Frontiers in Environmental Science (May 2024)

The spatiotemporal evolution and impact of green land use efficiency in resource-based cities in the yellow river basin under the background of sustainable development

  • Yuzhuo Li,
  • Dongbo Yu,
  • Xiangdong Zhang

DOI
https://doi.org/10.3389/fenvs.2024.1406460
Journal volume & issue
Vol. 12

Abstract

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Introduction: With the rapid advancement of industrialization and urbanization in the Yellow River Basin, the number of resource-based cities is constantly increasing, leading to an imbalance in land use structure and the gradual worsening of adverse effects such as damage to the ecological environment. Hence, improving the efficiency of green land use in resource-based cities has extremely crucial ecological and practical meaning for sustainable development.Methods: This study comprehensively considers interdisciplinary theories such as ecology and management, and combines the actual situation of resource-based cities in the Yellow River Basin to construct a new type of urban field green utilization efficiency assessment index system. To promote the coordinated development of different dimensions, the corresponding spatiotemporal evolution process and related influencing factors were also analyzed. Results and discussion: The research results indicate that the overall spatial evolution of the Yellow River Basin has active correlation. During the period from 2006 to 2022, the number of high value agglomeration cities in upstream resource-based cities increased by nearly 25%; Nearly 3% of resourcecities exhibit low-value heterogeneity, while the number of resource cities with low value agglomeration has decreased to 0. In addition, population density and scientific education expenditure level are key factors affecting the ratio of green land use in resource-based cities, while the impact of economic indicators is gradually decreasing. In summary, the assessment indicator system for urban land green utilization ratio proposed in the study is more comprehensive, and the spatial distribution results of influencing factors can provide a solid data foundation for decision-makers.

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