IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v30y1998i11p1943-1967.html
   My bibliography  Save this article

Urban Evolution on the Desktop: Simulation with the Use of Extended Cellular Automata

Author

Listed:
  • M Batty

    (Centre for Advanced Spatial Analysis, University College London, 1-19 Torrington Place, London WC1E 6BT, England)

Abstract

There is now wide agreement that to develop effective simulations of urban structure, urban models must be explicitly dynamic and must contain mechanisms for linking macrostructure to micro-behaviour. In this paper, the author poses the need to develop simple simulations which emphasise the conditions under which spontaneous growth, such as that which characterises the regeneration of inner cities and the location of edge cities, can be modelled. The model that is presented is based on the integration of positive feedback with the effects of local interaction, all set within a context in which innovations are produced randomly as spatial noise. The framework adopted to make this model operational is based on an extended cellular automaton in which demand for location, conceived of as potential for development, drives the system which responds through the supply of actual development. Various structures for such models are considered. The simulations are set up within a desktop environment by using the package StarLogo as the simulator, DataDesk as the means for exploring model results graphically and statistically, and Avid VideoShop as the moviemaker for simulating the dynamics of locational change. Experiments are conducted which involve systematically varying the weights or parameters of the feedback, interaction, and innovation effects, and then examining how the growth rate of the system interacts with locational change. The model is generalised to other situations where the growth of systems of cities are simulated and where the effects of self-organisation within the simulated patterns of locational change are examined. In essence, the model is able to predict the spontaneous growth of centres but under conditions where there is a high degree of noise or innovation in the system and where the growth rate is also high.

