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Land Green Utilization Efficiency and Its Driving Mechanisms in the Zhengzhou Metropolitan Area

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  • Linger Yu

    (School of Resources and Environment, Shandong Agricultural University, Taian 271000, China
    These authors contributed equally to this work.)

  • Keyi Liu

    (School of Resources and Environment, Shandong Agricultural University, Taian 271000, China
    These authors contributed equally to this work.)

Abstract

Improving land green use efficiency is of great significance for promoting high-quality economic development and promoting the modernization of harmonious coexistence between humans and nature. In this study, the super-efficiency SBM model with non-expected output was used to measure the level of land green use efficiency at county scale in the Zhengzhou metropolitan area from 2005 to 2020. Based on this, the spatio-temporal evolution and spatial agglomeration characteristics were analyzed. Finally, the driving mechanisms were revealed by using the geographical detector model. The results were as follows: (1) From 2005 to 2020, the land green use efficiency of the Zhengzhou metropolitan area fluctuated from 0.5329 to 0.5164, with an average annual decline rate of 0.21%, exhibiting three stages: decline, rise, then another slight decline. At the city level, Luohe City had the highest land green use efficiency, while Zhengzhou City had the lowest. (2) The land green use efficiency of the Zhengzhou metropolitan area showed a significant spatial positive correlation, Moran’s I index increased from 0.1472 to 0.2991, and the spatial agglomeration effect was continuously enhanced. On the local scale, high-high (H-H) aggregation and low-low (L-L) aggregation were dominant, high-high (H-H) aggregation areas were mainly distributed in the southwest and southeast of the Zhengzhou metropolitan area, and low-low (L-L) aggregation areas were mainly distributed in the central and western parts of the Zhengzhou metropolitan area. (3) There is heterogeneity in the degree of influence of different driving factors on land green use efficiency in the Zhengzhou metropolitan area, which is ranked as topographic relief (X7) > forest coverage rate (X8) > social consumption (X6) > industrial structure (X3) > urbanization rate (X2) > economic development (X1) > industrial added value scale (X5) > financial expenditure (X4). q values were 0.1856, 0.1119, 0.1082, 0.0741, 0.0673, 0.0589, 0.0492 and 0.0430, respectively. The interaction of two factors can enhance the explanatory power of land green use efficiency in the Zhengzhou metropolitan area. Except for the interaction of topographic relief and forest coverage rate, the other factors all show double factor enhancement. The explanatory power of the interaction between topographic relief and urbanization rate is the strongest, at 0.3513. In the future, policy regulation should be carried out from the perspectives of the interaction of social and economic conditions such as improving forest coverage rate, improving consumption power, optimizing industrial structure and improving land green use mechanisms to promote the improvement of land green use efficiency.

Suggested Citation

  • Linger Yu & Keyi Liu, 2024. "Land Green Utilization Efficiency and Its Driving Mechanisms in the Zhengzhou Metropolitan Area," Sustainability, MDPI, vol. 16(13), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5447-:d:1423010
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    References listed on IDEAS

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    1. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    2. Kaoru Tone & Miki Tsutsui, 2010. "An epsilon-based measure of efficiency in DEA revisited -A third pole of technical efficiency," GRIPS Discussion Papers 09-21, National Graduate Institute for Policy Studies.
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    1. Shuangfei Zhao & Wei Zeng & Da Feng, 2024. "Coupling Coordination of Urban Resilience and Urban Land Use Efficiency in Hunan Province, China," Sustainability, MDPI, vol. 16(24), pages 1-33, December.

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