutual trust and respect. The experience should also be allowed to shape participants’ futures based on their needs and based on the locally embedded scientific knowledge that they are instrumental in creating. Not only will this create a more informed public, but it will also generate a public that is critical and engaged in influencing science-policy decisions.

12.2.4 A Third Type of Citizen Science: Equitable Collaboration

A third type of citizen science based on equitable collaboration needs to emerge; in some places, it is already emerging. To produce science that is embedded in the local context, and to promote environmental and social justice, citizens need to be given more power within scientific processes. This type of citizen science requires scientific processes to be codesigned and knowledge to be coproduced by scientists and citizens (Colston et al. Reference Colston, Vadjunec and Wakeford2015). Such engagement can both contextualize and customize external scientific knowledge and learning so that it can both be translated into action that is locally owned and can inform international “expert” knowledge in ways that make that knowledge more relevant.

Standout challenges of undertaking citizen science of this type in urban, as compared to rural, environments include a greater diversity of stakeholders required to provide the needed contextualization and customization, an increase in complexity, and less social cohesion, all of which can make it difficult to identify and engage stakeholders. Capturing this complexity is critical in urban-focused science and action, and further illustrates the importance of pursuing citizen science based on equitable collaboration in urban settings.

The following urban citizen science case studies emphasize what successful projects in these areas can look like. They explore how the engagement of citizens from the outset influenced the process and outcome of the studies and produced benefits for everyone involved.

12.3 Case Study One: The Odo-Osun Natural Spring Project, Ibadan, Nigeria

Oke-Offa Babasale is an unplanned, high-density, low-income residential community in Ward 10, Ibadan North-East local government area, or IbNELGA, of Ibadan, Nigeria (Figure 12.1). A spring has been the major source of water to the community for drinking and other domestic uses year-round for over 80 years (Adewoye Reference Adewoye1995). The spring is located within a densely built community and is accessible from the nearest road only by a network of foot paths running between residential buildings. Prior to the development of the spring, the water supply situation in the community was poor. Women and children (ages 8 to 16 years old) spent hours scouting for water, and there was a high incidence of waterborne diseases, typhoid fever, and cholera (Odo-Akeu Spring Water Development Project Working Group 1996; SIP-TSU n.d.).

Figure 12.1 Odo-Osun Spring in Ibadan North-East local government.

Source: CNES/Airbus DS, DigitalGlobe/Esri, @OpenStreetMap.

The Odo-Osun Community Spring Water Development Project, or OCSWDP, was designed to provide 20 to 50 liters per person per day of clean and hygienic water to the people of Oke-Offa Babasale community and adjoining areas for an affordable fee. By improving the environment of a heavily polluted and underutilized natural spring, the project sought to enhance and sustain the community’s access to safe water.

The process of collaboration and integration evolved in stages through series of consultation and communication as follows:

  • The Oke-Offa Babasale Community conducted a situation analysis, identified problems related to the spring, and consulted the UN-Habitat sponsored Sustainable Ibadan Project-Technical Support Unit, also called SIP-TSU, for assistance;

  • SIP-TSU conducted a joint diagnostic survey of the environment and the quality of spring water with community leaders and representatives of other stakeholders;

  • SIP-TSU and other stakeholders communicated results using video documentation, print, and electronic media;

  • New water infrastructure was designed in consultation with SIP-TSU, representatives of the community, and other stakeholders;

  • A cost estimate was prepared and roles assigned to identified stakeholders;

  • Resources were mobilized, a project management committee was established, and a bank account was opened; and

  • Project implementation and design of a framework for operation took place between 1995 and 1997.

The SIP-TSU provided overall technical guidance and advice and assisted the community in establishing the 16-member Odo-Osun Spring Water Development Working Group, which served as the think-tank committee for the project. A respected community leader, Chief David Adewoye, coordinated the working group; it drew its membership from the community, Oyo State Department of Rural Development, Ibadan North-East LG Council, UNICEF, SIP, academia, and the private sector.

The collaboration ensured an equal partnership, based on consensus, in critical decision-making. Each side contributed time, material, financial resources, and human resources, though in varying proportions. Conventional scientists scaled up the community’s traditional method of increasing water yield from natural springs, brooks, and streams by introducing a concrete storage tank fitted with hand pumps and taps for easy and hygienic collection of water. The community members managing the project were taught how to fix simple faults in the pumps while plumbing artisans within the community could replace damaged pipes and taps.

