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Author: Jonathan Fink
The Human Genome Project may provide a model for mapping the “urban genome.”
We live in an urbanizing age, an age when people seeking economic opportunity, better health care and education, and cultural engagement are migrating from the countryside to cities. Despite the popular belief that cities are sites of wasteful consumption and pollution, when properly designed and administered they can have lower per capita environmental impacts than the rural areas from which their populations come. In fact, more and more people living in places where they can potentially consume less is arguably the single most effective way to achieve global sustainability goals (Calthorpe, 2010).
Despite the promise of cities, however, they do not automatically become engines for positive social transformation. Every city requires a complicated road map showing which policies, practices, and technologies can move its residents toward a more prosperous, healthier, and environmentally responsible future.
Because every metropolitan region has idiosyncrasies that influence the character of its road map, the discovery of general principles that might apply to all cities has been slow. What if we could classify the myriad attributes of a city into a finite set of characteristics, and these categories could in turn point urban policy makers toward the best options for alleviating poverty, stabilizing climate, and achieving energy independence? Is this just a utopian fantasy?
Perhaps not. Think, for example, of the Human Genome Project (HGP), one of the most celebrated scientific accomplishments of the late 20th century. The major public- and private-sector investments in HGP were justified on the grounds that all people share a common genetic framework, which when fully deciphered could point the way to cures for human diseases. Might we apply the same logic to cities, using a classification system for all urban traits—an Urban Genome Project (UGP)—to suggest the way(s) to metropolitan health?
Could such a typology inform computer-based models that can map alternative futures for individual cities and for the urbanized world as a whole? What new kinds of data would we have to collect? And how should the contributions of governments, non-governmental organizations (NGOs), companies, and their academic partners be funded, coordinated, and applied?
In this article, we explore these questions through an analogy with genetics and cite examples of technology and policy options that are already moving us toward a more scientific approach to achieving urban sustainability.
The Components of an Urban Genome Project
It took 13 years to characterize the human genome (McElheny, 2010), and the translation of that knowledge into treatments for disease is just beginning. Nevertheless, the initial political and financial support for HGP would not have materialized without the expectation that these applications would eventually be possible. In addition, the U.S. government’s intent to fund and coordinate the mapping of the genome shifted the emphasis from competition to collaboration and turned a seemingly unattainable idea into reality.
Similarly, a critical first step for a UGP would be to measure and classify cities using a set of common indicators. The greatest benefit of this exercise would be realized only later, when that information is entered into models that can forecast alternative outcomes. Those outcomes would, in turn, support informed choices, based partly on the real-world experiences of other cities. Equally important would be setting up a coordinating body to help finance and oversee the project.
A successful UGP would thus require: (1) a strategy for collecting and classifying urban characteristics; (2) the use of models and decision-making tools to sift through alternative future options; and (3) a well respected organization to administer and assemble resources. As we will see, many steps along this path have already been taken.
Urban Measurement: Identifying the DNA of Cities
Cities come in all shapes and sizes, from compact, sophisticated Scandinavian centers to disorganized East African refugee camps1 to automobile-dominated Sun Belt urban sprawl. Despite their variety, these conurbations can all be described in terms of common factors, such as physical and political boundaries, demographics, infrastructure, governance systems, commercial institutions, and natural resources. Each of these factors can, in turn, be subdivided into dozens of variables.
Physical attributes of cities, such as air quality, water flow, traffic patterns, building materials, and land use, can be tracked directly. Socio-economic properties, such as jobs, housing, and health outcomes, must be inferred from financial, demographic, occupational or service records maintained mostly by governments.
The Infusion of New Technologies
A key step in the development of a UGP will be the infusion of new technologies. In less affluent areas, urban information is still assembled and transmitted manually. In more advanced countries, data retrieval is becoming automated through embedded sensors, wireless transmitters, GPS devices, and software that can extract critical information from web-based databases. Some of these digital methods may soon become cheap enough to be deployed without capital-intensive intermediate steps, just as cell phones have penetrated markets in countries that never had landlines.
For example, a promising application is cell-phone geo-positioning to track mobility patterns (Ratti et al., 2006). In order to send a signal to a particular phone, wireless companies must repeatedly calculate its geospatial coordinates. This information, when stripped of personal identifiers, aggregated, and interpreted, can reveal trends in group activity. For instance, highway traffic and transit ridership can be monitored based on the locations of cell phones in commuters’ pockets. Similarly, text messaging and postings to social media2 can be mapped as a function of geography and time to illustrate, for example, dispersal patterns of people leaving a cultural or sporting event.
