IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i15p4012-d251344.html
   My bibliography  Save this article

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

Author

Listed:
  • Jing Yang

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China
    School of Geography, Nanjing Normal University, Nanjing 210023, China
    College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Feng Shi

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China
    School of Geography, Nanjing Normal University, Nanjing 210023, China
    College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China)

  • Yizhong Sun

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Nanjing 210023, China
    School of Geography, Nanjing Normal University, Nanjing 210023, China)

  • Jie Zhu

    (College of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China)

Abstract

While cellular automata (CA) has become increasingly popular in land-use and land-cover change (LUCC) simulations, insufficient research has considered the spatiotemporal heterogeneity of urban development strategies and applied it to constrain CA models. Consequently, we proposed to add a zoning transition rule and planning influence that consists of a development grade coefficient and traffic facility coefficient in the CA model to reflect the top-down and heterogeneous characteristics of spatial layout and the dynamic and heterogeneous external interference of traffic facilities on land-use development. Testing the method using Nanjing city as a case study, we show that the optimal combinations of development grade coefficients are different in different districts, and the simulation accuracies are improved by adding the grade coefficients into the model. Moreover, the integration of the traffic facility coefficient does not improve the model accuracy as expected because the deployment of the optimal spatial layout has considered the effect of the subway on land use. Therefore, spatial layout planning is important for urban green, humanistic and sustainable development.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:15:p:4012-:d:251344
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/15/4012/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/15/4012/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Henning S Hansen, 2012. "Empirically Derived Neighbourhood Rules for Urban Land-Use Modelling," Environment and Planning B, , vol. 39(2), pages 213-228, April.
    2. Michel Hagoort & Stan Geertman & Henk Ottens, 2008. "Spatial externalities, neighbourhood rules and CA land-use modelling," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(1), pages 39-56, March.
    3. Jeffrey A Onsted & Keith C Clarke, 2011. "Forecasting Enrollment in Differential Assessment Programs Using Cellular Automata," Environment and Planning B, , vol. 38(5), pages 829-849, October.
    4. Nuno Norte Pinto & António Pais Antunes, 2010. "A Cellular Automata Model Based on Irregular Cells: Application to Small Urban Areas," Environment and Planning B, , vol. 37(6), pages 1095-1114, December.
    5. Guan, DongJie & Li, HaiFeng & Inohae, Takuro & Su, Weici & Nagaie, Tadashi & Hokao, Kazunori, 2011. "Modeling urban land use change by the integration of cellular automaton and Markov model," Ecological Modelling, Elsevier, vol. 222(20), pages 3761-3772.
    6. Roger Vickerman, 1997. "High-speed rail in Europe: experience and issues for future development," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 31(1), pages 21-38.
    7. F Wu & C J Webster, 1998. "Simulation of Land Development through the Integration of Cellular Automata and Multicriteria Evaluation," Environment and Planning B, , vol. 25(1), pages 103-126, February.
    8. Cohen, Barney, 2004. "Urban Growth in Developing Countries: A Review of Current Trends and a Caution Regarding Existing Forecasts," World Development, Elsevier, vol. 32(1), pages 23-51, January.
    9. Niandry Moreno & André Ménard & Danielle J Marceau, 2008. "VecGCA: A Vector-Based Geographic Cellular Automata Model Allowing Geometric Transformations of Objects," Environment and Planning B, , vol. 35(4), pages 647-665, August.
    10. Willigers, Jasper & van Wee, Bert, 2011. "High-speed rail and office location choices. A stated choice experiment for the Netherlands," Journal of Transport Geography, Elsevier, vol. 19(4), pages 745-754.
    11. H Couclelis, 1997. "From Cellular Automata to Urban Models: New Principles for Model Development and Implementation," Environment and Planning B, , vol. 24(2), pages 165-174, April.
    12. H Couclelis, 1985. "Cellular Worlds: A Framework for Modeling Micro—Macro Dynamics," Environment and Planning A, , vol. 17(5), pages 585-596, May.
    13. 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.
    14. Paul M Torrens & David O'Sullivan, 2001. "Cellular Automata and Urban Simulation: Where Do We Go from Here?," Environment and Planning B, , vol. 28(2), pages 163-168, April.
    15. Bowes, David R. & Ihlanfeldt, Keith R., 2001. "Identifying the Impacts of Rail Transit Stations on Residential Property Values," Journal of Urban Economics, Elsevier, vol. 50(1), pages 1-25, July.
    16. Douglas P. Ward & Alan T. Murray & Stuart R. Phinn, 2003. "Integrating spatial optimization and cellular automata for evaluating urban change," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 37(1), pages 131-148, February.
    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. Bo Li & Yue Wang & Tong Wang & Xiaoman He & Jan K. Kazak, 2022. "Scenario Analysis for Resilient Urban Green Infrastructure," Land, MDPI, vol. 11(9), pages 1-19, September.
    2. Jinbu Zhao & Yongyou Nie & Kui Liu & Jizhi Zhou, 2020. "Evolution of the Individual Attitude in the Risk Decision of Waste Incinerator Construction: Cellular Automaton Model," Sustainability, MDPI, vol. 12(1), pages 1-16, January.
    3. Yuji Murayama & Matamyo Simwanda & Manjula Ranagalage, 2021. "Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries," Sustainability, MDPI, vol. 13(7), pages 1-5, March.