The Odo-Osun project has resulted in a number of benefits, including increased access to hygienic water; less time spent by women and children scouting for water; improved attendance of children at school; project accountability and probity; an example of effective multi-stakeholder collaboration; capacity building for community members on water system construction and repair; improved sanitation in the vicinity of the spring; improved health and reduction in waterborne diseases among the people of the community; sustainable natural resource protection and conservation; more time for women to pursue socioeconomic activities; and a good lesson in integration of citizen science and formal science (Figure 12.2).

Figure 12.2 Odo-Osun spring in 2010.

Source: Grace Oloukoi.

However, these benefits were not achieved without effort. The project was faced with some challenges, including:

  • Community members initially found the pay-as-you-draw water scheme, implemented to pay for project costs and ongoing maintenance, to be alien. Many residents protested the user fees, resisted payment, and forcefully drew water.

  • Community members were slow to understand the sustainability-related and cost-recovery implications of self-financing the service delivery, operations, and maintenance of a community-based resource.

  • A fence, erected around the spring to prevent pollution and vandalization of pumps and taps, was seen as limiting the previous 24-hour access.

  • There were complaints against the management committee about composition of the committee, lack of information, poor communication, and overprotection of the spring.

To resolve the conflict, project participants applied indigenous approaches (Wahab and Odetokun Reference Wahab and Odetokun2014). The SIP-TSU, acting as facilitator and mediator, consulted with and mobilized representatives of Oke-Offa Babasale community, including the youth, women, and project development stakeholders, to attend a series of meetings over five months to resolve the grievances. At the end, the project put in place a more robust, inclusive project management structure composed of the representatives of each zone, the elders, youth, women, and an auditor.

The citizen-initiated OCSWDP, realized through multi-stakeholder collaboration, earned international recognition as an ambassador project on New Solutions for Sustainable Cities during the Stockholm Partnership for Sustainable Cities final event held in Stockholm, June 4–7, 2002. This project has demonstrated how citizen science can be integrated with formal science to enhance the quality of a community-based water resource, to increase a community’s access to potable water, and to promote sustainable water delivery. The project experienced some challenges from the integration of the two sciences, but these were resolved using the extant indigenous approaches to conflict resolution within the community.

12.4 Case Study Two: Using City Stakeholder-Defined Extreme Weather Thresholds to Customize Climate Projections, United States

The Climate Thresholds Project is designed to enlist city stakeholders and climate scientists to codevelop climate projection data customized specifically to city needs. Started in 2014, the project is funded by the National Oceanic and Atmospheric Administration’s Sectoral Applications Research Program and is led by Adaptation International, with support from the Southern Climate Impacts Planning Program, the Climate Assessment for the Southwest, Atmos Research, and ISET-International. The project is partnering with four cities of various sizes, capacities, and resources with a diversity of climate challenges: Boulder, Colorado; Miami, Oklahoma; Las Cruces, New Mexico; and San Angelo, Texas.

Many communities around the world are already vulnerable to extreme weather events. As climate conditions change, many of these vulnerabilities may get worse or increase in frequency, magnitude, and/or intensity. Communities already know from experience when weather goes from being a nuisance to a problem for their citizens, city operations, natural resources, and other things that matter to the community. To develop effective community responses to future change, it is essential to utilize local experience and knowledge to identify critical thresholds for extreme weather events and to understand how these events may be altered in the future as the climate changes.

To be truly useful for local decision-making, climate information needs to be as specific as possible for that community. For many communities, generic thresholds for extreme weather events are insufficient to connect people with climate impacts and catalyze actions. The Climate Thresholds Project is piloting and testing a methodology for: (1) engaging citizens to identify critical thresholds for extreme weather events specific to their communities; (2) using these thresholds to analyze localized climate projections to community-specific needs; and (3) supporting community stakeholders to take new actions in response to identified risks.

The core of the methodology is a series of community workshops in each city called Shared Learning Dialogues – participatory, multisector workshops where new information is introduced and explored collectively. This approach addresses two major challenges in building resilience and adaptive responses to climate change: 1) translating scientific information into forms useable by stakeholders; and 2) generating buy-in and developing practical solutions that include a variety of stakeholders who operate in different ways, with different tools and contexts, and from different interests (Randolph Reference 259Randolph and Goldstein2011).