Cell phones can also be a tool for residents to help manage their cities through distributed data measurement. For instance, OpenStreetMap and other groups now commonly rely on volunteers with cell phones to prepare and aggregate real-time information for plotting passable routes through disaster zones.3
Bottom-Up and Top-Down Data Collection
Most methods of urban data collection are “bottom-up”; that is, sensors are located on or near the phenomena being monitored. “Top-down” approaches include remote sensing instruments mounted on satellites or aircraft. Although such instrument packages were initially deployed for non-urban purposes, such as observing oceans, the atmosphere, or agriculture, they can provide detailed, consistent, and objective coverage of city characteristics without direct physical access. So far, the use of top-down information by municipal governments has been largely restricted to mapping resources on visible-spectrum images.
Other promising tools include infrared spectrometers that measure both the temperature and composition of urban surfaces (Quattrochi et al., 2000). These data can track dust generation in cities, reveal heat loss through poorly insulated roofs, and map vulnerabilities to urban heat-island effects. LIDAR can show the shapes of individual buildings and can help estimate the vulnerability of low-lying areas to sea-level rise.4 Interferometric synthetic aperture radar (InSAR) can show how falling water tables beneath cities lead to ground subsidence.5
If satellites with sensors and targeting schedules were optimized for urban priorities, they could be even more useful. However, this idea has not yet gained traction with government agencies because no single application has been considered important enough to justify their expense ($50–$200 million). The most likely motivation will be the mitigation of urban heat, which has killed tens of thousands of people in Europe in the past decade and which will certainly worsen as global warming accelerates. One or more “CitySats”6 could provide standardized inputs for all cities, which is not possible today.
The Need for Standardized Measurements
For the purposes of a UGP, it will be critical that there be broad agreement on a strategy for common indicators. Once an over-arching program has been established, interest groups can develop subsets of measures and analyses related to particular applications, such as transportation planning, energy use, or housing affordability. A UGP could not only catalogue these indicator subsystems, but would also serve as the host database that would ensure the quality control, correlation, and distribution of data to city administrators and the public.
Every municipal body regularly already records many urban variables. But because no two cities measure all of them the same way, it is extremely difficult to compare cities or to identify common patterns of urban practice. To overcome this limitation, several groups, including United Nations Habitat,7 ICLEI (Local Governments for Sustainability),8 the Inter-American Development Bank (IDB),9 academic groups, and private companies (e.g., SustainLane)10 have attempted to create urban indicator systems.
Each of these groups has focused on a subset of urban interests. For instance, Habitat’s indicators track progress toward meeting housing goals, IDB’s concentrate on natural hazards, and SustainLane’s are focused on sustainability measures. These limited approaches cannot capture interconnections among urban factors and, therefore, have less value for managers than more broad-based urban measures.
In 2006, the World Bank initiated the most ambitious and general urban-indicator project to date. First, they commissioned a study in which nine cities were asked to develop a list of essential metrics that they would be willing to measure on a regular basis. This exercise resulted in the launching, in 2009, of the Global City Indicators Facility (GCIF),11 housed at the University of Toronto.
As of November 2010, GCIF had enlisted 125 cities and metropolitan areas in the program. Each city agrees to collect and annually update information, which is stored on a city-specific web page maintained by GCIF. Currently, 115 variables are grouped into 20 themes (e.g., water management, governance and finance, climate vulnerability, and aging) under the broad categories of city services and quality of life. Because of the breadth of data collected, GCIF can provide input for an unlimited number of analyses.
The backing of the World Bank for GCIF increases the chances that it may become the de facto global standard for city metrics. GCIF also provides a communication platform through which cities can learn best practices from each other.
Urban Modeling and Communication: Diagnosing Healthier Futures
The genetic information compiled by HGP cannot by itself provide cures for illness. It must be combined with models for determining how genetic conditions and non-genetic environmental factors influence human health. Once identified, suspected correlations between diseases and genetic factors must be evaluated by medical researchers who can test them against databases that may not yet exist.
A UGP would face a similar problem. Data collection and compilation programs provide a foundation for characterizing the status of cities. But identifying paths to reducing urban environmental and social impacts requires the ability to make predictions and show the implications of alternative policies.
