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Spatial Pattern and Spillover Effects of the Urban Land Green Use Efficiency for the Lanzhou-Xining Urban Agglomeration of the Yellow River Basin

Author

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  • Yufan Sun

    (Ministry of Education Key Laboratory of Western China’s Environmental System, College of Earth & Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Zhuo Jia

    (Ministry of Education Key Laboratory of Western China’s Environmental System, College of Earth & Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Qi Chen

    (Ministry of Education Key Laboratory of Western China’s Environmental System, College of Earth & Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Heya Na

    (Ministry of Education Key Laboratory of Western China’s Environmental System, College of Earth & Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

Abstract

Green development is necessary for building high-quality modern economic systems. Due to limited land resources, ensuring the ecological benefits will not be damaged while developing the economy is necessary, as is improving urban land green use efficiency (ULGUE). Lanzhou-Xining Urban Agglomeration is a crucial urban agglomeration in the upper reaches of the Yellow River Basin. The improvement of ULGUE can promote the integrated management of the region’s land and achieve harmonious development with the social economy. This study adopts a super-efficiency SBM model to quantify the ULGUE of the Lanzhou-Xining urban agglomeration between 2015 and 2020, analysing its spatial and temporal patterns by combining exploratory spatial data analysis. The spatial spillover effect was discussed using the spatial Durbin model. The results showed that the average value of ULGUE in the study period was on the rise and showed positive spatial autocorrelation. The ULGUE of provincial capital cities was higher than non, along with the efficiency of city proper, compared to other counties. Many factors were found to positively influence the ULGUE of the whole study region. Among these were the optimisation of industrial structure, economic development, urbanisation level, and government intervention. Population concentration and environmental regulation had a negative spatial spillover effect.

Suggested Citation

  • Yufan Sun & Zhuo Jia & Qi Chen & Heya Na, 2022. "Spatial Pattern and Spillover Effects of the Urban Land Green Use Efficiency for the Lanzhou-Xining Urban Agglomeration of the Yellow River Basin," Land, MDPI, vol. 12(1), pages 1-15, December.
    • Handle: RePEc:gam:jlands:v:12:y:2022:i:1:p:59-:d:1014688
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    References listed on IDEAS

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    1. Xie, Hualin & Chen, Qianru & Lu, Fucai & Wu, Qing & Wang, Wei, 2018. "Spatial-temporal disparities, saving potential and influential factors of industrial land use efficiency: A case study in urban agglomeration in the middle reaches of the Yangtze River," Land Use Policy, Elsevier, vol. 75(C), pages 518-529.
    2. Liangen Zeng, 2022. "The Driving Mechanism of Urban Land Green Use Efficiency in China Based on the EBM Model with Undesirable Outputs and the Spatial Dubin Model," IJERPH, MDPI, vol. 19(17), pages 1-20, August.
    3. Liu, Shuchang & Xiao, Wu & Li, Linlin & Ye, Yanmei & Song, Xiaoli, 2020. "Urban land use efficiency and improvement potential in China: A stochastic frontier analysis," Land Use Policy, Elsevier, vol. 99(C).
    4. James P. Lesage, 2008. "An Introduction to Spatial Econometrics," Revue d'économie industrielle, De Boeck Université, vol. 0(3), pages 19-44.
    5. Capozza, Dennis R. & Helsley, Robert W., 1989. "The fundamentals of land prices and urban growth," Journal of Urban Economics, Elsevier, vol. 26(3), pages 295-306, November.
    6. Zhang, Wenxi & Wang, Bo & Wang, Jian & Wu, Qun & Wei, Yehua Dennis, 2022. "How does industrial agglomeration affect urban land use efficiency? A spatial analysis of Chinese cities," Land Use Policy, Elsevier, vol. 119(C).
    7. Sijia Li & Meichen Fu & Yi Tian & Yuqing Xiong & Cankun Wei, 2022. "Relationship between Urban Land Use Efficiency and Economic Development Level in the Beijing–Tianjin–Hebei Region," Land, MDPI, vol. 11(7), pages 1-18, June.
    8. Qiaowen Lin & Huiting Ling, 2021. "Study on Green Utilization Efficiency of Urban Land in Yangtze River Delta," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
    9. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    10. Desiere, Sam & Jolliffe, Dean, 2018. "Land productivity and plot size: Is measurement error driving the inverse relationship?," Journal of Development Economics, Elsevier, vol. 130(C), pages 84-98.
    11. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    12. Kun Ge & Shan Zou & Shangan Ke & Danling Chen, 2021. "Does Urban Agglomeration Promote Urban Land Green Use Efficiency? Take the Yangtze River Economic Zone of China as an Example," Sustainability, MDPI, vol. 13(19), pages 1-19, September.
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