IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i4p1649-d492854.html
   My bibliography  Save this article

Evaluating the Impact of Mega-Sports Events on Urbanization Focusing on Land-Use Changes Using a Scenario-Based Model

Author

Listed:
  • Jinjin Fan

    (Institute of Remote Sensing and Geosciences, Hangzhou Normal University, Hangzhou 311121, China
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou 311121, China)

  • Yue Li

    (Division of Environment and Sustainability, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China)

  • Wenquan Zhu

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Yan Chen

    (Institute of Remote Sensing and Geosciences, Hangzhou Normal University, Hangzhou 311121, China
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou 311121, China)

  • Yao Li

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands)

  • Hao Hou

    (Institute of Remote Sensing and Geosciences, Hangzhou Normal University, Hangzhou 311121, China
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou 311121, China)

  • Tangao Hu

    (Institute of Remote Sensing and Geosciences, Hangzhou Normal University, Hangzhou 311121, China
    Zhejiang Provincial Key Laboratory of Urban Wetlands and Regional Change, Hangzhou 311121, China)

Abstract

Mega-sports events have a profound impact on promoting the urbanization process, optimizing the urban spatial structure, and improving the competitiveness of the host city. Taking the 19th Asian Games Hangzhou 2022 (AGH) as an example, we used remote sensing data and a scenario-based model to simulate land-use changes and developments from 2005 to 2025. By setting two scenarios, natural development and AGH-driven development, we explored the impact of AGH on urban development and its driving factors. The results show that (1) cultivated land areas decreased by 369.96 km 2 , while construction land areas increased by 488.33 km 2 among the main land-use types in Hangzhou from 2005 to 2020. Urban areas quickly expanded with the West Lake as the center. (2) Urban sprawl intensity under the AGH-driven scenario is expected to increase by 0.91% compared to in the natural-development scenario, indicating that hosting AGH would accelerate the expansion of urban land, particularly in districts set with sports venues such as Binjiang, Xiaoshan, and Yuhang. The strategic trend of supporting the Qiantang River is obvious. (3) Under the influence of AGH, the centroid of urban construction land shifted towards the southeast, and the spatial direction was remarkable. The construction of venues and supporting facilities, and construction land for public rail transit, are the main direct driving forces of urban expansion. The AGH enhances the pace of urbanization, significantly altering the urban spatial structure and helping the city achieve a major transition from the West Lake Era to the Qiantang River Era. Furthermore, our research can provide insights into other cities that will host mega-sports events.

Suggested Citation

  • Jinjin Fan & Yue Li & Wenquan Zhu & Yan Chen & Yao Li & Hao Hou & Tangao Hu, 2021. "Evaluating the Impact of Mega-Sports Events on Urbanization Focusing on Land-Use Changes Using a Scenario-Based Model," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1649-:d:492854
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/4/1649/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/4/1649/
    Download Restriction: no
    ---><---

