The statistical physics of cities

Challenges due to the rapid urbanization of the world — especially in emerging countries — range from an increasing dependence on energy to air pollution, socio-spatial inequalities and environmental and sustainability issues. Modelling the structure and evolution of cities is therefore critical because policy makers need robust theories and new paradigms for mitigating these problems. Fortunately, the increased data available about urban systems opens the possibility of constructing a quantitative ‘science of cities’, with the aim of identifying and modelling essential phenomena. Statistical physics plays a major role in this effort by bringing tools and concepts able to bridge theory and empirical results. This Perspective illustrates this point by focusing on fundamental objects in cities: the distribution of the urban population; segregation phenomena and spin-like models; the polycentric transition of the activity organization; energy considerations about mobility and models inspired by gravity and radiation concepts; CO2 emitted by transport; and finally, scaling that describes how various socio-economical and infrastructures evolve when cities grow.This Perspective describes how statistical physics helps understand some of the key aspects of cities: their spatial structure and social organization, the distribution of their population, urban mobility and how some critical factors vary with population.

[1]  R. Gibrat,et al.  Les inégalités économiques : applications, aux inégalitês des richesses, a la concentration des entreprises, aux populations des villes, aux statistiques des familles, etc. : d'une loi nouvelle la loi de l'effet proportionnel , 1931 .

[2]  G. Zipf The P 1 P 2 D Hypothesis: On the Intercity Movement of Persons , 1946 .

[3]  Yuen Ren Chao,et al.  Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology , 1950 .

[4]  E. Wigner Characteristic Vectors of Bordered Matrices with Infinite Dimensions I , 1955 .

[5]  J. Jacobs The Death and Life of Great American Cities , 1962 .

[6]  J. Olsen,et al.  The European Commission , 2020, The European Union.

[7]  Thomas C. Schelling,et al.  Dynamic models of segregation , 1971 .

[8]  Yacov Zahavi,et al.  TRAVELTIME BUDGETS AND MOBILITY IN URBAN AREAS , 1974 .

[9]  David Branston,et al.  LINK CAPACITY FUNCTIONS: A REVIEW , 1976 .

[10]  Masahisa Fujita,et al.  Multiple equilibria and structural transition of non-monocentric urban configurations , 1982 .

[11]  L. Sander,et al.  Diffusion-limited aggregation , 1983 .

[12]  Jeffrey Kenworthy,et al.  Gasoline Consumption and Cities: A Comparison of U.S. Cities with a Global Survey , 1989 .

[13]  N. F. Stewart,et al.  The Gravity Model in Transportation Analysis - Theory and Extensions , 1990 .

[14]  The New York Review of Books; 11 juin 1992; Who Killed Soviet Communism ? Theodore Draper Rand Paper; The Etiology of European Change Carl H. Builder et Steven Bankes , 1992 .

[15]  C. Marchetti Anthropological invariants in travel behavior , 1994 .

[16]  Michael Batty,et al.  Fractal Cities: A Geometry of Form and Function , 1996 .

[17]  H. Stanley,et al.  Modelling urban growth patterns , 1995, Nature.

[18]  D. Sornette,et al.  Convergent Multiplicative Processes Repelled from Zero: Power Laws and Truncated Power Laws , 1996, cond-mat/9609074.

[19]  P. Krugman The Self Organizing Economy , 1996 .

[20]  M. Levy,et al.  POWER LAWS ARE LOGARITHMIC BOLTZMANN LAWS , 1996, adap-org/9607001.

[21]  G. Vojta Fractals and Disordered Systems , 1997 .

[22]  K. Small,et al.  URBAN SPATIAL STRUCTURE. , 1997 .

[23]  M. Mézard,et al.  Out of equilibrium dynamics in spin-glasses and other glassy systems , 1997, cond-mat/9702070.

[24]  M. Marsili,et al.  Interacting Individuals Leading to Zipf's Law , 1998, cond-mat/9801289.

[25]  J. S. Andrade,et al.  Modeling urban growth patterns with correlated percolation , 1998, cond-mat/9809431.

[26]  X. Gabaix Zipf's Law for Cities: An Explanation , 1999 .

[27]  P. Krugman,et al.  The Spatial Economy , 1999 .

[28]  M. Mézard,et al.  Wealth condensation in a simple model of economy , 2000, cond-mat/0002374.

[29]  A. Venables,et al.  The Spatial Economy: Cities, Regions, and International Trade , 2000 .

[30]  Stanley N. Salthe,et al.  Understanding Complexity , 2001, Springer US.

[31]  D. Helbing,et al.  Energy laws in human travel behaviour , 2003, cond-mat/0301386.

[32]  P. Mokhtarian,et al.  TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets , 2004 .

[33]  D. Pumain Scaling laws and urban systems , 2004 .

[34]  Westone,et al.  Home Page , 2004, 2022 2nd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA).

