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Spatial-Temporal Evolution and Its Influencing Factors on Urban Land Use Efficiency in China’s Yangtze River Economic Belt

Author

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  • Liguo Zhang

    (School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China)

  • Luchen Huang

    (School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China
    Department of Mathematics and Statistics, Chonnam National University, Gwangju 61186, Republic of Korea)

  • Jinglin Xia

    (School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China)

  • Kaifeng Duan

    (School of Economics and Management, Fuzhou University, Fuzhou 350108, China)

Abstract

Improving urban land use efficiency is a feasible way to realize sustainable development and alleviate urban land pressure on the city. The main purpose of this article is to measure the urban land use efficiency of the Yangtze River Economic Belt, and explore its evolutionary trends and influencing factors, so as to provide references for policy formulation to promote efficient land use and sustainable development. Therefore, we calculated the value of urban land use efficiency in the Yangtze River economic belt from 2004 to 2019, based on the super efficiency SBM model, including unexpected output. Further, we analyzed the spatial-temporal evolution, and spatial correlation and its influencing factors. The main results are as follows: Firstly, urban land use efficiency in the Yangtze River economic belt continues to improve as a whole, but it is higher in the east and lower in the west. In the kernel density evolution map, the development trend is steep at first and then slows, and the gap tends to decrease. Secondly, the spatial correlation of urban land use efficiency in the Yangtze River economic belt increases year by year, showing a positive correlation overall. The high-high agglomeration shifts to the east, low-low agglomeration shifts to the west, and low-high and high-low agglomeration show scattered distribution. The hot and cold spots are distributed regionally and have a diffusion trend. Thirdly, the results of the spatial Dubbin model show that the urbanization level, government expenditure and industrial instruction transformation can promote the improvement of urban land use efficiency, and people density and land use scale can inhibit its improvement. Additionally, there is remarkable heterogeneity in the effect of these influencing factors. On the whole, the effect of non-resource-based cities is better, and it is more so in the cities of the eastern region.

Suggested Citation

  • Liguo Zhang & Luchen Huang & Jinglin Xia & Kaifeng Duan, 2022. "Spatial-Temporal Evolution and Its Influencing Factors on Urban Land Use Efficiency in China’s Yangtze River Economic Belt," Land, MDPI, vol. 12(1), pages 1-19, December.
  • Handle: RePEc:gam:jlands:v:12:y:2022:i:1:p:76-:d:1015723
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    References listed on IDEAS

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    1. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency: Some clarifications," European Journal of Operational Research, Elsevier, vol. 206(3), pages 702-702, November.
    2. Koroso, Nesru H. & Zevenbergen, Jaap A. & Lengoiboni, Monica, 2020. "Urban land use efficiency in Ethiopia: An assessment of urban land use sustainability in Addis Ababa," Land Use Policy, Elsevier, vol. 99(C).
    3. Song, Yang & Yeung, Godfrey & Zhu, Daolin & Xu, Yang & Zhang, Lixin, 2022. "Efficiency of urban land use in China’s resource-based cities, 2000–2018," Land Use Policy, Elsevier, vol. 115(C).
    4. Xue, Dan & Yue, Li & Ahmad, Fayyaz & Draz, Muhammad Umar & Chandio, Abbas Ali & Ahmad, Munir & Amin, Waqas, 2022. "Empirical investigation of urban land use efficiency and influencing factors of the Yellow River basin Chinese cities," Land Use Policy, Elsevier, vol. 117(C).
    5. Sidong Zhao & Kaixu Zhao & Yiran Yan & Kai Zhu & Chiming Guan, 2021. "Spatio-Temporal Evolution Characteristics and Influencing Factors of Urban Service-Industry Land in China," Land, MDPI, vol. 11(1), pages 1-32, December.
    6. Liejia Huang & Peng Yang & Boqing Zhang & Weiyan Hu, 2021. "Spatio-Temporal Coupling Characteristics and the Driving Mechanism of Population-Land-Industry Urbanization in the Yangtze River Economic Belt," Land, MDPI, vol. 10(4), pages 1-17, April.
    7. Yangyang Wang & Yanjun Liu & Guolei Zhou & Zuopeng Ma & Hongri Sun & Hui Fu, 2022. "Coordinated Relationship between Compactness and Land-Use Efficiency in Shrinking Cities: A Case Study of Northeast China," Land, MDPI, vol. 11(3), pages 1-19, March.
    8. Shengqiang Jing & Yueguan Yan & Fangqu Niu & Wenhui Song, 2022. "Urban Expansion in China: Spatiotemporal Dynamics and Determinants," Land, MDPI, vol. 11(3), pages 1-16, February.
    9. Yan, Siqi & Peng, Jianchao & Wu, Qun, 2020. "Exploring the non-linear effects of city size on urban industrial land use efficiency: A spatial econometric analysis of cities in eastern China," Land Use Policy, Elsevier, vol. 99(C).
    10. 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.
    11. Richard V. Burkhauser & Ludmila Rovba, 2006. "Income Inequality in the 1990s: Comparing the United States, Great Britain and Germany," Discussion Papers of DIW Berlin 576, DIW Berlin, German Institute for Economic Research.
    12. Färe, Rolf & Grosskopf, Shawna, 2010. "Directional distance functions and slacks-based measures of efficiency," European Journal of Operational Research, Elsevier, vol. 200(1), pages 320-322, January.
    13. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    14. Du, Juan & Liang, Liang & Zhu, Joe, 2010. "A slacks-based measure of super-efficiency in data envelopment analysis: A comment," European Journal of Operational Research, Elsevier, vol. 204(3), pages 694-697, August.
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