IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v9y2020i6p184-d366645.html
   My bibliography  Save this article

Modeling the Collaborative Evolution of Urban Land Considering Urban Interactions under Intermediate Intervention, in the Urban Agglomeration in the Middle Reaches of the Yangtze River in China

Author

Listed:
  • Chun Li

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China)

  • Jianhua He

    (School of Resources and Environment Science, Wuhan University, Wuhan 430079, China)

  • Xingwu Duan

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China)

Abstract

As the dominant area in regional competitions, the urban agglomeration has experienced a dramatic urban land evolution, which has had a significant impact on regional socio-economic development and ecological environment. Conventional simulation models mainly explore the dynamic change of urban land based on the situation of a single city. The urban interactions, which linked separate cities into an organic urban agglomeration area, have not been sufficiently concerned, especially the urban interaction in the context of intermediate intervention. In this paper, we employ the radiation model to measure the urban interaction under intermediate intervention, and further spatially explicitly express the spatial network and influence of such an interaction. A simulation model coupling improved urban interaction is proposed to model the collaborative evolution of urban land in urban agglomeration by considering the influence of improved urban interactions into the basic framework of the cellular automata model. Taking the urban agglomeration in the middle reaches of the Yangtze River in China as a case study, the validity and suitability of the model are evaluated. The results show that, the proposed simulation model exhibits better performance in capturing the networked evolution of urban land. Considering urban interactions under intermediate intervention is necessary for modeling the collaborative evolution of urban land in urban agglomeration areas. The distribution of the urban interaction’s influence can be a beneficial reference for guiding the optimal allocation of urban land in a networked way.

Suggested Citation

  • Chun Li & Jianhua He & Xingwu Duan, 2020. "Modeling the Collaborative Evolution of Urban Land Considering Urban Interactions under Intermediate Intervention, in the Urban Agglomeration in the Middle Reaches of the Yangtze River in China," Land, MDPI, vol. 9(6), pages 1-18, June.
    • Handle: RePEc:gam:jlands:v:9:y:2020:i:6:p:184-:d:366645
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/9/6/184/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/9/6/184/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roberta Capello & Roberto Camagni, 2000. "Beyond Optimal City Size: An Evaluation of Alternative Urban Growth Patterns," Urban Studies, Urban Studies Journal Limited, vol. 37(9), pages 1479-1496, August.
    2. Evert J Meijers & Martijn J Burger, 2010. "Spatial Structure and Productivity in US Metropolitan Areas," Environment and Planning A, , vol. 42(6), pages 1383-1402, June.
    3. van Vliet, Jasper & Bregt, Arnold K. & Hagen-Zanker, Alex, 2011. "Revisiting Kappa to account for change in the accuracy assessment of land-use change models," Ecological Modelling, Elsevier, vol. 222(8), pages 1367-1375.
    4. Evert Meijers & Marloes Hoogerbrugge & Rodrigo Cardoso, 2018. "Beyond Polycentricity: Does Stronger Integration Between Cities in Polycentric Urban Regions Improve Performance?," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 109(1), pages 1-21, February.
    5. Mustafa, Ahmed & Cools, Mario & Saadi, Ismaïl & Teller, Jacques, 2017. "Coupling agent-based, cellular automata and logistic regression into a hybrid urban expansion model (HUEM)," Land Use Policy, Elsevier, vol. 69(C), pages 529-540.
    6. Paolo Veneri & David Burgalassi, 2011. "Questioning Polycentric Development and its Effects. Issues of Definition and Measurement for the Italian NUTS-2 Regions," European Planning Studies, Taylor & Francis Journals, vol. 20(6), pages 1017-1037, January.
    7. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
    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. Zhangfeng Yao & Kunhui Ye & Liang Xiao & Xiaowei Wang, 2021. "Radiation Effect of Urban Agglomeration’s Transportation Network: Evidence from Chengdu–Chongqing Urban Agglomeration, China," Land, MDPI, vol. 10(5), pages 1-21, May.
    2. Qingyao Huang & Yihua Liu, 2021. "The Coupling between Urban Expansion and Population Growth: An Analysis of Urban Agglomerations in China (2005–2020)," Sustainability, MDPI, vol. 13(13), pages 1-18, June.
    3. Hui Li & Kunqiu Chen & Lei Yan & Yulin Zhu & Liuwen Liao & Yangle Chen, 2021. "Urban Land Use Transitions and the Economic Spatial Spillovers of Central Cities in China’s Urban Agglomerations," Land, MDPI, vol. 10(6), pages 1-27, June.