Equally essential is clear information about changing climate and extreme weather conditions and the associated impacts and risks that the city will face. To date, projections of climate change have generally been provided in one of two ways: one-size-fits-all national or regional reports and datasets; or locally tailored, external, expert-driven, desktop studies. Even the best of these generally fails to present information in ways that relate to local, on-the-ground issues and needs. The Shared Learning Dialogue approach works to address this disconnection between information holders and information users by bringing them both into the dialogue and allowing both sides to learn (Tyler and Moench Reference Tyler and Moench2012). It also recognizes that information users have unique local experience that is invaluable in developing meaningful knowledge for the community.

In each city, stakeholders involved in the Shared Learning Dialogues include city and county staff; emergency management personnel; medical and mental health professionals; utility representatives; local, state, and federal researchers; and local and state decision-makers, as well as project staff and scientists. This diversity allows participants to look beyond their traditional job duties and identify areas of common interest or particular problematic climate and extreme weather events. For example, in Las Cruces, key concerns included extreme heat, extreme cold, extreme wind and dust, flooding, and city water demand, with specific questions related to each. Following the Shared Learning Dialogue, the project team worked with participants to narrow these concerns down to specific, quantifiable indicators that localized global climate models can project with medium-high confidence. Table 12.1 gives examples of participant questions and their associated thresholds.

Table 12.1 Las Cruces, NM, stakeholder-identified extreme weather thresholds

CategoryProblemQuestionThreshold
Extreme heatHigh heatHow will summer temperatures change?Number of days per year with maximum temperatures above 100°F (El Paso airport closes the short runway)
Nighttime temperatures greater than 85°F for two or more days (temperatures start becoming a human health problem)
HumidityEvaporative coolingHow will the effectiveness of evaporative cooling change in the future?90°F or more and 35 percent relative humidity or more
Extreme coldFreezing conditionsWill more freeze events occur, like in 2011?Maximum daily temperatures below 32°F for two or more days
How could freezing conditions change?Number of nights of hard freeze (28°F)
PrecipitationFloodingHow might flooding change in the future?2.5 in. per day precipitation events (similar to event on August 1, 2006)
Three or more consecutive days of precipitation of 1 in. or more each day
Water resourcesMunicipal water usageHow will temperatures affect water demand?The occurrence of three or more days of 100°F or higher temperatures combined with no precipitation
WindDust stormsHow will the frequency of dust storms change?Years with similar temperature and precipitation conditions to 2003 and 2011 (calendar years)

Many of the thresholds identified in Las Cruces are similar to those in the other three cities – high maximum temperatures, high nighttime temperatures, increased frequency of flooding – but the exact numbers vary, fitting the local environments of each city. Other thresholds – the effectiveness of evaporative cooling and frequency of dust storms – are particular to Las Cruces.

The workshop discussions in each city have been strongly influenced by the diversity and the multisectoral views represented. Discussions have ranged from the potential climate impacts on agriculture and how they could change local culture, to explorations of the various types of climate action that will be needed and how to achieve these through local code changes, to how to educate and influence funding agencies and political entities to begin building support for acting more broadly.

The questions that city stakeholders are asking about how future climate will affect them, their operations, and the things they care about are focused and insightful. They have gone far beyond disseminating generic climate projection information. They are grappling with a broad range of possible impacts that could result from changing climatic conditions and are deciding what they can start doing today to mitigate or adapt to those impacts. These questions span departments and disciplines – the county transportation department is talking with the city sustainability officer, the police chief, and the state senator’s office staff about what their issues are and how they can work together to solve challenges. The results are dramatically more proactive than is typically achieved in a more traditional, top-down climate modeling project.

This project clearly falls into the third category of citizen science focused on equitable collaboration. The ultimate users of the information are not only those identifying thresholds, but are also those coproducing knowledge about why those thresholds are important and how to incorporate the new information they have gleaned into decision-making processes. From a scientific perspective, the results are equally expansive. Project staff are being pushed to identify resources for city players that can help them generate urban heat island maps, understand the potential impacts of climate change on crops, and explore how to distinguish between natural variability and changing climatic conditions. The questions that city stakeholders are asking make it clear how much more could be done to make climate projection information actionable and are generating exciting new avenues for scientific exploration.

12.5 Case Study Three: Adversity to Advantage in Gorakhpur, India

Climate change is threatening food production systems and, therefore, the livelihoods and food security of millions of people who depend on agriculture in India. Consistent warming trends and more frequent and intense extreme weather events have been observed in recent decades, and climate change projections show consistent temperature increases and erratic precipitation trends. Farmers must adapt to these changing conditions to build resilient livelihoods.

