IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i8p810-d76216.html
   My bibliography  Save this article

Dynamic Simulation of Urban Expansion Based on Cellular Automata and Logistic Regression Model: Case Study of the Hyrcanian Region of Iran

Author

Listed:
  • Meisam Jafari

    (Department of Environmental Science, Science and Research Branch, Islamic Azad University, Tehran, Iran)

  • Hamid Majedi

    (Department of Art and Architecture, Science and Research Branch, Islamic Azad University, Tehran, Iran)

  • Seyed Masoud Monavari

    (Department of Land use Planning and Assessment, Science and Research Branch, Islamic Azad University, Tehran, Iran)

  • Ali Asghar Alesheikh

    (Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran)

  • Mirmasoud Kheirkhah Zarkesh

    (Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran)

Abstract

The hypothesis addressed in this article is to determine the extent of selected land use categories with respect to their effect on urban expansion. A model that combines a logistic regression model, Markov chain, together with cellular automata based modeling, is introduced here to simulate future urban growth and development in the Gilan Province, Iran. The model is calibrated based on data beginning in 1989 and ending in 2013 and is applied in making predictions for the years 2025 and 2037, across 12 urban development criteria. The relative operating characteristic (ROC) is validated with a very high rate of urban development. The analyzed results indicate that the area of urban land has increased by more than 1.7% that is, from 36,012.5 ha in 1989 to 59,754.8 ha in 2013 and the area of the Caspian Hyrcanian forestland has reduced by 31,628 ha. The simulation results, with respect to prediction, indicate an alarming increase in the rate of urban development in the province by 2025 and 2037 that is, 0.82% and 1.3%, respectively. The development pattern is expected to be uneven and scattered, without following any particular direction. The development will occur close to the existing or newly-formed urban infrastructure and around major roads and commercial areas. If not controlled, this development trend will lead to the loss of 25,101 ha of Hyrcanian forest and, if continued, 21,774 ha of barren and open lands are expected to be destroyed by the year 2037. These results demonstrate the capacity of the integrated model in establishing comparisons with urban plans and their utility to explain both the volume and constraints of urban growth. It is beneficial to apply the integrated approach in urban dynamic assessment through land use modeling with respect to spatio-temporal representation in distinct urban development formats.

Suggested Citation

  • Meisam Jafari & Hamid Majedi & Seyed Masoud Monavari & Ali Asghar Alesheikh & Mirmasoud Kheirkhah Zarkesh, 2016. "Dynamic Simulation of Urban Expansion Based on Cellular Automata and Logistic Regression Model: Case Study of the Hyrcanian Region of Iran," Sustainability, MDPI, vol. 8(8), pages 1-18, August.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:8:p:810-:d:76216
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/8/810/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/8/8/810/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Xin & Zheng, Xin-Qi & Lv, Li-Na, 2012. "A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata," Ecological Modelling, Elsevier, vol. 233(C), pages 11-19.
    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. 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.
    2. Melaku Bogale Fitawok & Ben Derudder & Amare Sewnet Minale & Steven Van Passel & Enyew Adgo & Jan Nyssen, 2020. "Modeling the Impact of Urbanization on Land-Use Change in Bahir Dar City, Ethiopia: An Integrated Cellular Automata–Markov Chain Approach," Land, MDPI, vol. 9(4), pages 1-17, April.
    3. Roghayeh Sadeghi Pasvisheh & Marie Anne Eurie Forio & Long Tuan Ho & Peter L. M. Goethals, 2021. "Evidence-Based Management of the Anzali Wetland System (Northern Iran) Based on Innovative Monitoring and Modeling Methods," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    4. Youjung Kim & Galen Newman & Burak Güneralp, 2020. "A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models," Land, MDPI, vol. 9(8), pages 1-22, July.
    5. Xuesong Gao & Yu Liu & Lun Liu & Qiquan Li & Ouping Deng & Yali Wei & Jing Ling & Min Zeng, 2018. "Is Big Good or Bad?: Testing the Performance of Urban Growth Cellular Automata Simulation at Different Spatial Extents," Sustainability, MDPI, vol. 10(12), pages 1-10, December.
    6. 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.
    7. Sadooghi, Seyed Ehsan & Taleai, Mohammad & Abolhasani, Somaie, 2022. "Simulation of urban growth scenarios using integration of multi-criteria analysis and game theory," Land Use Policy, Elsevier, vol. 120(C).

