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周建锦, 柳娥, 陈建成. 滇中城市群新型城镇化与绿色低碳协同发展研究[J]. 中国林业经济, 2023, (4): 19-26. DOI: 10.13691/j.cnki.cn23-1539/f.2023.04.004
引用本文: 周建锦, 柳娥, 陈建成. 滇中城市群新型城镇化与绿色低碳协同发展研究[J]. 中国林业经济, 2023, (4): 19-26. DOI: 10.13691/j.cnki.cn23-1539/f.2023.04.004
ZHOU Jian-jin, LIU E, CHEN Jian-cheng. Research on the New Urbanization and Green and Low Carbon Collaborative Development of the Central Yunnan Urban Agglomeration in Yunnan Province[J]. China Forestry Economics, 2023, (4): 19-26. DOI: 10.13691/j.cnki.cn23-1539/f.2023.04.004
Citation: ZHOU Jian-jin, LIU E, CHEN Jian-cheng. Research on the New Urbanization and Green and Low Carbon Collaborative Development of the Central Yunnan Urban Agglomeration in Yunnan Province[J]. China Forestry Economics, 2023, (4): 19-26. DOI: 10.13691/j.cnki.cn23-1539/f.2023.04.004

滇中城市群新型城镇化与绿色低碳协同发展研究

Research on the New Urbanization and Green and Low Carbon Collaborative Development of the Central Yunnan Urban Agglomeration in Yunnan Province

  • 摘要: 以云南省滇中城市群为研究对象,通过构建新型城镇化与绿色低碳指标评价体系,借助熵值法与耦合协调度模型,探究2012—2021年滇中城市群新型城镇化与绿色低碳耦合协调的时空演变特征,并在此基础上,构建随机效应面板Tobit模型,进一步分析滇中城市群各州市新型城镇化与绿色低碳耦合协调发展的影响因素。结果表明:新型城镇化与绿色低碳综合发展水平的空间格局分别表现为:“中心高四周低”“西高东低”;区域的耦合协调度较高,且呈“一极多核”的分布特征。在影响因素上,城镇化水平、经济发展、科技教育与绿色生态对耦合协调度具有强正相关性,产业发展、城乡差距、碳排放对耦合协调度具有强负相关性。

     

    Abstract: Taking the central Yunnan urban agglomeration as the research object, this paper explored the spatiotemporal evolution characteristics of new urbanization and green low-carbon coupling coordination in the central Yunnan urban agglomeration from 2012 to 2021 by constructing an evaluation system for new urbanization and green low-carbon indicators, and using entropy method and coupling coordination degree model. Then, it constructed a random effects panel Tobit model to further analyze the influencing factors of the coordinated development of new urbanization and green low-carbon coupling in various states and cities of the central Yunnan urban agglomeration. The results showed that the spatial pattern of the comprehensive development level of new urbanization and green low-carbon was as follows: “high in the center and low in the surrounding areas”, “high in the west and low in the east”; The coupling coordination degree of the region was relatively high, and it exhibited a distribution characteristic of “one pole with multiple cores”. In terms of influencing factors, it could be concluded that urbanization level, economic development, science and technology education, and green ecology had a strong positive correlation with the coupling coordination degree, while industrial development, urban-rural gap, and carbon emissions had a strong negative correlation with the coupling coordination degree.

     

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