    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. Stella Kostopoulou & Paraskevi-Kali Sofianou & Konstantinos Tsiokanos, 2021. "Silk Road Heritage Branding and Polycentric Tourism Development," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    2. Mingshu Wang & Ben Derudder & Xingjian Liu, 2019. "Polycentric urban development and economic productivity in China: A multiscalar analysis," Environment and Planning A, , vol. 51(8), pages 1622-1643, November.
    3. Guzman, Luis A. & Escobar, Francisco & Peña, Javier & Cardona, Rafael, 2020. "A cellular automata-based land-use model as an integrated spatial decision support system for urban planning in developing cities: The case of the Bogotá region," Land Use Policy, Elsevier, vol. 92(C).
    4. Wen Chen & Komali Yenneti & Yehua Dennis Wei & Feng Yuan & Jiawei Wu & Jinlong Gao, 2019. "Polycentricity in the Yangtze River Delta Urban Agglomeration (YRDUA): More Cohesion or More Disparities?," Sustainability, MDPI, vol. 11(11), pages 1-18, June.
    5. Wenfang Fu & Chuanjian Luo & Modan Yan, 2023. "Does Urban Agglomeration Promote the Development of Cities? Evidence from the Urban Network Externalities," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    6. Jiejing Wang, 2020. "Urban government capacity and economic performance: An analysis of Chinese cities," Environment and Planning A, , vol. 52(5), pages 981-1004, August.
    7. Raphael Karutz & Christian J. A. Klassert & Sigrun Kabisch, 2023. "On Farmland and Floodplains—Modeling Urban Growth Impacts Based on Global Population Scenarios in Pune, India," Land, MDPI, vol. 12(5), pages 1-21, May.
    8. Tingting Xu & Dingjie Zhou & Yuhua Li, 2022. "Integrating ANNs and Cellular Automata–Markov Chain to Simulate Urban Expansion with Annual Land Use Data," Land, MDPI, vol. 11(7), pages 1-15, July.
    9. Wan Li & Bindong Sun & Tinglin Zhang, 2019. "Spatial structure and labour productivity: Evidence from prefectures in China," Urban Studies, Urban Studies Journal Limited, vol. 56(8), pages 1516-1532, June.
    10. Martijn J. Burger & Evert J. Meijers & Frank G. van Oort, 2014. "Editorial: The Development and Functioning of Regional Urban Systems," Regional Studies, Taylor & Francis Journals, vol. 48(12), pages 1921-1925, December.
    11. Paolo Veneri & David Burgalassi, 2011. "Questioning Polycentric Development and its Effects. Issues of Definition and Measurement for the Italian NUTS-2 Regions," European Planning Studies, Taylor & Francis Journals, vol. 20(6), pages 1017-1037, January.
    12. Kyusang Kwon & Minho Seo, 2018. "Does the Polycentric Urban Region Contribute to Economic Performance? The Case of Korea," Sustainability, MDPI, vol. 10(11), pages 1-10, November.
    13. Evert Meijers & Martijn Burger & Evert J. Meijers & Martijn J. Burger & Marloes M. Hoogerbrugge, 2016. "Borrowing size in networks of cities: City size, network connectivity and metropolitan functions in Europe," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 181-198, March.
    14. Siqi Yan & Jian Wang, 2022. "Does Polycentric Development Improve Green Utilization Efficiency of Urban Land? An Empirical Study Based on Panel Threshold Model Approach," Land, MDPI, vol. 11(1), pages 1-17, January.
    15. Di Zhu & Yinghong Wang & Shangui Peng & Fenglin Zhang, 2022. "Influence Mechanism of Polycentric Spatial Structure on Urban Land Use Efficiency: A Moderated Mediation Model," IJERPH, MDPI, vol. 19(24), pages 1-18, December.
    16. Shuai Shi & Kathy Pain, 2020. "Investigating China’s Mid-Yangtze River economic growth region using a spatial network growth model," Urban Studies, Urban Studies Journal Limited, vol. 57(14), pages 2973-2993, November.
    17. Yanting Tang & Jinlong Gao & Wen Chen, 2022. "The Spatial-Temporal Evolution of Population in the Yangtze River Delta, China: An Urban Hierarchy Perspective," Land, MDPI, vol. 11(10), pages 1-15, October.
    18. Xiaosi Zhang & Jizhong Shao, 2024. "Evaluation of the Suitability of Street Vending Planning in Urban Public Space in the Post-COVID-19 Era," Land, MDPI, vol. 13(4), pages 1-26, April.
    19. Zhonghua Cheng & Xiaowen Hu, 2023. "The effects of urbanization and urban sprawl on CO2 emissions in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1792-1808, February.
    20. Tao, Miaomiao, 2024. "Dynamics between electric vehicle uptake and green development: Understanding the role of local government competition," Transport Policy, Elsevier, vol. 146(C), pages 227-240.

    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:jlands:v:9:y:2020:i:6:p:184-:d:366645. 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.