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Exploring Spatial-Temporal Coupling and Its Driving Factors of Green and Low-Carbon Urban Land Use Efficiency and High-Quality Economic Development in China

Author

Listed:
  • Lina Peng

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guizhou University of Finance and Economics, Guiyang 550025, China
    Artificial Intelligence and Digital Finance Lab, Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou University of Finance and Economics Regional Economic High-Quality Development Research Provincial Innovation Team, Guiyang 550025, China)

  • Juan Liang

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Kexin Wang

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Wenqian Xiao

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Artificial Intelligence and Digital Finance Lab, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Jian Zou

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Artificial Intelligence and Digital Finance Lab, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yuxuan Hong

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou University of Finance and Economics Regional Economic High-Quality Development Research Provincial Innovation Team, Guiyang 550025, China)

  • Rui Ding

    (College of Big Data Application and Economics (Guiyang College of Big Data Finance), Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou Collaborative Innovation Center of Green Finance and Ecological Environment Protection, Guizhou University of Finance and Economics, Guiyang 550025, China
    Artificial Intelligence and Digital Finance Lab, Guizhou University of Finance and Economics, Guiyang 550025, China
    Guizhou University of Finance and Economics Regional Economic High-Quality Development Research Provincial Innovation Team, Guiyang 550025, China)

Abstract

Green and low-carbon use of urban land (GLUUL) and high-quality economic development (HED) are two closely linked and mutually reinforcing systems, and their coordinated development is of great theoretical and practical significance to the realization of green and sustainable urban development. Based on theoretical analysis, this paper used data from 2005 to 2020 to measure GLUUL efficiency and HED level and their coupling coordination degree (CCD) successively of 282 cities in China, and then analyzed in-depth the main factors affecting CCD and its spatial–temporal heterogeneity using the GTWR model. This study found that (1) GLUUL efficiency and HED levels are increasing with different trends, and the development is unbalanced. High-value cities in the two systems show a staggered distribution pattern. (2) The CCD of the two was dominated by primary and intermediate coordination types, and the overall became increasingly coordinated, with the “intermediate coordination—advanced development” type having the highest representation. (3) There is a gradual convergence of CCD spatial differences, showing an overall spatial distribution pattern that is “high in the northwest and southeast, low in the central area”. (4) The influence degree and direction of different factors on CCD are distinguishing. The positive impact of industrial structure upgrading (Isu) is obviously greater than other factors, which has the strongest effect on the industrial corridor along the Yangtze River and the Beijing–Tianjin–Hebei region. The findings can offer insightful recommendations for promoting sustainable development in China and similar developing countries and regions.

Suggested Citation

  • Lina Peng & Juan Liang & Kexin Wang & Wenqian Xiao & Jian Zou & Yuxuan Hong & Rui Ding, 2024. "Exploring Spatial-Temporal Coupling and Its Driving Factors of Green and Low-Carbon Urban Land Use Efficiency and High-Quality Economic Development in China," Sustainability, MDPI, vol. 16(8), pages 1-31, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3455-:d:1379604
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