浙江省山区县城乡融合测度时空特征及影响因素研究

Research on the Spatial-temporal Characteristics and Influencing Factors of Urban-rural Integration in Mountainous Counties of Zhejiang Province

  • 摘要: 文章以浙江省山区县为研究案例地,多维度构建了山区县城乡融合评价指标体系,运用熵权法确定浙江山区县城乡融合评价指标体系权重,使用标准差和变异系数对浙江省山区县2010—2020年城乡融合发展水平的时序演变特征进行评价,并在子系统层面作出时空特征分析,最后,采用时空地理加权回归模型(GWTR)分析主要影响因素的相关性。结果表明:1)浙江山区县城乡融合度呈现逐年上升的演变态势,区域内部各县域城乡融合度时空特征显著。2)城乡融合发展水平在空间融合层面改善最为明显,产业融合层面总体上呈现出整体增长的态势,在城乡要素融合和城乡治理融合方面整体发展水平偏低。3)城乡信息交流、城市空间扩张、劳动力流动、经济发展水平、城乡就业结构、山地覆盖率等因素对浙江山区县城乡融合发展水平的影响程度较大。

     

    Abstract: Taking mountainous counties in Zhejiang Province as research case, a multi-dimensional evaluation index system for urban-rural integration in mountainous counties was constructed. The entropy weight method was used to determine the weight of the evaluation index system for urban-rural integration in mountainous counties in Zhejiang Province. The standard deviation and coefficient of variation were used to evaluate the temporal evolution characteristics of the urban-rural integration development level in mountainous counties in Zhejiang Province from 2010 to 2020, and spatial-temporal characteristics were analyzed at the subsystem level. Finally, the spatial-temporal geographic weighted regression model (GWTR) was used to analyze the correlation of the main influencing factors. The results indicate that: 1) The urban-rural integration degree in mountainous counties in Zhejiang Province is showing an increasing trend year by year, and the spatial-temporal characteristics of urbanrural integration degree in each county within the region are significant. 2) The level of urban-rural integration development is most significantly improved at the level of spatial integration, while the overall level of industrial integration shows a stable growth trend. The overall development level is relatively low in terms of urban-rural factor integration and urban-rural governance integration. 3) The level of urban-rural integration development in mountainous counties in Zhejiang Province is greatly influenced by urban-rural information exchange, urban spatial expansion, labor factors, economic development level, urban-rural employment structure, and mountain coverage.

     

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