Fifty Years of Urban Modeling: Macro-Statics to Micro-Dynamics

  • Michael Batty


This chapter presents both a chronological and conceptual history of urban land use-transportation models movement in the context of current developments. Such models —‘urban models’ for short — first appeared in the 1950s in North America and were made possible by two interrelated forces: the development of digital computing from which large-scale simulation emanated, and policy imperatives for testing the effects of large-scale public investments on cities. Essentially, urban models are still pragmatically motivated tools for testing the impact of changes in the locations of land use and transportation on dense and usually large urban agglomerations. Planning and policy determine their rationale although their foundations are built on theoretical ideas which go back to the roots of modern social science and the influence of physics and mathematics from the time of the Enlightenment. During the brief but turbulent years since this field has developed, there have been substantial shifts in viewpoint. Indeed even the paradigms that condition what attributes of the city are to be modeled, and the way such modeling takes place, have changed. We will chart these changes, beginning with a set of intersecting time lines focusing on theoretical origins and practical applications. We will show how urban models were first conceived in aggregative, static terms when the concern was for simulating the way cities appeared at a cross-section in time. This aggregative, static conception of urban structure has slowly given way to one where much more detailed disaggregate activities appear more important and where dynamics rather than statics is the focus. This reflects as much our abilities to simulate more elaborate computational structures and collect better data as any grand theoretical revision of the way we look at the city, although such a revision is now under way As such, this chapter sets a context for many of the current advances in urban modeling reported elsewhere in this book.