People involved in agriculture tend to be among the poorest urban residents, and the poorest of all tend to be women farmers. Yet the women farmers of Mahewa ward of Gorakhpur city, in eastern Uttar Pradesh, have been adopting innovative and resilient agricultural practices. These practices have sustained their farming – especially vegetable cultivation – in an area that is acutely waterlogged.

Mahewa ward is situated in a low-lying area on the southwestern periphery of Gorakhpur city (Figure 12.3) where residents have particularly poor socioeconomic status. Located near a wholesale vegetable market, the majority of the farmers of Mahewa ward grow vegetables to sustain their livelihoods. Waterlogging and weather uncertainties – such as late monsoons, intense rains, and drought – adversely impact the vegetable farming in the area. Farming in such challenging conditions has been successful only because of the synergy between scientific methods adopted by the farmers and the application of citizen science.

Figure 12.3 Mahewa ward, Gorakhpur, India.

Source: map provided by GEAG.

Gorakhpur Environmental Action Group, or GEAG, formed under the Asian Cities Climate Change Resilience Network initiative, began promoting resilient agriculture with small, marginal, and women farmers in 2010. Their underlying strategy is to make farming economically viable and to demonstrate new, climate-resilient farming techniques.

To engage with farmers, GEAG set up and facilitated a neighborhood committee on Climate Resilient Agriculture, or CRA. The CRA committee provides a platform for farmers to share their agriculture-related problems and to find solutions. Since the platform meets monthly at the ward level, it is easy for women farmers to access, participate, and learn new methods of farming. This platform has been instrumental in scaling up new techniques to other farmers.

One of the key agricultural practices promoted by GEAG in the CRA committee has been dhaincha (Sesbania aculeate; Figure 12.4) farming. Dhaincha is a leguminous crop that is tolerant of high saline and waterlogged conditions. It is popularly and scientifically known for its green manuring attributes; scientists recommend it as a measure to reclaim alkaline soils that have been induced by waterlogging. GEAG’s past experiences had shown that dhaincha survives very well in waterlogged conditions.

Figure 12.4 Dhaincha (center).

Source: photo by GEAG.

The farmers who grew dhaincha for a year saw additional potential uses for the crop. They began using the hard, semi-woody stem of dhaincha as the base for climber crops in a multitier cropping system. This unique method of crop combination (dhaincha with vegetable crops) helps reduce the impacts of waterlogging on the vegetable crops and, simultaneously, increases soil fertility when the farmers plough dhaincha back into the soil after the vegetable crop is harvested. Farmers also began using dhaincha as fuel and as fodder for livestock. In the CRA committee meetings, successes were shared and expanded.

Dhaincha farming has improved the incomes of local farmers. Table 12.2 shows the income of Ms. I.D., a farmer in Mahewa ward, who sowed dhaincha along with sponge gourd on a quarter of an acre of land. With an input cost of Rs. 1250 (18.75 USD), she earned profits worth Rs. 7750 (116.50 USD).

Table 12.2 Cost-benefit ratio of dhaincha cultivation

CropCropping area (acres)Input cost (in Indian rupees)Total production (quintals)Output cost (in Indian rupees)Net profitCost-benefit ratio
Dhaincha0.25505.0200019501:39
Sponge gourd12007.0700058001:5
Total125012.090007750

Dhaincha is very popular in the urban environment. The intervention started with 10 farmers; now, more than 500 farmers have adopted it. The farmers are also promoting this technique in farmer field schools, meetings, in farmers’ fairs, and so forth. Word-of-mouth popularity has produced much recognition and adoption of the crop. Farmers have also started using it as a “trap crop,” as it provides protection against pests and insects.

Equitable collaboration between GEAG and the farmers improved the dhaincha farming model substantially. The resulting model delivers sustainable social and economic benefits to poor farmers, enabling them to increase their incomes and improve the quality of their lives. Such local innovations are attracting large numbers of other farmers who are facing similar problems farming in waterlogged contexts and are experiencing deteriorating soil health. Today, this citizen science initiative, acting in synergy with conventional science, is helping approximately 800 farmers in this flood-affected region.

12.6 Discussion

All three case studies fall into our third category of citizen science, which focuses on equitable collaboration. In all three cases, scientists worked with citizens to coproduce knowledge about how information could be best used locally. This process was facilitated by boundary organizations that have links to the community and experts. Likewise, in all three cases, the outside experts learned how extensively their information needed to be tailored to be adapted for local action.

