IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v47y2020i6p1047-1064.html
   My bibliography  Save this article

Modelling urban growth incorporating spatial interactions between the cities: The example of the Tehran metropolitan region

Author

Listed:
  • Sanaz Alaei Moghadam
  • Mohammad Karimi

    (K.N. Toosi University of Technology, Iran)

  • Kyoumars Habibi

Abstract

Interactions between cities play a significant role in the development of metropolitan regions. Although these interactions and their role in the urban growth modelling have already been investigated, there is still room for more studies. In this research, in addition to conventional urban growth factors, spatial interactions between the cities (SIBC) are incorporated into urban growth modelling. This causes directional trends in urban growth (DTUG). Therefore, first the DTUG of each city was measured using a developed indicator based on the history of urban growth that was extracted from satellite images and spatial statistics. The SIBC was then estimated by integrating the DTUG of the cities. Finally, the SIBC and other driving forces, including the physical suitability, accessibility and neighbourhood effects, were integrated using a cellular automata-based model. The accuracy of the model in the Tehran metropolitan region was increased by 6.44% after considering the SIBC. The analysis of the DTUG and SIBC in the Tehran metropolitan region during 1991–2000–2007–2014 revealed specific patterns as the spatial interactions intensified over time and usually peaked in the periphery of the central business districts and intense interactions existed between the metropolises and other major cities. These findings could help urban managers with strategic decision-making in the metropolitan regions and adjust the science and practice relation in this field.