Suggested Citation

  • M Batty, 1998. "Urban Evolution on the Desktop: Simulation with the Use of Extended Cellular Automata," Environment and Planning A, , vol. 30(11), pages 1943-1967, November.
    • Handle: RePEc:sae:envira:v:30:y:1998:i:11:p:1943-1967
    DOI: 10.1068/a301943
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/a301943
    Download Restriction: no
    File URL: https://libkey.io/10.1068/a301943?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. R White & G Engelen, 1993. "Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns," Environment and Planning A, , vol. 25(8), pages 1175-1199, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rongxu Qiu & Wei Xu & John Zhang & Karl Staenz, 2018. "Modeling and simulating industrial land-use evolution in Shanghai, China," Journal of Geographical Systems, Springer, vol. 20(1), pages 57-83, January.
    2. Eric de Noronha Vaz & Teresa de Noronha & Peter Nijkamp, 2013. "An Exploratory Landscape Metrics Approach to Agricultural Changes: Applications of Spatial Economic Consequences for the Algarve, Portugal," Tinbergen Institute Discussion Papers 13-140/VIII, Tinbergen Institute.
    3. Zimu Jia & Bingran Ma & Jing Zhang & Weihua Zeng, 2018. "Simulating Spatial-Temporal Changes of Land-Use Based on Ecological Redline Restrictions and Landscape Driving Factors: A Case Study in Beijing," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
    4. Wickramasuriya, Rohan Chandralal & Bregt, Arnold K. & van Delden, Hedwig & Hagen-Zanker, Alex, 2009. "The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model," Ecological Modelling, Elsevier, vol. 220(18), pages 2302-2309.
    5. Di Traglia, Mario & Attorre, Fabio & Francesconi, Fabio & Valenti, Roberto & Vitale, Marcello, 2011. "Is cellular automata algorithm able to predict the future dynamical shifts of tree species in Italy under climate change scenarios? A methodological approach," Ecological Modelling, Elsevier, vol. 222(4), pages 925-934.
    6. Shen, Yu & de Abreu e Silva, João & Martínez, Luis Miguel, 2014. "Assessing High-Speed Rail’s impacts on land cover change in large urban areas based on spatial mixed logit methods: a case study of Madrid Atocha railway station from 1990 to 2006," Journal of Transport Geography, Elsevier, vol. 41(C), pages 184-196.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kwok Hung Lau & Booi Hon Kam, 2005. "A Cellular Automata Model for Urban Land-Use Simulation," Environment and Planning B, , vol. 32(2), pages 247-263, April.
    2. José I Barredo & Luca Demicheli & Carlo Lavalle & Marjo Kasanko & Niall McCormick, 2004. "Modelling Future Urban Scenarios in Developing Countries: An Application Case Study in Lagos, Nigeria," Environment and Planning B, , vol. 31(1), pages 65-84, February.
    3. Caruso, Geoffrey & Peeters, Dominique & Cavailhes, Jean & Rounsevell, Mark, 2007. "Spatial configurations in a periurban city. A cellular automata-based microeconomic model," Regional Science and Urban Economics, Elsevier, vol. 37(5), pages 542-567, September.
    4. C J Webster & F Wu, 1999. "Regulation, Land-Use Mix, and Urban Performance. Part 1: Theory," Environment and Planning A, , vol. 31(8), pages 1433-1442, August.
    5. Michel Opelele Omeno & Ying Yu & Wenyi Fan & Tolerant Lubalega & Chen Chen & Claude Kachaka Sudi Kaiko, 2021. "Analysis of the Impact of Land-Use/Land-Cover Change on Land-Surface Temperature in the Villages within the Luki Biosphere Reserve," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    6. M Batty & Y Xie, 1994. "From Cells to Cities," Environment and Planning B, , vol. 21(7), pages 31-48, December.
    7. repec:rre:publsh:v:33:y:2003:i:3:p:264-83 is not listed on IDEAS
    8. Stephen M McCauley & John Rogan & James T Murphy & Billie L Turner & Samuel Ratick, 2015. "Modeling the Sociospatial Constraints on Land-Use Change: The Case of Periurban Sprawl in the Greater Boston Region," Environment and Planning B, , vol. 42(2), pages 221-241, April.
    9. Liu, Dongya & Zheng, Xinqi & Zhang, Chunxiao & Wang, Hongbin, 2017. "A new temporal–spatial dynamics method of simulating land-use change," Ecological Modelling, Elsevier, vol. 350(C), pages 1-10.
    10. Ricardo Ruiz & Bernardo Alves Furtado, 2007. "An Agent Based Model for Urban Structure: the case of Belo Horizonte - Brazil," EcoMod2007 23900079, EcoMod.
    11. Nerea Martín-Raya & Jaime Díaz-Pacheco & Abel López-Díez & Pedro Dorta Antequera & Amílcar Cabrera, 2023. "A lava flow simulation experience oriented to disaster risk reduction, early warning systems and response during the 2021 volcanic eruption in Cumbre Vieja, La Palma," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(3), pages 3331-3351, July.
    12. Parker, Dawn Cassandra, 2007. "Revealing "space" in spatial externalities: Edge-effect externalities and spatial incentives," Journal of Environmental Economics and Management, Elsevier, vol. 54(1), pages 84-99, July.
    13. Eda Ustaoglu & Brendan Williams & Laura O. Petrov & Harutyun Shahumyan & Hedwig Van Delden, 2017. "Developing and Assessing Alternative Land-Use Scenarios from the MOLAND Model: A Scenario-Based Impact Analysis Approach for the Evaluation of Rapid Rail Provisions and Urban Development in the Greate," Sustainability, MDPI, vol. 10(1), pages 1-34, December.
    14. Yan Liu & Yongjiu Feng, 2016. "Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China," Sustainability, MDPI, vol. 8(10), pages 1-16, October.
    15. François Sémécurbe & Cécile Tannier & Stéphane G. Roux, 2019. "Applying two fractal methods to characterise the local and global deviations from scale invariance of built patterns throughout mainland France," Journal of Geographical Systems, Springer, vol. 21(2), pages 271-293, June.
    16. Man, Wang & Nie, Qin & Li, Zongmei & Li, Hui & Wu, Xuewen, 2019. "Using fractals and multifractals to characterize the spatiotemporal pattern of impervious surfaces in a coastal city: Xiamen, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 44-53.
    17. André Ménard & Danielle J Marceau, 2005. "Exploration of Spatial Scale Sensitivity in Geographic Cellular Automata," Environment and Planning B, , vol. 32(5), pages 693-714, October.
    18. Haozhi Pan & Stan Geertman & Brian Deal, 2020. "What does urban informatics add to planning support technology?," Environment and Planning B, , vol. 47(8), pages 1317-1325, October.
    19. Qindong Fan & Fengtian Du & Hu Li, 2020. "A Study of the Spatial Form of Maling Village, Henan, China," Sustainability, MDPI, vol. 12(18), pages 1-24, September.
    20. Md. Monjure Alam Pramanik & Demetris Stathakis, 2016. "Forecasting urban sprawl in Dhaka city of Bangladesh," Environment and Planning B, , vol. 43(4), pages 756-771, July.
    21. Linfeng Xu & Xuan Liu & De Tong & Zhixin Liu & Lirong Yin & Wenfeng Zheng, 2022. "Forecasting Urban Land Use Change Based on Cellular Automata and the PLUS Model," Land, MDPI, vol. 11(5), pages 1-16, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envira:v:30:y:1998:i:11:p:1943-1967. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.