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A Comparative Study on the Identification Methods of Urban–Rural Integration Zones from the Perspective of Symbiosis Theory and Urban Expansion Theory

Author

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  • Jiaxiang Wang

    (School of Architecture & Fine Art, Dalian University of Technology, Dalian 116081, China)

  • Fanqi Meng

    (School of Architecture & Fine Art, Dalian University of Technology, Dalian 116081, China)

  • Li Dong

    (School of Architecture & Fine Art, Dalian University of Technology, Dalian 116081, China)

  • Shiwei Yu

    (School of Architecture & Fine Art, Dalian University of Technology, Dalian 116081, China)

  • Yu Zhang

    (School of Architecture & Fine Art, Dalian University of Technology, Dalian 116081, China)

Abstract

Urban–rural integration zones are areas with the most prominent and complex contradictions in economic and social, humanistic and geographical, and urban–rural contexts. Properly identifying such zones is essential for promoting urban–rural integrated development and rural revitalization efforts. In this study, symbiosis theory and urban expansion theory are employed to analyze and identify the spatial characteristics of urban–rural integration zones in the main urban area of Dalian City. Two distinct methods, namely the G-statistic (G-S) method and the urban–urban–rural integration zone–rural gradient model (U-URIZ-R GM) method, are used to delimit these zones. Furthermore, the results of these methods are compared and analyzed to explore their respective practical applications. The results indicate that both methods produce satisfactory identification outcomes for delimiting urban–rural integration zones in the main urban area of Dalian. Specifically, the identified urban–rural integration zones are predominantly situated in the northwest and south regions, aligning with the coastline and major transportation routes. However, hilly terrain is a crucial factor that influences the delimitation of urban–rural integration zones, and it is worth considering whether forested areas located in the urban fringe should be included based on the development needs of different cities. Notably, within the core area of Dalian’s main city, an extensive expanse of mountainous woodland exists, leading to limitations in the applicability of certain indicators within the index system, such as surface temperature and vegetation cover, for determining urban–rural integration zones. Symbiosis and urban expansion theories play a vital role in guiding the identification of urban–rural integration zones. Although both methods can be used to demarcate these zones, the G-statistics method is probably more useful in cities with significant topographical features, while the urban–urban–rural integration zone–rural gradient model is more appropriate for cities with less impact from topography on urban expansion.

Suggested Citation

  • Jiaxiang Wang & Fanqi Meng & Li Dong & Shiwei Yu & Yu Zhang, 2023. "A Comparative Study on the Identification Methods of Urban–Rural Integration Zones from the Perspective of Symbiosis Theory and Urban Expansion Theory," Land, MDPI, vol. 12(7), pages 1-23, June.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1272-:d:1176345
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    References listed on IDEAS

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    1. Francesco Pagliacci, 2017. "Measuring EU Urban-Rural Continuum Through Fuzzy Logic," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 108(2), pages 157-174, April.
    2. Millward, Hugh & Spinney, Jamie, 2011. "Time use, travel behavior, and the rural–urban continuum: results from the Halifax STAR project," Journal of Transport Geography, Elsevier, vol. 19(1), pages 51-58.
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