Suggested Citation

  • Sanaz Alaei Moghadam & Mohammad Karimi & Kyoumars Habibi, 2020. "Modelling urban growth incorporating spatial interactions between the cities: The example of the Tehran metropolitan region," Environment and Planning B, , vol. 47(6), pages 1047-1064, July.
    • Handle: RePEc:sae:envirb:v:47:y:2020:i:6:p:1047-1064
    DOI: 10.1177/2399808318816701
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/2399808318816701
    Download Restriction: no
    File URL: https://libkey.io/10.1177/2399808318816701?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. Bin Wang & Wenzhong Shi & Zelang Miao, 2015. "Confidence Analysis of Standard Deviational Ellipse and Its Extension into Higher Dimensional Euclidean Space," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-17, March.
    2. Robert Pontius & Wideke Boersma & Jean-Christophe Castella & Keith Clarke & Ton Nijs & Charles Dietzel & Zengqiang Duan & Eric Fotsing & Noah Goldstein & Kasper Kok & Eric Koomen & Christopher Lippitt, 2008. "Comparing the input, output, and validation maps for several models of land change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 11-37, March.
    3. repec:asg:wpaper:1001 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    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. Fei Tao & Guoan Tang & Yihao Wu & Tong Zhou, 2022. "Spatiotemporal Heterogeneity and Driving Mechanism of Co-Ordinated Urban Development: A Case Study of the Central Area of the Yangtze River Delta, China," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
    2. Yang, Yuanyuan & Bao, Wenkai & Liu, Yansui, 2020. "Scenario simulation of land system change in the Beijing-Tianjin-Hebei region," Land Use Policy, Elsevier, vol. 96(C).
    3. Youjung Kim & Galen Newman, 2019. "Climate Change Preparedness: Comparing Future Urban Growth and Flood Risk in Amsterdam and Houston," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    4. Aritta Suwarno & Meine van Noordwijk & Hans-Peter Weikard & Desi Suyamto, 2018. "Indonesia’s forest conversion moratorium assessed with an agent-based model of Land-Use Change and Ecosystem Services (LUCES)," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(2), pages 211-229, February.
    5. Yuanyuan Yang & Shuwen Zhang & Jiuchun Yang & Xiaoshi Xing & Dongyan Wang, 2015. "Using a Cellular Automata-Markov Model to Reconstruct Spatial Land-Use Patterns in Zhenlai County, Northeast China," Energies, MDPI, vol. 8(5), pages 1-21, May.
    6. Bonoua Faye & Guoming Du & Edmée Mbaye & Chang’an Liang & Tidiane Sané & Ruhao Xue, 2023. "Assessing the Spatial Agricultural Land Use Transition in Thiès Region, Senegal, and Its Potential Driving Factors," Land, MDPI, vol. 12(4), pages 1-20, March.
    7. Rifat, Shaikh Abdullah Al & Liu, Weibo, 2022. "Predicting future urban growth scenarios and potential urban flood exposure using Artificial Neural Network-Markov Chain model in Miami Metropolitan Area," Land Use Policy, Elsevier, vol. 114(C).
    8. Jing Yang & Feng Shi & Yizhong Sun & Jie Zhu, 2019. "A Cellular Automata Model Constrained by Spatiotemporal Heterogeneity of the Urban Development Strategy for Simulating Land-use Change: A Case Study in Nanjing City, China," Sustainability, MDPI, vol. 11(15), pages 1-19, July.
    9. Brian Pickard & Joshua Gray & Ross Meentemeyer, 2017. "Comparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change Models," Land, MDPI, vol. 6(3), pages 1-21, August.
    10. Ju-Sung Lee & Tatiana Filatova & Arika Ligmann-Zielinska & Behrooz Hassani-Mahmooei & Forrest Stonedahl & Iris Lorscheid & Alexey Voinov & J. Gareth Polhill & Zhanli Sun & Dawn C. Parker, 2015. "The Complexities of Agent-Based Modeling Output Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-4.
    11. Yafang Bao & Hanjing Jiang & Emily Ma & Zhi Sun & Lihua Xu, 2022. "A Longitudinal Spatial-Temporal Analysis of Ancient Village Tourism Development in Zhejiang, China," Sustainability, MDPI, vol. 15(1), pages 1-20, December.
    12. Zhang, Yan & Chang, Xia & Liu, Yanfang & Lu, Yanchi & Wang, Yiheng & Liu, Yaolin, 2021. "Urban expansion simulation under constraint of multiple ecosystem services (MESs) based on cellular automata (CA)-Markov model: Scenario analysis and policy implications," Land Use Policy, Elsevier, vol. 108(C).
    13. Andreas Rauh & Stefan Wirtensohn & Patrick Hoher & Johannes Reuter & Luc Jaulin, 2022. "Reliability Assessment of an Unscented Kalman Filter by Using Ellipsoidal Enclosure Techniques," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    14. Margaret Gitau & Nathaniel Bailey, 2012. "Multi-Layer Assessment of Land Use and Related Changes for Decision Support in a Coastal Zone Watershed," Land, MDPI, vol. 1(1), pages 1-27, December.
    15. Xiaoli Hu & Xin Li & Ling Lu, 2018. "Modeling the Land Use Change in an Arid Oasis Constrained by Water Resources and Environmental Policy Change Using Cellular Automata Models," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    16. Yaya Jin & Jiahe Ding & Yue Chen & Chaozheng Zhang & Xianhui Hou & Qianqian Zhang & Qiankun Liu, 2023. "Urban Land Expansion Simulation Considering the Increasing versus Decreasing Balance Policy: A Case Study in Fenghua, China," Land, MDPI, vol. 12(12), pages 1-21, November.
    17. Charlotte Shade & Peleg Kremer, 2019. "Predicting Land Use Changes in Philadelphia Following Green Infrastructure Policies," Land, MDPI, vol. 8(2), pages 1-19, February.
    18. repec:ris:cieodp:2013_019 is not listed on IDEAS
    19. Wu, Wei & Yeager, Kevin M. & Peterson, Mark S. & Fulford, Richard S., 2015. "Neutral models as a way to evaluate the Sea Level Affecting Marshes Model (SLAMM)," Ecological Modelling, Elsevier, vol. 303(C), pages 55-69.
    20. Robert Gilmore Pontius, 2018. "Criteria to Confirm Models that Simulate Deforestation and Carbon Disturbance," Land, MDPI, vol. 7(3), pages 1-14, September.
    21. Kikuko Shoyama, 2021. "Assessment of Land-Use Scenarios at a National Scale Using Intensity Analysis and Figure of Merit Components," Land, MDPI, vol. 10(4), pages 1-13, April.

    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:envirb:v:47:y:2020:i:6:p:1047-1064. 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.