Cellular Automaton Cellular Automaton Urban Growth Location Theory Cellular Automaton Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Allen PM (1997) Cities and Regions as Self-Organizing Systems: Models of Complexity. Taylor and Francis, LondonGoogle Scholar
  2. Alonso W (1964) Location and Land Use. Harvard University Press, Cambridge, MAGoogle Scholar
  3. Anas A (1982) Residential Location Markets and Urban Transportation: Economic Theory, Econometrics and Policy Analysis with Discrete Choice Models. Academic Press, New YorkGoogle Scholar
  4. Andersson C (2005) Urban Evolution. Doctoral thesis, Chalmers Institute of Technology, Göteborg, SwedenGoogle Scholar
  5. Ball P (2004) Critical Mass: How One Thing Leads to Another. Heinemann, LondonGoogle Scholar
  6. Batty M (1971) Modelling Cities as Dynamic Systems. Nature 231: 425–428CrossRefGoogle Scholar
  7. Batty M (1979) Progress, Success and Failure in Urban Modelling. Environment and Planning A 11: 863–878CrossRefGoogle Scholar
  8. Batty M (2005a) Cities and Complexity. MIT Press, Cambridge, MAGoogle Scholar
  9. Batty M (2005b) Agents, Cells, and Cities: New Representational Models for Simulating Multi-scale Urban Dynamics. Environment and Planning A 37, in pressGoogle Scholar
  10. Batty M, Longley PA (1994) Fractal Cities: A Geometry of Form and Function. Academic Press, San Diego, CAGoogle Scholar
  11. Ben Akiva M, Lerman S (1985) Discrete Choice Analysis. MIT Press, Cambridge, MAGoogle Scholar
  12. Chapin FS, Weiss SF (1968) A Probabilistic Model for Residential Growth. Transportation Research 2: 375–390CrossRefGoogle Scholar
  13. Christaller W (1966) Central Places in Southern Germany. Prentice-Hall, Englewood Cliffs, NJ (translated from the 1933 German Edition Die Zentralen Orte in Suddeutschland by CW Baskin)Google Scholar
  14. Clarke G (ed) (1996) Microsimulation for Urban and Regional Policy Analysis. Pion Press, LondonGoogle Scholar
  15. Clarke KC, Hoppen S, Gaydos L (1997) A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area. Environment and Planning B 24: 247–261CrossRefGoogle Scholar
  16. Couclelis H (1985) Cellular Worlds: A Framework for Modeling Micro-Macro Dynamics. Environment and Planning A 17: 585–596CrossRefGoogle Scholar
  17. de la Barra T (1989) Integrated Land Use and Transport Modelling. Cambridge University Press, CambridgeGoogle Scholar
  18. Dendrinos DS, Mullally H (1985) Urban Evolution: Studies in the Mathematical Ecology of Cities. Oxford University Press, Oxford, UKGoogle Scholar
  19. Dendrinos DS, Sonis M (1990) Chaos and Socio-Spatial Dynamics. Springer, New YorkGoogle Scholar
  20. Echenique M (1985) The Use of Integrated Land Use and Transport Models: The Cases of Sao Paulo, Brazil and Bilbao, Spain. In: Florian M (ed) The Practice of Transportation Planning. Elsevier, AmsterdamGoogle Scholar
  21. Forrester JW (1969) Urban Dynamics. MIT Press, Cambridge, MAGoogle Scholar
  22. Fujita M (1989) Urban Economic Theory: Land Use and City Size. Cambridge University Press, Cambridge, UKGoogle Scholar
  23. Fujita M, Krugman P, Venables AJ (1999) The Spatial Economy: Cities, Regions, and International Trade. MIT Press, Cambridge, MAGoogle Scholar
  24. Gottman J (1957) Megalopolis, or the Urbanisation of the North Eastern Seaboard. Economic Geography 33: 189–200CrossRefGoogle Scholar
  25. Guhathakurta S (2002) Urban Modeling as Storytelling: Using Simulation Models as Narrative, Environment and Planning B 29: 895–911CrossRefGoogle Scholar
  26. Harris B (1965) Urban Development Models: A New Tool for Planners. Journal of the American Institute of Planners 31: 90–95Google Scholar
  27. Harris B, Britton B (1985) Urban Simulation Models in Regional Science. Journal of Regional Science 25: 548–568Google Scholar
  28. Ingram GK, Kain JF, Ginn JR (1972) The Detroit Prototype of the NBER Urban Simulation Model. National Bureau of Economic Research, Columbia University Press, New YorkGoogle Scholar
  29. Isard W (1956) Location and Space-Economy: A General Theory Relating to Industrial Location, Market Areas, Land Use, Trade and Urban Structure. MIT Press, Cambridge, MAGoogle Scholar
  30. Landis JD, Zhang M (1998) The Second Generation of the California Urban Futures Model. Part 1: Model Logic and Theory. Environment and Planning B 25: 657–666CrossRefGoogle Scholar
  31. Lathrop GT, Hamburg JR (1965) An Opportunity-Accessibility Model for Allocating Regional Growth. Journal of the American Institute of Planners 31: 95–103Google Scholar
  32. Lee DB (1973) Requiem for Large Scale Models. Journal of the American Institute of Planners 39: 163–178Google Scholar
  33. Losch A (1954) The Economics of Location. Yale University Press, New Haven, CN (translated from the 1943 German Edition Die Raumliche Ordnung der Wirtschaft by WH Woglom)Google Scholar
  34. Lowry IS (1964) Model of Metropolis. Memorandum RM-4035-RC, Rand Corporation, Santa Monica, CAGoogle Scholar
  35. Maguire D, Batty M, Goodchild M (eds)(2005) GIS, Spatial Analysis, and Modeling. ESRI Press, Redlands, CAGoogle Scholar
  36. Mayer HM, Kohn CF (eds) (1959) Readings in Urban Geography. University of Chicago Press, Chicago, IllinoisGoogle Scholar
  37. Nijkamp P, Reggiani A (1992) Interaction, Evolution and Chaos in Space. Springer, BerlinGoogle Scholar
  38. Park RE, Burgess EW (1925) The City. University of Chicago Press, Chicago, IllinoisGoogle Scholar
  39. Portugali J (2000) Self-Organization and the City. Springer, BerlinGoogle Scholar
  40. Propolis Consortium (2004) PROPOLIS (Policies and Research of Policies for Land Use and Transport for Increasing Urban Sustainability). Final Report for the Commission of the European Communities, from LT Consultants Ltd., Helsinki, FinlandGoogle Scholar
  41. Putman SH (1991) Integrated Urban Models 2. New Research and Applications of Optimization and Dynamics. Pion, London, UKGoogle Scholar
  42. Schweitzer F (2003) Brownian Agents and Active Particles: Collective Dynamics in the Natural and Social Sciences. Springer, BerlinGoogle Scholar
  43. Spartacus Consortium (1998) SPARTACUS (System for Planning and Research in Towns and Cities for Urban Sustainability). Final Report for the Commission of the European Communities, from LT Consultants Ltd., Helsinki, FinlandGoogle Scholar
  44. Thom R (1975) Structural Stability and Morphogenesis. Benjamin, Reading, MAGoogle Scholar
  45. Tobler WR (1970) A Computer Movie Simulating Population Growth in the Detroit Region. Economic Geography 42: 234–240CrossRefGoogle Scholar
  46. Tobler WR (1979) Cellular Geography. In Gale S, Olsson G (eds) Philosophy in Geography. Reidel, Dordrecht, pp 279–386Google Scholar
  47. von Thünen JH (1966) Von Thünen’s Isolated State. Pergamon, Oxford, UK (translation from the 1826 German Edition Der Isolierte Staat in Beziehung auf Landwirtschaft und Nationaloekonomie by PG Hall)Google Scholar
  48. Voorhees AM (1959) Land Use and Traffic Models. Journal of the American Institute of Planners 25: 55–57Google Scholar
  49. Waddell P (2002) UrbanSim: Modeling Urban Development for Land Use, Transportation and Environmental Planning. Journal of the American Planning Association 68: 297–314Google Scholar
  50. Webster FV, Bly P, Paulley NJ (eds)(1988) Urban Land Use and Transport: Policies and Models. Avebury, Aldershot, UKGoogle Scholar
  51. Wegener M (1994) Operational Urban Models: State of the Art. Journal of the American Planning Association 60: 17–29Google Scholar
  52. Wegener M (2004) Overview of land-use transport models. In: Henscher DA, Button K (eds) Transport Geography and Spatial Systems. Handbook 5 of the Handbook in Transport, Pergamon/Elsevier Science, Kidlington, UKGoogle Scholar
  53. White RW, Engelen G (1997) Cellular Automaton as the Basis of Integrated Dynamic Regional Modelling. Environment and Planning B 24: 235–246CrossRefGoogle Scholar
  54. Wilson AG (1970) Entropy in Urban and Regional Modelling. Pion Press, LondonGoogle Scholar
  55. Wilson AG (1981) Catastrophe Theory and Bifurcation: Applications to Urban and Regional Systems. University of California Press, Berkeley, CAGoogle Scholar
  56. Wilson AG, Coelho JD, Macgill SM, Williams HCWL (1981) Optimization in Locational and Transport Analysis. John Wiley, Chichester, UKGoogle Scholar
  57. Zipf GK (1949) Human Behavior and The Principle of Least Effort. Addison-Wesley, Cambridge, MAGoogle Scholar

Copyright information

© Physica-Verlag Heidelberg and Accademia di Architettura, Mendrisio, Switzerland 2008

Authors and Affiliations

  • Michael Batty
    • 1
  1. 1.Centre for Advanced Spatial Analysis (CASA)University College LondonUK

Personalised recommendations