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Replication of Spatio-temporal Land Use Patterns at Three Levels of Aggregation by an Urban Cellular Automata

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Cellular Automata (ACRI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3305))

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Abstract

The SLEUTH urban growth model [1] is a cellular automata model that has been widely applied throughout the geographic literature to examine the historic settlement patterns of cities and to forecast their future growth. In this research, the ability of the model to replicate historical patterns of land use is examined by calibrating the model to fit historical data with 5, 10, and 15 different land use classes. The model demonstrates it robustness in being able to correctly replicate 72-93% of the land use transitions over an eight-year time period, in both space and time.

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References

  1. Clarke, K.C., Hoppen, S., Gaydos, L.: A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B 24, 247–261 (1997)

    Article  Google Scholar 

  2. Batty, M., Xie, Y.: Modelling inside GIS: Part 1. Model structures, exploratory spatial data analysis and aggregation. International Journal of Geographical Information Systems 8, 291–307 (1994)

    Article  Google Scholar 

  3. Tobler, W.: Cellular Geography. In: Gale, S., Olsson, G. (eds.) Philosophy in Geography, pp. 379–386. D. Reidel Publishing Company, Dordrecht (1979)

    Google Scholar 

  4. Couclelis, H.: Cellular worlds: a framework for modeling micro-macro dynamics. International Journal of Urban and Regional Research 17, 585–596 (1985)

    Google Scholar 

  5. Torrens, P., O’Sullivan, D.: Cellular automata and urban simulation: where do we go from here? Environment and Planning B 28, 163–168 (2001)

    Article  Google Scholar 

  6. Couclelis, H.: Of mice and men: What rodent populations can teach us about complex spatial dynamics. Environment and Planning A 29, 99–109 (1988)

    Article  Google Scholar 

  7. Batty, M., Xie, Y.: Possible urban automata. Environment and Planning B 24, 175–192 (1997)

    Article  Google Scholar 

  8. White, R., Engelen, G.: Cellular automata and fractal urban form: a cellular modeling approach to the evolution of urban land-use patterns. Environment and Planning A 25, 1175–1199 (1993)

    Article  Google Scholar 

  9. Silva, E.A., Clarke, K.C.: Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal. Computers, Environment and Urban Systems 26, 525–552 (2002)

    Article  Google Scholar 

  10. Yang, X., Lo, C.P.: Modelling urban growth and landscape change in the Atlanta metropolitan area. International Journal of Geographical Information Science 17, 463–488 (2003)

    Article  Google Scholar 

  11. Jantz, C.A., Goetz, S.J., Shelley, M.K.: Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Baltimore-Washington metropolitan area. Environment and Planning B 31, 251–271 (2004)

    Article  Google Scholar 

  12. Clarke, K.C.: Land use modeling with Deltatrons. In: The Land Use Modeling Conference, Sioux Falls, South Dakota June 5-6 (1997), http://www.ncgia.ucsb.edu/conf/landuse97/

  13. Dietzel, C.: Spatio-temporal difference in model outputs and parameter space as determined by calibration extent. In: Atkinson, P., Foody, G., Darby, S., Wu, F. (eds.) Geodynamics. Taylor and Francis, London (2004)

    Google Scholar 

  14. Project Gigalopolis Webpage, www.ncgia.ucsb.edu/projects/gig

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© 2004 Springer-Verlag Berlin Heidelberg

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Dietzel, C., Clarke, K.C. (2004). Replication of Spatio-temporal Land Use Patterns at Three Levels of Aggregation by an Urban Cellular Automata. In: Sloot, P.M.A., Chopard, B., Hoekstra, A.G. (eds) Cellular Automata. ACRI 2004. Lecture Notes in Computer Science, vol 3305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30479-1_54

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  • DOI: https://doi.org/10.1007/978-3-540-30479-1_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23596-5

  • Online ISBN: 978-3-540-30479-1

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