    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. Wang, Han & Tian, Fuan & Wu, Jianxian & Nie, Xin, 2023. "Is China forest landscape restoration (FLR) worth it? A cost-benefit analysis and non-equilibrium ecological view," World Development, Elsevier, vol. 161(C).
    2. 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.
    3. 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.
    4. Yusuyunjiang Mamitimin & Zibibula Simayi & Ayinuer Mamat & Bumairiyemu Maimaiti & Yunfei Ma, 2023. "FLUS Based Modeling of the Urban LULC in Arid and Semi-Arid Region of Northwest China: A Case Study of Urumqi City," Sustainability, MDPI, vol. 15(6), pages 1-14, March.
    5. Esther Shupel Ibrahim & Bello Ahmed & Oludunsin Tunrayo Arodudu & Jibril Babayo Abubakar & Bitrus Akila Dang & Mahmoud Ibrahim Mahmoud & Halilu Ahmad Shaba & Sanusi Bello Shamaki, 2022. "Desertification in the Sahel Region: A Product of Climate Change or Human Activities? A Case of Desert Encroachment Monitoring in North-Eastern Nigeria Using Remote Sensing Techniques," Geographies, MDPI, vol. 2(2), pages 1-23, April.
    6. Riao, Dao & Guga, Suri & Bao, Yongbin & Liu, Xingping & Tong, Zhijun & Zhang, Jiquan, 2023. "Non-overlap of suitable areas of agro-climatic resources and main planting areas is the main reason for potato drought disaster in Inner Mongolia, China," Agricultural Water Management, Elsevier, vol. 275(C).
    7. Grzegorz Oleniacz, 2021. "Czekanowski’s Diagram and Spatial Data Cluster Analysis for Planning Sustainable Development of Rural Areas," Sustainability, MDPI, vol. 13(20), pages 1-13, October.
    8. Tomasz Zaborowski, 2021. "It’s All about Details. Why the Polish Land Policy Framework Fails to Manage Designation of Developable Land," Land, MDPI, vol. 10(9), pages 1-27, August.
    9. Courage Kamusoko & Yukio Wada & Toru Furuya & Shunsuke Tomimura & Mitsuru Nasu & Khamma Homsysavath, 2013. "Simulating Future Forest Cover Changes in Pakxeng District, Lao People’s Democratic Republic (PDR): Implications for Sustainable Forest Management," Land, MDPI, vol. 2(1), pages 1-19, January.
    10. Jian Gong & Jianxin Yang & Wenwu Tang, 2015. "Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China," IJERPH, MDPI, vol. 12(11), pages 1-24, November.
    11. Mansour, Shawky & Al-Belushi, Mohammed & Al-Awadhi, Talal, 2020. "Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques," Land Use Policy, Elsevier, vol. 91(C).
    12. Haozhe Zhang & Qingyuan Yang & Huiming Zhang & Lulu Zhou & Hongji Chen, 2021. "Optimization of Land Use Based on the Source and Sink Landscape of Ecosystem Services: A Case Study of Fengdu County in the Three Gorges Reservoir Area, China," Land, MDPI, vol. 10(11), pages 1-24, November.
    13. Dingrao Feng & Wenkai Bao & Meichen Fu & Min Zhang & Yiyu Sun, 2021. "Current and Future Land Use Characters of a National Central City in Eco-Fragile Region—A Case Study in Xi’an City Based on FLUS Model," Land, MDPI, vol. 10(3), pages 1-25, March.
    14. Hashem Dadashpoor & Fardis Salarian, 2020. "Urban sprawl on natural lands: analyzing and predicting the trend of land use changes and sprawl in Mazandaran city region, Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 593-614, February.
    15. Zhen Li & Songlin Wu & Shiwen Zhang & Chaojia Nie & Yong Li & Yuanfang Huang, 2020. "Optimization of Land Reuse Structure in Coal Mining Subsided Areas Considering Regional Economic Development: A Case Study in Pei County, China," Sustainability, MDPI, vol. 12(8), pages 1-16, April.
    16. Borowska-Stefańska, Marta & Kobojek, Sławomir & Kowalski, Michał & Lewicki, Marek & Tomalski, Przemysław & Wiśniewski, Szymon, 2021. "Changes in the spatial development of flood hazard areas in Poland between 1990 and 2018 in the light of legal conditions," Land Use Policy, Elsevier, vol. 102(C).
    17. Cheechouyang Faichia & Zhijun Tong & Jiquan Zhang & Xingpeng Liu & Emmanuel Kazuva & Kashif Ullah & Bazel Al-Shaibah, 2020. "Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    18. Zaheer Abbas & Guang Yang & Yuanjun Zhong & Yaolong Zhao, 2021. "Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China," Land, MDPI, vol. 10(6), pages 1-26, June.
    19. Ruci Wang & Hao Hou & Yuji Murayama, 2018. "Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    20. Shufang Wang & Xiyun Jiao & Liping Wang & Aimin Gong & Honghui Sang & Mohamed Khaled Salahou & Liudong Zhang, 2020. "Integration of Boosted Regression Trees and Cellular Automata—Markov Model to Predict the Land Use Spatial Pattern in Hotan Oasis," Sustainability, MDPI, vol. 12(4), pages 1-13, February.

    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:gam:jsusta:v:8:y:2016:i:8:p:810-:d:76216. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.