    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. Bhattacharjee, Sutapa & Goetz, Andrew R., 2016. "The rail transit system and land use change in the Denver metro region," Journal of Transport Geography, Elsevier, vol. 54(C), pages 440-450.
    3. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
    4. Jincheng Huang & Yueyan Liu & Xiaoying Zhang & Yu Wang & Yisong Wang, 2019. "A Scenario-Based Simulation of Land System Changes on Dietary Changes: A Case Study in China," Sustainability, MDPI, vol. 11(19), pages 1-18, September.
    5. Rasmussen, Laura Vang & Rasmussen, Kjeld & Reenberg, Anette & Proud, Simon, 2012. "A system dynamics approach to land use changes in agro-pastoral systems on the desert margins of Sahel," Agricultural Systems, Elsevier, vol. 107(C), pages 56-64.
    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. Dehui Shi & Meichen Fu, 2022. "How Does Rail Transit Affect the Spatial Differentiation of Urban Residential Prices? A Case Study of Beijing Subway," Land, MDPI, vol. 11(10), pages 1-19, October.
    3. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.
    4. Kun Cheng & Qiang Fu & Xi Chen & Tianxiao Li & Qiuxiang Jiang & Xiaosong Ma & Ke Zhao, 2015. "Adaptive Allocation Modeling for a Complex System of Regional Water and Land Resources Based on Information Entropy and its Application," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 4977-4993, November.
    5. Wang, Xiaoquan & Yin, Chaoying & Zhang, Junyi & Shao, Chunfu & Wang, Shengyou, 2021. "Nonlinear effects of residential and workplace built environment on car dependence," Journal of Transport Geography, Elsevier, vol. 96(C).
    6. Shasha Liu & Toshiyuki Yamamoto & Enjian Yao, 2023. "Joint modeling of mode choice and travel distance with intra-household interactions," Transportation, Springer, vol. 50(5), pages 1527-1552, October.
    7. Liu Yang & Yuanqing Wang & Yujun Lian & Zhongming Guo & Yuanyuan Liu & Zhouhao Wu & Tieyue Zhang, 2022. "Key Factors, Planning Strategy and Policy for Low-Carbon Transport Development in Developing Cities of China," IJERPH, MDPI, vol. 19(21), pages 1-14, October.
    8. Nilsson, Isabelle & Delmelle, Elizabeth, 2018. "Transit investments and neighborhood change: On the likelihood of change," Journal of Transport Geography, Elsevier, vol. 66(C), pages 167-179.
    9. Deyas, Gebeyew T. & Woldeamanuel, Mintesnot G., 2020. "Social and economic impacts of public transportation on adjacent communities: The case of the Addis Ababa light rail transit," Research in Transportation Economics, Elsevier, vol. 84(C).
    10. Jian, Yuqing & Liu, Zhengjia & Gong, Jianzhou, 2022. "Response of landscape dynamics to socio-economic development and biophysical setting across the farming-pastoral ecotone of northern China and its implications for regional sustainable land management," Land Use Policy, Elsevier, vol. 122(C).
    11. Emami, Maryam & Haghshenas, Hossein & Talebian, Ahmadreza & Kermanshahi, Shahab, 2022. "A game theoretic approach to study the impact of transportation policies on the competition between transit and private car in the urban context," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 320-337.
    12. Yang, Mian & Ma, Tiemeng & Sun, Chuanwang, 2018. "Evaluating the impact of urban traffic investment on SO2 emissions in China cities," Energy Policy, Elsevier, vol. 113(C), pages 20-27.
    13. Arefeh Nasri & Lei Zhang, 2019. "How Urban Form Characteristics at Both Trip Ends Influence Mode Choice: Evidence from TOD vs. Non-TOD Zones of the Washington, D.C. Metropolitan Area," Sustainability, MDPI, vol. 11(12), pages 1-16, June.
    14. 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.
    15. 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.
    16. He Yin & Van Butsic & Johanna Buchner & Tobias Kuemmerle & Alexander V. Prishchepov & Matthias Baumann & Eugenia V. Bragina & Hovik Sayadyan & Volker C. Radeloff, 2019. "Agricultural abandonment and recultivation during and after the Chechen Wars in the northern Caucasus," HiCN Working Papers 294, Households in Conflict Network.
    17. Rasmussen, Laura Vang, 2018. "Re-Defining Sahelian ‘Adaptive Agriculture’ when Implemented Locally: Beyond Techno-fix Solutions," World Development, Elsevier, vol. 108(C), pages 274-282.
    18. Elizabeth Delmelle & Isabelle Nilsson, 2020. "New rail transit stations and the out-migration of low-income residents," Urban Studies, Urban Studies Journal Limited, vol. 57(1), pages 134-151, January.
    19. Issa Ouedraogo & Jürgen Runge & Joachim Eisenberg & Jennie Barron & Séraphine Sawadogo-Kaboré, 2014. "The Re-Greening of the Sahel: Natural Cyclicity or Human-Induced Change?," Land, MDPI, vol. 3(3), pages 1-16, September.
    20. Yang, Jiawen & Su, Pinren & Cao, Jason, 2020. "On the importance of Shenzhen metro transit to land development and threshold effect," Transport Policy, Elsevier, vol. 99(C), pages 1-11.

    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:13:y:2021:i:4:p:1649-:d:492854. 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.