These case studies illustrate several elements that we believe should be at the foundation of citizen science if it is to reach its full potential:

  1. 1. Coproduction of knowledge, as illustrated in the dhaincha farming study

  2. 2. Meaningful participation, as illustrated in the climate thresholds study

  3. 3. Citizen ownership of solutions, as illustrated in the Odo-Osun study

We note that, in addition to these three elements, monitoring and evaluation is a growing area of donor interest and an undertaking that supports the development of strong science, particularly science focused on producing change. As such, we see monitoring and evaluation as fundamental to citizen science and an area in which citizen science could grow considerably. However, a detailed exploration of monitoring and evaluation, insofar as it can help support and develop citizen science, is beyond the scope of this chapter.

The dhaincha farming case study illustrates the benefits of coproduction of knowledge. GEAG brought top-down information on green manuring with dhaincha into Mahewa ward, but it was the women farmers, working together and with GEAG, who quickly realized dhaincha could also be used to address other issues they were having – trouble growing vegetable crops in waterlogged soils and lack of fuel and fodder. By customizing the top-down information with bottom-up knowledge of local needs and capacities, highly useful science was created. The credibility, legitimacy, and saliency of this knowledge to the local community is evident in the rapid uptake and continued development of this crop by other farmers, and in the economic impacts it is having on farmers’ lives.

The climate thresholds case study illustrates the value of meaningful participation. Climate projection data have been available in the United States for well over a decade, yet governments, agencies, organizations, and businesses are only just beginning to take action to mitigate climate emissions or to adapt to anticipated climate change impacts. Action, where taken, still tends to be highly focused within one or a few sectors. In this case study, the use of Shared Learning Dialogues to convene highly diverse, multidisciplinary groups significantly changed the content of the dialogue in all four project cities. Participants’ thinking became substantially broader, opportunities for cross-sectoral collaboration were identified, and local stakeholders began actively exploring the depths of internal and external expert knowledge in the room. This is only possible when participants feel they are engaged as equals, such that their knowledge, perspective, and opinions matter.

Finally, the Odo-Osun case study illustrates the value of citizen ownership of solutions. Many of the issues identified as challenges for the Odo-Osun project are typical of development projects worldwide – conflict over who is involved, over access, and over cost. The other common cause of project failure is selection of technology that cannot be maintained by those using it. By keeping the community at the heart of this project, technologies the community could maintain were preserved, and the challenges were addressed.

All three types of citizen action explored in this chapter – citizen data collection, citizen analysis, and equitable collaboration – are valuable. Citizen data collection is changing the nature of information available to conventional science and is making new analyses possible. Similarly, citizen analysis is challenging the conventional knowledge base and provides much broader sets of data and assessments in the conducted areas. Nonetheless, we believe the real power of citizen science lies in the third area – equitable collaboration. The three case studies we have explored here demonstrate the different cultures, problems, and solutions that are present in urban settings; still, the core method of equitable collaboration used in all three cases has contributed to the success of all three projects, has led to learning both for the citizens and scientists involved, and, through co-development of project focuses and goals, has produced valuable outcomes for the citizens who participated in the work.

12.7 Opportunities Moving Forward

Citizen science is changing the scientific process in powerful ways, and its full potential has yet to be tapped. However, to add value, citizen science needs to be done well, which takes time and funding. If we are to invest our time and money, where should we focus to make our investment as influential as possible?

Some of the opportunities we see include:

  • Scale: Citizen science can help bridge the micro- versus macroscale gap. Conventional knowledge, particularly outside the developed world, is generally only available at a macroscale, and, frequently, it is stuck there due to a lack of finer-scale data. Increasingly, citizen science can help us to close that gap, informing the macroscale picture with microscale detail.

  • Framing: Many of the data that can be easily captured by citizens aren’t data that scientists can use. We need to explore ways to take what can be captured easily and to give it value.

  • Techniques: Local knowledge, such as changes in distribution of indicator species, is not easily crowd-sourced. We need more research into what communities know and how this could support, or challenge, conventional science; how citizens can capture this information and feed it into conventional science; and how we can incentivize citizen participation.