For instance, a city that wants to reduce its water use would have to take into account the size, consumption patterns, and receptivity to conservation strategies of its population; the amount of water used to produce food, generate energy, support industry, and protect the natural environment; and the cost of infrastructure construction and maintenance. The interdependence of some of these variables might be approximated based on existing functional relationships, but other variables would have to be derived empirically from diverse data sets. These interactions would then have to be tested against historical data, and those data sets might or might not yet exist.
Approaches to Modeling Urban Systems
There are two general approaches to modeling urban systems: comprehensive and partial. The former, like the popular computer game SimCity, attempts to show how all components of a city interact and change as a function of policy choices. To date, such models have remained beyond computational capabilities or data availability.
Urban engineers, computer scientists, natural scientists, and planners have developed models that describe portions of urban systems, many in considerable detail. For example, ModFlow,12 a model developed by the U.S. Geological Survey, shows how subsurface ground water flows beneath cities. The National Center for Atmospheric Research model, Weather Research and Forecasting (WRF) Model,13 simulates urban climate. And the Los Alamos National Laboratory model, Transims,14 describes how intercity transportation networks function.
Note that no single model connects climate, ground water, and transportation. Even UrbanSim15 (Waddell, 2000) uses agent-based microsimulation algorithms to forecast interactions among housing, jobs, and transportation, but does not directly link to ecological or geophysical variables.
The goal of developing a comprehensive, dynamic, urban modeling tool is also being pursued in the private sector. As an offshoot of IBM’s Smarter Cities campaign, the company recently launched a game, called CityOne,16 that combines SimCity’s inter-active appeal with real-world problems in four domains: water, energy, retail, and banking. In contrast to research- and operations-oriented models like UrbanSim, the purpose of CityOne is to educate professionals and the public about the trade-offs associated with managing urban systems.
Given the state of the art in city modeling today, a UGP should encourage researchers to bundle more focused models (e.g., Modflow; WRF) into an over-arching framework like CityOne or UrbanSim.
Although building urban models is technically difficult, an even bigger challenge is ensuring that their outputs are useful to planners, politicians, and the public. The two innovative programs described below are designed to combine metrics, models, and visualization-based feedback mechanisms to aid decision making.
IBM is not the only company actively involved in addressing urban issues. Cisco Systems, Siemens, Autodesk, Google, and Microsoft all have programs for improving how cities function. In 2006, Cisco, NASA, and the city of San Francisco launched Connected Urban Development (CUD),17 an initiative to provide Internet-based tools to help urban residents understand and reduce their carbon emissions.
The heart of CUD is the Urban EcoMap,18 an interactive, web-based interface that aggregates information about city dwellers’ energy consumption, transportation choices, and recycling rates. Individuals can input personal data to see how they compare with neighbors in their zip code or with people in the city as a whole.
EcoMap takes the “Prius effect”—the tendency of individuals to make positive changes in behavior if they can see the effects in real time (Fantino, 2008)—to a new scale. The EcoMap website currently shows only San Francisco and Amsterdam, but several other cities in Europe and Asia are in the process of joining the program.
EcoMap represents a promising element of a UGP. It offers residents several ways of understanding and contributing to the health of their cities. Future versions will include more urban characteristics (e.g., water consumption) and will link more closely with inventory functions for which city managers are responsible.
Other helpful innovations would be a standard format applicable to all cities and closer integration with indicator programs, such as GCIF, and other models, such as CityOne or UrbanSim. These enhancements would make it possible for managers and the public in all participating cities to interact and make decisions that promote sustainability.
Tools for Day-to-Day Decision Making
Day-to-day policy-making requires tools optimized for small, focused groups. One example is Decision Theater (DT), a facility housed at Arizona State University.19 DT began as an immersive environment in which decision making could be assisted by advanced visualization and collaborative techniques. Initially, DT projects used system dynamic models that enabled audiences of up to two dozen people to explore alternative futures in real time. Projects have since evolved to include technology-independent practices intended to help individuals from a variety of professional backgrounds communicate with each other.
Most DT projects involve urban issues, such as water management, land-use planning, crime fighting, and disaster response. Because so many groups in Metro Phoenix have used DT in their projects, the community has embraced it as a regional decision-making asset.
Sister sites are being set up in other cities around the world, making inter-urban comparisons easier.20 Because the technical details of such facilities or programs may vary greatly, an organization or office that can serve as a neutral convener and synthesizer will be essential for a successful UGP.
