长江流域资源与环境 >> 2022, Vol. 31 >> Issue (7): 1467-1481.doi: 10.11870/cjlyzyyhj202207005

• 区域可持续发展 • 上一篇    下一篇

长江中游城市群县域生态效率时空动态性及驱动机制

马  勇1,2,张  瑞1*,任  洁3   

  1. (1.湖北大学商学院,湖北 武汉 430062;2.中国旅游研究院生态旅游研究基地,湖北 武汉 430062;3.中南财经政法大学工商管理学院,湖北武汉 430073)
  • 出版日期:2022-07-20 发布日期:2022-08-22

Spatial and Temporal Dynamics and Its Driving Mechanism of County-scale Eco-efficiency in Urban Agglomeration in Middle Reaches of Yangtze River

MA Yong1,2,ZHANG Rui1,REN Jie3   

  1. (1. School of Business, Hubei University, Wuhan 430062, China; 2. Ecotourism Research Base of China Tourism Academy, Wuhan 430062, China; 3. School of Business Administration, Zhongnan University of Economics and Law, Wuhan 430073, China)
  • Online:2022-07-20 Published:2022-08-22

摘要: 县域生态效率是支撑区域绿色发展的重要基础单元。以长江中游城市群为研究区域,依托多源数据构建县域生态效率投入产出指标体系,运用超效率EBM模型进行测度,并借助LISA时间路径、LISA时空跃迁等方法分析其时空动态特征,进一步将时空跃迁类型与面板分位数回归模型嵌套以探究驱动机制。结果表明:长江中游城市群县域生态效率整体水平于2005~2018年显著提升,其空间分布凝聚力较强且具备较高路径锁定特征,各县域单元存在一定跃迁惰性,“武汉城市圈-环长株潭城市群”周边县域单元生态效率局部空间特征动态性更强,在空间依赖方向上,丰城市具备最大波动性,长沙市市辖区具备最大稳定性;经济-气候驱动、产业-资源制约、经济-资源驱动、产业-降水制约等4种驱动/制约模式呈现出自“武汉城市圈-环鄱阳湖城市群”至“环长株潭城市群”由制约向驱动转化的演进格局,各自蕴含不同的驱动机理。

Abstract: County-scale eco-efficiency has been recognized as one of the important base unit that supports regional green development. Taking the urban agglomeration in the middle reaches of Yangtze River as the study area, this paper constructed the input-output index system of eco-efficiency based on multi-source data, used the Super-EBM model to measure the county eco-efficiency from 2005 to 2018, and analyzed the dynamic characteristics of its spatial pattern with the help of LISA time path and LISA temporal and spatial transition methods. The spatiotemporal transition types were nested with the panel quantile regression model to explore the driving mechanism. The results showed that the overall level of county-scale eco-efficiency of the urban agglomeration in the Middle Reaches of the Yangtze River increased significantly during 2005 to 2018. The agglomeration development effect of the three provincial capitals as the center was significant. Urban agglomeration in the middle reach of county-scale eco-efficiency of spatial distribution of cohesion was stronger and had a higher path lock feature, there was a transition in each county unit inertia, the local spatial characteristics of eco-efficiency are more dynamic in connecting county units of “Wuhan Metropolitan Circle-Changzhou-Zhuzhou-Xiangtan Urban agglomeration”, Fengcheng in space depended on the direction of maximum volatility, Changsha municipal districts had maximum stability. Four driving-restraining models, including economy-climate drive, industry-resource control, economy-resource control, and industry-precipitation control, presented an evolution pattern from “Wuhan City Circle-Poyang Lake Urban Agglomeration” to “Changzhou-Zhuzhou-Xiangtan Urban Agglomeration” from restriction to drive, each containing different driving mechanisms.

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