[35]  K. Soo Zipf's law for cities: a cross-country investigation , 2005 .

[36]  P. Bocquier WORLD URBANIZATION PROSPECTS: AN ALTERNATIVE TO THE UN MODEL OF PROJECTION COMPATIBLE WITH URBAN TRANSITION THEORY 1 , 2005 .

[37]  Denise Pumain,et al.  Fractals in urban geography: a theoretical outline and an empirical example , 2005 .

[38]  D. Levinson,et al.  The rational locator reexamined: Are travel times still stable? , 2005 .

[39]  David Levinson,et al.  Self-Organization of Surface Transportation Networks , 2006, Transp. Sci..

[40]  M. Batty Rank clocks , 2006, Nature.

[41]  A. Kirman,et al.  A physical analogue of the Schelling model , 2006, Proceedings of the National Academy of Sciences.

[42]  C. Ratti,et al.  Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis , 2006 .

[43]  Matteo Marsili,et al.  LETTER: Statistical physics of the Schelling model of segregation , 2007 .

[44]  D. Helbing,et al.  Growth, innovation, scaling, and the pace of life in cities , 2007, Proceedings of the National Academy of Sciences.

[45]  Hernán D. Rozenfeld,et al.  Laws of population growth , 2008, Proceedings of the National Academy of Sciences.

[46]  M. Moses,et al.  Cities as Organisms: Allometric Scaling of Urban Road Networks , 2008 .

[47]  Pablo Jensen,et al.  Competition between collective and individual dynamics , 2009, Proceedings of the National Academy of Sciences.

[48]  A. Vespignani Predicting the Behavior of Techno-Social Systems , 2009, Science.

[49]  S. Fortunato,et al.  Statistical physics of social dynamics , 2007, 0710.3256.

[50]  Jean-Pierre Nadal,et al.  Phase diagram of a Schelling segregation model , 2009, 0903.4694.

[51]  Matthias Roth,et al.  Cities as Net Sources of CO 2 : Review of Atmospheric CO2 Exchange in Urban Environments Measured by Eddy Covariance Technique , 2010 .

[52]  L. Benguigui,et al.  Is the Suburban Railway System a Fractal , 2010 .

[53]  Matthew E. Kahn,et al.  The Greenness of Cities: Carbon Dioxide Emissions and Urban Development , 2008 .

[54]  Nagui M. Rouphail,et al.  Bottleneck and Queuing Analysis , 2011 .

[55]  Yannick Malevergne,et al.  Testing the Pareto against the lognormal distributions with the uniformly most powerful unbiased test applied to the distribution of cities. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[56]  Guillaume Deffuant,et al.  A Universal Model of Commuting Networks , 2012, PloS one.

[57]  Marta C. González,et al.  A universal model for mobility and migration patterns , 2011, Nature.

[58]  Vito Latora,et al.  Elementary processes governing the evolution of road networks , 2012, Scientific Reports.

[59]  Cecilia Mascolo,et al.  Correction: A Tale of Many Cities: Universal Patterns in Human Urban Mobility , 2012, PLoS ONE.

[60]  Cecilia Mascolo,et al.  A Tale of Many Cities: Universal Patterns in Human Urban Mobility , 2011, PloS one.

[61]  Michael Batty,et al.  There is More than a Power Law in Zipf , 2012, Scientific Reports.

[62]  M. Batty The New Science of Cities , 2013 .

[63]  J. Bouchaud Crises and Collective Socio-Economic Phenomena: Simple Models and Challenges , 2012, 1209.0453.

[64]  M. Batty,et al.  City boundaries and the universality of scaling laws , 2013 .

[65]  L. Bettencourt,et al.  Supplementary Materials for The Origins of Scaling in Cities , 2013 .

[66]  K. Seto,et al.  Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas , 2013, PloS one.

[67]  Hyejin Youn,et al.  The hypothesis of urban scaling: formalization, implications and challenges , 2013, 1301.5919.

[68]  M. Barthelemy,et al.  Modeling the polycentric transition of cities. , 2013, Physical review letters.

[69]  J. S. Andrade,et al.  Large cities are less green , 2014, Scientific Reports.

[70]  M. Barthelemy,et al.  How congestion shapes cities: from mobility patterns to scaling , 2014, Scientific Reports.

[71]  M. Barthelemy,et al.  From mobile phone data to the spatial structure of cities , 2014, Scientific Reports.

[72]  Zbigniew Smoreda,et al.  The scaling of human interactions with city size , 2012, Journal of The Royal Society Interface.

[73]  Marc Barthelemy,et al.  Anatomy and efficiency of urban multimodal mobility , 2014, Scientific Reports.

[74]  Jacques-François Thisse,et al.  The New Science of Cities by Michael Batty: The Opinion of an Economist , 2014 .

[75]  R'emi Louf,et al.  Scaling: Lost in the Smog , 2014, 1410.4964.