Managing the Urban Genome Project
Prospects for Government Support
The success of HGP depended on cooperation among several sectors. The federal government provided funding and oversight; academia supplied research facilities and talent; industry provided technical advances, venture capital, and scientists; and NGOs served as advocates for political support. Federal sponsorship was the most critical factor, just as it would be for a UGP.
HGP was one of the first federally funded “mega-science” projects in biology. It was backed by the U.S. Department of Energy (DOE), which focuses on high-performance computing and the development of new technology, and by the National Institutes of Health (NIH), which is responsible for finding cures for disease.
Ultra-large-scale research programs in particle physics, astronomy, climate science, geology, and ecology have also secured political and federal agency support.21 In contrast, the social sciences have not proposed an analogous project, in part because social science research is less instrument-intensive and, therefore, tends to be less expensive, and in part because many members of Congress tend to be skeptical of the social sciences.
Obtaining federal funding for a UGP would also have to overcome political challenges beyond the social science stigma. First, the federal government does not have a major emphasis on urban research. In fact, no federal mission agency “owns” the urban agenda, even though most of them oversee selected aspects of city life (e.g., the U.S. Department of Housing and Urban Development, [HUD], deals with shelter; U.S. Department of Transportation [DOT] addresses urban mobility; and U.S. Geological Survey [USGS] and Environmental Protection Agency [EPA] monitor urban water supplies).
Second, the unique role of cities in alleviating global sustainability challenges is not well understood by U.S. policy makers. Third, the short-term benefits of better planning and exchanges of ideas for urban policies would accrue disproportionately to developing countries.
There are signs, however, that the orphan status of urban research by government agencies may be coming to an end. The National Research Council (NRC), which often develops and articulates new federal research priorities, held a workshop in 2009 that brought together representatives of federal agencies and academia to discuss how government-funded urban research programs could be coordinated (NRC, 2010). Since then, a series of symposia on urban sustainability have been held in cities around the country to explore synergies between federal, state, and local participants. Coincidental with these meetings, HUD, DOT, and EPA launched the Partnership for Sustainable Communities, the first multi-agency research initiative that focuses on urban sustainability.22
Past NRC recommendations have led to the funding of major new academic and government research centers. The urban research community would benefit tremendously from the establishment of a National Science Foundation Engineering Research Center, Science and Technology Center, or Industry/University Cooperative Research Center.
In the longer term, the federal government could establish a federal laboratory focused on sustainable urban systems. This facility could be affiliated with one of several mission agencies, such as DOE, EPA, or DOT. However, the most appropriate and novel arrangement would be a multi-agency center that would support interdisciplinary and interagency partnerships.
Prospects for Academic Support
A UGP might also have difficulty obtaining support from academia, because research universities are not well organized to participate. HGP relied on highly interdisciplinary research groups, including geneticists, biologists, chemists, computer scientists, mathematicians, ethicists, and policy experts. In addition, HGP promoted and benefited from the emergence of bio-informatics as a subfield of genetics and computer science programs in leading universities across the United States, Europe, and Japan.
An aggressive attempt to unravel an urban genome would require not only participation by large numbers of university faculty and students, but also the creation of urban taxonomy and dynamics, a new sub-discipline at the nexus of geography, sociology, history, political science, architecture, civil and environmental engineering, ecology, economics, computer science, and planning.
The timing for this kind of initiative may be propitious, as universities have recently begun formulating administrative structures in response to growing interest in sustainability. Experiments range from sustainability minors offered in traditional departments to free-standing schools of sustainability23 to the repurposing of entire colleges24 to support an emphasis on sustainability. Similarly, interest in urban systems could lead to a variety of new pedagogic approaches, from new degree programs to, perhaps, the redesign of entire universities.
Unlike the growth of genetics, which required large investments in infrastructure that could be supplied only by the wealthiest schools, “urban genomics” could be initiated without major financial outlays, especially at institutions that already have an “applied” urban focus. In the United States, many of these institutions are members of the Coalition of Urban Serving Universities.25 As often happens, academic research and training changes direction in response to signals based on government funding priorities.
Global Aspects of Urban Studies
Unlike genetics in the 1980s, the applied study of cities is not dominated by U.S. institutions. In fact, many European26 and Asian27 universities have strong individual and collective programs already in place.
However, mapping and interpreting “urban DNA” will require complex new consortia that include academic groups as well as companies, NGOs, and government agencies. In addition, the participation of and application to cities in the global South, which have the largest populations and growth rates, will be as important as the participation of cities in the North.