    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. 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.
    2. Liu, Xiaoping & Li, Xia & Shi, Xun & Wu, Shaokun & Liu, Tao, 2008. "Simulating complex urban development using kernel-based non-linear cellular automata," Ecological Modelling, Elsevier, vol. 211(1), pages 169-181.
    3. Basse, Reine Maria, 2013. "A constrained cellular automata model to simulate the potential effects of high-speed train stations on land-use dynamics in trans-border regions," Journal of Transport Geography, Elsevier, vol. 32(C), pages 23-37.
    4. 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).
    5. Piotr Rosik & Julia Wójcik, 2022. "Transport Infrastructure and Regional Development: A Survey of Literature on Wider Economic and Spatial Impacts," Sustainability, MDPI, vol. 15(1), pages 1-19, December.
    6. Han, Yu & Jia, Haifeng, 2017. "Simulating the spatial dynamics of urban growth with an integrated modeling approach: A case study of Foshan, China," Ecological Modelling, Elsevier, vol. 353(C), pages 107-116.
    7. Li, Hongchang & Strauss, Jack & Shunxiang, Hu & Lui, Lu, 2018. "Do high-speed railways lead to urban economic growth in China? A panel data study of China’s cities," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 70-89.
    8. Chih Cheng CHEN, 2014. "The Operation Of New Transportation Infrastructure And Regional Economic Efficiency: A Case Study Of High Speed Rail In Western Taiwan," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 14(1), pages 179-194.
    9. LIANG, Jingmin & CHEN, Jiayu & TONG, De & LI, Xin, 2022. "Planning control over rural land transformation in Hong Kong: A remote sensing analysis of spatio-temporal land use change patterns," Land Use Policy, Elsevier, vol. 119(C).
    10. Markos Mathewos & Semaria Moga Lencha & Misgena Tsegaye, 2022. "Land Use and Land Cover Change Assessment and Future Predictions in the Matenchose Watershed, Rift Valley Basin, Using CA-Markov Simulation," Land, MDPI, vol. 11(10), pages 1-28, September.
    11. 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.
    12. Cascetta, Ennio & Cartenì, Armando & Henke, Ilaria & Pagliara, Francesca, 2020. "Economic growth, transport accessibility and regional equity impacts of high-speed railways in Italy: ten years ex post evaluation and future perspectives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 412-428.
    13. Chao Xu & Didit O Pribadi & Dagmar Haase & Stephan Pauleit, 2020. "Incorporating spatial autocorrelation and settlement type segregation to improve the performance of an urban growth model," Environment and Planning B, , vol. 47(7), pages 1184-1200, September.
    14. Shuqing Wang & Xinqi Zheng, 2023. "Dominant transition probability: combining CA-Markov model to simulate land use change," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6829-6847, July.
    15. Mathey, Anne-Hélène & Krcmar, Emina & Dragicevic, Suzana & Vertinsky, Ilan, 2008. "An object-oriented cellular automata model for forest planning problems," Ecological Modelling, Elsevier, vol. 212(3), pages 359-371.
    16. Pilehforooshha, Parastoo & Karimi, Mohammad & Taleai, Mohammad, 2014. "A GIS-based agricultural land-use allocation model coupling increase and decrease in land demand," Agricultural Systems, Elsevier, vol. 130(C), pages 116-125.
    17. Enshou Zhang & Lei Chen & Pei Kuang & David G. Dickinson, 2023. "An Accessibility Measurement Based on Commuter Behaviour and Living Conditions: An Empirical Analysis of the High-Speed Railway Network in the East of China," Sustainability, MDPI, vol. 15(5), pages 1-29, February.
    18. Jack Strauss, 2017. "Do High Speed Railways Lead to Urban Economic Growth in China?," Proceedings of Economics and Finance Conferences 4807677, International Institute of Social and Economic Sciences.
    19. Xuan Yang & Qiusheng Zhang & Xiaotian Shen & Jie Qin & Qian Sun & Yuanze Xu, 2022. "Could the Opening of HSR Reduce the M&A Premium?," Sustainability, MDPI, vol. 14(10), pages 1-28, May.
    20. Chen Wang & Jack Strauss & Lei Zheng, 2021. "High-Speed Railway Opening and Corporate Fraud," Sustainability, MDPI, vol. 13(23), pages 1-23, December.

    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:11:y:2019:i:15:p:4012-:d:251344. 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.