4.6 Article

Applying SBM-GPA Model to Explore Urban Land Use Efficiency Considering Ecological Development in China

期刊

LAND
卷 10, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/land10090912

关键词

urban land use efficiency; geospatial analysis methods (GPA); slacks-based measure model (SBM); China

资金

  1. China Postdoctoral Science Foundation [2019M651885]
  2. Open Project of Key Laboratory of Ethnic Information E-commerce in Universities of Gansu Province (CN) [2020-2]
  3. Fundamental Research Funds for the Central Universities
  4. Zhongnan University of Economics and Law (CN) [202111023, 202111073, 202111076]

向作者/读者索取更多资源

This study conducted a quantitative analysis of urban land use efficiency (ULUE) at the provincial scale in China from 2008 to 2017 using the SBM-GPA integration model. The analysis found possibilities for improvement in ULUE, strong correlation between ULUE and agglomeration characteristics, and identified three clusters of ULUE values (high, medium, low). The results can better support decision making in urban land use management.
Rapid urban sprawl is a key characteristic of the current urban land use changes in China. It leads, however, to inefficient land use and spatial imbalance. This paper conducts a quantitative analysis of the urban land use efficiency (ULUE) at a provincial scale in China, based on the SBM-GPA integration model, and using the datasets of 31 province-level regions (provinces, municipalities and autonomous regions) in Chinese mainland from 2008 to 2017. The analysis demonstrates that: (1) the proportion of provinces reaching the production frontiers is low, but there are possibilities to improve for the ULUE; (2) the provincial ULUE strongly correlates to the type of agglomeration characteristics, and the degree of agglomeration tends to increase year by year; (3) there are three types of clusters of provincial ULUE values: high, medium, and low; (4) the gravity center of the provincial ULUE is located in Henan Province, where values are relatively stable and limited changes occur. The novelty of this research is that it applies spatial modeling to characterize and analyze ULUE spatial and temporal variations and clusters in China. Practically, this can better support decision making in urban land use management.

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