[76]  Mason A. Porter,et al.  Multilayer networks , 2013, J. Complex Networks.

[77]  Geertje Bekebrede,et al.  Understanding Complexity , 2015 .

[78]  F. Creutzig,et al.  Global typology of urban energy use and potentials for an urbanization mitigation wedge , 2015, Proceedings of the National Academy of Sciences.

[79]  M. Batty,et al.  Constructing cities, deconstructing scaling laws , 2013, Journal of The Royal Society Interface.

[80]  Shanjiang Zhu,et al.  Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle , 2015, PloS one.

[81]  Enrique Frías-Martínez,et al.  Uncovering the spatial structure of mobility networks , 2015, Nature Communications.

[82]  Vincent D. Blondel,et al.  A survey of results on mobile phone datasets analysis , 2015, EPJ Data Science.

[83]  M. Barthelemy,et al.  Modelling the relation between income and commuting distance , 2016, Journal of The Royal Society Interface.

[84]  Jorge C. Leitao,et al.  Is this scaling nonlinear? , 2016, Royal Society Open Science.

[85]  Maxime Lenormand,et al.  Systematic comparison of trip distribution laws and models , 2015, 1506.04889.

[86]  András Kovács,et al.  Further We Travel the Faster We Go , 2016, PloS one.

[87]  Marta C. González,et al.  Understanding congested travel in urban areas , 2016, Nature Communications.

[88]  Antonio Lima,et al.  Understanding individual routing behaviour , 2016, Journal of The Royal Society Interface.

[89]  Marc Barthelemy,et al.  The Structure and Dynamics of Cities: Urban Data Analysis and Theoretical Modeling , 2017 .

[90]  Marc Barthelemy,et al.  A stochastic model of randomly accelerated walkers for human mobility , 2015, Nature Communications.

[91]  Nicu Sebe,et al.  The Death and Life of Great Italian Cities: A Mobile Phone Data Perspective , 2016, WWW.

[92]  Sergio Gómez,et al.  Decongestion of Urban Areas with Hotspot Pricing , 2016, ArXiv.

[93]  Alan Wilson,et al.  Complex Spatial Systems: The Modelling Foundations of Urban and Regional Analysis , 2016 .

[94]  Cecilia Mascolo,et al.  If I build it, will they come?: Predicting new venue visitation patterns through mobility data , 2017, SIGSPATIAL/GIS.

[95]  Dominik E. Reusser,et al.  Cities as nuclei of sustainability? , 2013, 1304.4406.

[96]  Mattia Zanella,et al.  Form and urban change – An urban morphometric study of five gentrified neighbourhoods in London , 2017 .

[97]  Michael Batty,et al.  Revealing centrality in the spatial structure of cities from human activity patterns , 2017 .

[98]  J. M. Sobstyl,et al.  Role of structural morphology in urban heat islands , 2017, 1705.00504.

[99]  K. Seto,et al.  Carbon footprints of 13 000 cities , 2018, Environmental Research Letters.

[100]  Marc Barthelemy,et al.  From global scaling to the dynamics of individual cities , 2017, Proceedings of the National Academy of Sciences.

[101]  Wenyun Tang,et al.  Deviation between Actual and Shortest Travel Time Paths for Commuters , 2018, Journal of Transportation Engineering, Part A: Systems.

[102]  Michael Batty,et al.  Using mobility data as proxy for measuring urban vitality , 2018, J. Spatial Inf. Sci..

[103]  Jordan Cambe,et al.  Giant Catalytic Effect of Altruists in Schelling's Segregation Model. , 2018, Physical review letters.

[104]  J. M. Sobstyl,et al.  Role of City Texture in Urban Heat Islands at Nighttime. , 2018, Physical review letters.

[105]  C. Ratti,et al.  Do different datasets tell the same story about urban mobility — A comparative study of public transit and taxi usage , 2018, Journal of Transport Geography.

[106]  H. Dadashpoor,et al.  Centralization or decentralization? A review on the effects of information and communication technology on urban spatial structure , 2018, Cities.

[107]  Carlo Ratti,et al.  Human mobility and socioeconomic status: Analysis of Singapore and Boston , 2018, Comput. Environ. Urban Syst..

[108]  C. Binder,et al.  Evolution of urban scaling: Evidence from Brazil , 2018, PloS one.

[109]  Zoltán Néda,et al.  Commuting patterns: the flow and jump model and supporting data , 2018, EPJ Data Science.

[110]  M. Barthelemy,et al.  Human mobility: Models and applications , 2017, 1710.00004.

[111]  Marc Barthelemy,et al.  Critical factors for mitigating car traffic in cities , 2019, PloS one.

[112]  M. Lafourcade,et al.  The Carbon 'Carprint' of Suburbanization: New Evidence from French Cities , 2018, Regional Science and Urban Economics.