Funding for international research may come from a wide variety of public and private sources, including the United Nations, development banks, international programs of government science foundations, the charitable arms of multinational corporations, and other major philanthropic organizations.
By linking data generation tools like CitySat with the validation capabilities of an indicator system like GCIF, modeling approaches like UrbanSim and CityOne, and decision-support tools like EcoMaps and Decision Theater, a UGP could significantly increase the contributions of cities to achieving global sustainability. Requirements for a UGP will include a well articulated vision for how all of these pieces would fit together, a multi-strategy approach for obtaining funding, and an international organization with enough “clout” to bring all of the players to the table.
HGP promised new solutions to age-old threats to human well-being. Even if the idea of a UGP is not fully implemented, just discussing its possibility could open doors to comparable benefits for society as a whole.
Calthorpe, P. 2010. Urbanism in the Age of Climate Change. New York: Island Press.
Fantino, E. 2008. Choice, conditioned reinforcement, and the Prius Effect. Behavioral Analysis 31(2): 95–111.
McElheny, V. 2010. Drawing the Map of Life: Inside the Human Genome Project. New York: Basic Books.
NRC (National Research Council). 2010. Pathways to Urban Sustainability. Washington, D.C.: National Academies Press.
Quattrochi, D.A., J.C. Luvall, D.L. Rickman, M.G. Estes, C.A. Laymon, and B.F. Howell. 2000. A decision support information system for urban landscape management using thermal infrared data. Photogrammetric Engineering and Remote Sensing 66: 1195–1208.
Ratti, C., R.M. Pulselli, S. Williams, and D. Frenchman. 2006. Mobile landscapes: using location data from cell phones for urban analysis. Environment and Planning B: Planning and Design 33(5): 727–748.
Waddell, P. 2000. A behavioral simulation model for metropolitan policy analysis and planning: residential location and housing market components of UrbanSim. Environment and Planning B: Planning and Design 27(2): 247–263.
1 Some African refugee camps have populations of 300,000 people. Online at http://www.msnbc.msn.com/id/31569565/ns/world_news-africa/ .
2 Online at http://www.casa.ucl.ac.uk/tom/.
3 Online at http://haiti.openstreetmap.nl/.
4 Online at http://www.epa.gov/climatechange/effects/coastal/.
5 Online at http://www.adwr.state.az.us/azdwr/Hydrology/Geophysics/ LandSubsidenceInArizona.htm.
6 Online at http://cesa.asu.edu/sites/default/files/Phil Christensen Intro.pdf.
7 Online at http://ww2.unhabitat.org/programmes/guo/guo_indicators. asp.
8 Online at http://www.iclei.org/index.php?id=801.
9 Online at http://www.iadb.org.
10 Online at http://www.sustainlane.com/us-city-rankings/.
11 Online at http://cityindicators.org.
12 Online at http://water.usgs.gov/nrp/gwsoftware/modflow.html.
13 Online at http://www.wrf-model.org/.
14 Online at http://tmip.fhwa.dot.gov/community/user_groups/transims.
15 Online at http://www.urbansim.org.
16 Online at http://www-01.ibm.com/software/solutions/soa/innov8/cityone.
17Online at http://www.connectedurbandevelopment.org. In 2010, Cisco handed over leadership of CUD to NGOs The Climate Group (http://www.theclimategroup.org) and Metropolis (http://www.metropolis.org).
18 Online at http://www.urbanecomap.org. The Urban EcoMap and companion San Francisco Solar Map (http://sf.solarmap.org) were developed in partnership with engineering firm CH2M HILL.
19 Online at http://www.decisiontheater.org.
20 Online at http://asunews.asu.edu/20100610_hustdecisiontheater.
21 The Manhattan Project and linear accelerators (physics); ground- and space-based telescopes (astronomy); U.S. Global Change Research Program (climate); Earthscope (geology); NEON (ecology).
22 Online at http://www.epa.gov/smartgrowth/partnership/.
23 Arizona State University. Online at http://schoolofsustainability.asu.edu.
24 College of the Atlantic. Online at http://www.coa.edu.
25 Online at http://www.usucoalition.org.
26 European Urban Knowledge Network (http://www.eukn.org/), Sustainable Urban Development European Network (http://www.suden.org/), World Health Organization European Healthy Cities Network.
27Asian Network of Major Cities. Online at http://www.anmc21.org/english/.