  • Validation: Science typically requires verifiable information rather than perception, myth, or ideology. Yet, citizen-collected data are often based on perception, and in the context of vastly differing lived experiences for citizen scientists and conventional scientists. These perceptions are an important part of how fact is interpreted and provide valuable information about existing needs, values, and constraints. While perceptions are difficult to validate, collaborative engagement between citizens and conventional science can help bridge the gap between formal and informal ways of knowing and create a knowledge that is valid and relevant for a given context.

  • Ownership and action: Increased coproduction of science can lead to high feelings of ownership and high levels of action based on the research results. Refining techniques for building ownership and fostering action will assist in scaling coproduction up and out.

Overall, citizen science is supporting the growth of new science endeavors in exciting ways, particularly as technology has progressed and virtual networks have expanded, increasing scientific literacy and inclusivity of contributors. But, it is not being utilized to its full potential. In this chapter, we have identified the value and opportunities for conducting citizen science that is more equitable and collaborative as a means of narrowing the gap between knowledge and action, particularly in urban settings. We know there are multiple organizations that have been practicing this type of science for years, as illustrated by the studies explored here. We hope this chapter inspires more organizations to embrace citizen science, both for the benefit of citizens, for the benefit of research, and for the benefit of the positive change it can affect for us all.

References
Adewoye, D. (1995). A Brief Address on Odo-Akeu Community Development Association. Address presented to stakeholders on Odo-Akeu Spring Water Development Project at the weekly meeting of the Association on September 6.
Bonney, R., Cooper, C.B., Dickinson, J., Kelling, S., Phillips, T., Rosenberg, K.V., and Shirk, J. (2009). Citizen Science: A Developing Tool for Expanding Science Knowledge and Scientific Literacy. BioScience, 59(11): 977984.
Colston, N.M., Vadjunec, J.M., and Wakeford, T. (2015). Exploring the Entry Points for Citizen Science in Urban Sustainability Initiatives. Current Opinion in Environmental Sustainability, 17: 6671.
Connors, J.P., Lei, S., and Kelly, M. (2012). Citizen Science in the Age of Neogeography: Utilizing Volunteered Geographic Information for Environmental Monitoring. Annals of the Association of American Geographers, 102(6): 12671289.
Dilling, L., and Lemos, M.C. (2011). Creating Usable Science: Opportunities and Constraints for Climate Knowledge Use and Their Implications for Science Policy. Global Environmental Change, 21(2): 680689.
Haraway, D. (1988). Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective. Feminist Studies, 14(3): 575599.
Harding, S. (2011). The Postcolonial Science and Technology Studies Reader. Durham, NC: Duke University Press.
Herbertson, K. (2012). Citizen Science Supports a Healthy Mekong. International Rivers, retrieved from www.internationalrivers.org/resources/citizen-science-supports-a-healthy-mekong-7759.
Lemos, M.C., and Morehouse, B.J. (2005). The Co-Production of Science and Policy in Integrated Climate Assessments. Global Environmental Change, 15(1): 5768.
Mueller, M.P., and Tippins, D. (2012). The Future of Citizen Science. Democracy and Education, 20(1), Article 2.
Odo-Akeu Spring Water Development Project Working Group (1996). Proposal for Technical and Financial Assistances for the Development of Odo-Akeu Spring Water at Babasale in Ibadan North-East Local Government. Unpubl. report by SIP Technical Support Unit.
Randolph, J. (2011). Creating the Climate Change Resilient Community, in B.E. Goldstein (ed.) Collaborative Resilience: Moving Through Crisis to Opportunity, Cambridge, MA: MIT Press, pp. 127148.
Shediac-Rizkallah, M.C., and Bone, L.R. (1998). Planning for the Sustainability of Community-Based Health Programs: Conceptual Frameworks and Future Directions for Research, Practice and Policy. Health Education Research, 13(1): 87108.
Simpson, L., Wood, L., and Daws, L. (2003). Community Capacity Building: Starting with People Not Projects. Community Development Journal, 38(4): 277286.
SIP-TSU (2015). Executive Summary on Odo-Osun Natural Spring Project at Oke-Offa Babasale, Ibadan, in Ibadan North-East Local government area of Oyo State. Unpubl. report by SIP Technical Support Unit.
Tyler S., and Moench M. (2012). A Framework for Urban Climate Resilience. Climate and Development, 4(4): 311326.
Wahab, B. and Odetokun, O. (2014). Indigenous Approaches to Housing-Induced Domestic Conflict Management in Ondo City, Nigeria. Journal of Sustainable Development, 7(4): 2846. http://dx.doi.org/10.5539/jsd.v7n4p28.