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Dr. Paul M. Torrens, Center for Urban Science + Progress, New York University

A toolkit for measuring sprawl

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Project overview

Debate regarding suburban sprawl in urban studies is contentious. It is fair to say that the phenomenon is not fully understood to satisfaction in the academic, policy, or planning communities and there are a host of reasons why this may be the case. Characterization of sprawl in the literature is often narrative and subjective. Measurement is piecemeal and largely data-driven. Existing studies yield contrary results for the same cities in many cases. The partial appreciation for the intricacies of sprawl is problematic. In practice, city planning agencies and citizen advocacy groups are scrambling to suggest and develop "smart growth" strategies to curb sprawl, without a strong empirical basis for measuring the phenomenon. Yet, sprawl is extremely popular with consumers.


In this project, we are developing an innovative approach to diagnosing sprawl, looking across the full range of its characteristic attributes in a comprehensive fashion that is robust to some well-known challenges. This proves to be very useful in sweeping the parameter space of the phenomenon, enabling the visualization and valuation of sprawl surfaces across attributes, allowing us to check the pulse of a developing city. We have already applied the work to some well-known, but controversial exemplars of American sprawl, with the surprising result that sprawl and "smart growth" are found to co-exist and co-evolve. This raises questions about relationships between the two, with consequences for planning and public policy.


We have developed a 42-metric empirical scheme as foundation for an extensible toolkit for measuring sprawl:

Eye candy

Local hotspots and coolspots of population density


Population density surfaces


Accessibility to the the city's top-500 employers


Accessibility to the city's central business district

Torrens, P.M. (2000-2004) “Sprawlsim”. UK Economic and Social Research Council (Postgraduate Studentship)
Guhathakurta, S.; Bender, D.; Crittenden, J.; Collins, D.; Holston, J.; Kobayashi, Y.; Konjevod, G.; Li, K.; Lant, T.; Morton, T.; Patel, M.; Torrens, P.M. (2006-2010) “Digial Phoenix”. Herberger Foundation
Related groups
Environmental Simulation Laboratory, Tel Aviv University
Centre for Advanced Spatial Analysis (CASA), University College London
SLUCE Project, University of Michigan
Center for Urban Simulation and Policy Analysis (Urbansim), University of Washington
Project Gigalopolis, NCGIA, UC Santa Barbara
Environmental Simulation Center, New York
Urban Ecology Research Laboratory, University of Washington
Complex Systems Research Centre, Cranfield University
HEGIS Lab, University of Minnesota
Digital Phoenix, Arizona State University


GIS movement tracks

Big data movement analytics


climate indicators spatial analysis

Land indicators of climate

geosimulation high performance computing

High-performance computing and networking for geosimulation

earthquake model agent based GIS

Earthquake models

CA ice sheet model

Ice-sheet modeling

kinect control of GIS and robots
Robot motion control

simulating disasters ABM GIS
Human behavior in critical scenarios

crowd model riot model simulation wired

Modeling riots

physics engine GIS

Dynamic physics for built infrastructure

moving agents through space and time

Moving agents through space and time

validating agent based models

Validating agent-based models

machine learning GIS

Machine-learning behavioral geography

high performance computing urban simulation emergence

Accelerating agent-based models

megacity models

Megacity futures

immersive modeling

Immersive modeling

space-time GIS

Space-time GIS and analysis

measuring sprawl

A toolkit for measuring sprawl

space-time GIS

Modeling time, space, and behavior

simulating crowd behavior

Simulating crowd behavior

wi-fi geography

Wi-Fi geography

Simulating sprawl

Simulating sprawl