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

Author

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  • 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
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    References listed on IDEAS

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    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.
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