Temporal-spatial evolution and influencing factors of land green use efficiency of resource-based cities in the Yellow River Basin, China

被引:0
|
作者
Ding, Yi [1 ]
Guo, Qingxia [1 ]
Qin, Mingxing [1 ]
机构
[1] College of Resources and Environment, Shanxi Agricultural University, Taigu,030801, China
关键词
Spatial variables measurement - Watersheds - Agglomeration - Economic analysis - Efficiency - Sustainable development - Economic and social effects - Rivers;
D O I
10.11975/j.issn.1002-6819.2021.19.029
中图分类号
学科分类号
摘要
The Yellow River Basin has been one of the most important energy bases in China. The land green use efficiency of resource-based cities directly dominates the sustainable and high-quality development in this region. In this study, taking the resource-based cities in the Yellow River Basin as the case study area, a novel index system of land green use efficiency was developed, where the resource and environmental consumption were as input indicators, while the economic, social, and environmental benefits as output indicators. SSBM (Super Slack Based Measure) model was also used to measure the land green use efficiency of resource-based cities in the study area from 2009 to 2018. A spatial autocorrelation and GTWR (Geographically and Temporally Weighted Regression) model were selected to analyze the spatial evolution characteristics and driving factors of land green use efficiency, respectively. The results showed that: 1) There was a trend of fluctuation on the land green use efficiency of resource-based cities in the study areas from 2009 to 2018. There was also a relatively low proportion of high-value cities in the land green use efficiency, where there was not a significant change over the past 10 years. Furthermore, there was a low growth rate of land green use efficiency with the insufficient rising power in the cities, due mainly to the regional restrictions and economic development. Specifically, the land green use efficiency increased the fastest in Henan and Shaanxi Provinces from 2009 to 2018. Ningxia, Shandong, and Inner Mongolia were in the slow growth stage, while Shanxi and Gansu showed a downward trend. 2) The Global Moran's I index of land green use efficiency was between -0.179 and 0.192 for the resource-based cities in the study area, indicating that the global spatial evolution was ranging from the relatively strong to weak correlation from 2009 to 2018. There were also the small-scale agglomeration and large-scale dispersion in the spatial distributions of land green use efficiency for the resource-based cities in the study area, according to the LISA index. As such, it is necessary to further strengthen the coordinated development among upper, middle, and lower reaches in the study areas. 3) There was spatial heterogeneity in the driving factors of land green use efficiency. The economic and industrial structure factors were consistently dominated the land green use efficiency in the study area. The most critical factor in the main driving factors was gradually shifted to the level of science and technology for different types of resource-based cities in 2018. Furthermore, the growing or declining resource-based cities depended strongly on the economy, industrial structure, and policy. The mature resource-based cities were mainly influenced by technology and urbanization. More importantly, technology and industrial structure posed a strong impact on renewable resource-based cities. Consequently, the finding can widely be used to guide the decision-making for better efficiency of land green use in various resource-based cities. © 2021, Editorial Department of the Transactions of the Chinese Society of Agricultural Engineering. All right reserved.
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页码:250 / 259
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