地理科学进展 ›› 2023, Vol. 42 ›› Issue (4): 629-643.doi: 10.18306/dlkxjz.2023.04.002

• 研究论文 • 上一篇    下一篇

中国城乡融合时空演化及驱动因素

罗婉璐1(), 王武林2,1,*(), 林珍1, 周伟健1   

  1. 1.福州大学环境与安全工程学院,福州 350116
    2.湖南师范大学旅游学院,长沙 410081
  • 收稿日期:2022-09-14 修回日期:2022-12-16 出版日期:2023-04-28 发布日期:2023-04-27
  • 通讯作者: *王武林(1982— ),男,湖南邵阳人,博士后,副教授,硕士生导师,主要研究方向为区域经济、交通地理。E-mail: wangwulin421@163.com
  • 作者简介:罗婉璐(1999— ),女,福建尤溪人,硕士生,主要研究方向为区域经济、乡村地理。E-mail: luowanlu21@163.com
  • 基金资助:
    福建省社会科学基金重点项目(FJ2021A003);国家自然科学基金项目(41701118)

Spatiotemporal evolution and driving factors of urban-rural integration in China

LUO Wanlu1(), WANG Wulin2,1,*(), LIN Zhen1, ZHOU Weijian1   

  1. 1. College of Environment and Safety Engineering, Fuzhou University, Fuzhou 350116, China
    2. College of Tourism, Hunan Normal University, Changsha 410081, China
  • Received:2022-09-14 Revised:2022-12-16 Online:2023-04-28 Published:2023-04-27
  • Supported by:
    Key Program of Social Science Foundation of Fujian Province(FJ2021A003);National Natural Science Foundation of China(41701118)

摘要:

城乡融合是指导中国城乡转型的全新思路,探究城乡融合的时空特征及驱动机制是突破农村发展不充分、城乡发展不平衡等现实困境的迫切需要。论文基于“基础—动力—结果”过程性框架,构建了城乡融合评价指标体系,利用改进熵值法评价模型、kernel密度估计和地理探测器模型,测度2000—2020年中国的城乡融合水平,探究城乡融合水平时空分异及其驱动因素异质性演变。结果表明:① 中国城乡融合水平整体较低,呈先降后升的“√”型演变趋势,空间差异趋于缩小。② 以“胡焕庸线”为界,中国城乡融合水平呈现“东高西低”的空间格局;高值区中心极化特征突出,呈“带状”聚集趋势;中等水平区“集群化”特征有所减弱,且呈现由东部向中西部蔓延的趋势;低值区团簇于西部地区,其数量趋于减少。③ 全国尺度城乡融合水平的核心因素为人口流动、经济发展水平、城乡收入差距和教育支持,潜力因素为产业结构优化和对外开放水平,投资成效和政府干预“阈值”效应显著;区域尺度城乡融合水平的核心因素空间异质性明显,2020年东部地区为经济发展水平、投资成效、政府干预等,中部地区为投资成效、对外开放水平、城乡收入差距等,西部地区为教育支持、政府干预、产业结构优化等;各驱动因素交互作用对城乡融合水平的影响程度远超单因素,交通通达性与其他社会经济因素的交互作用显著增强。中国城乡融合时空演化及机理研究可为乡村振兴以及城乡高质量发展提供理论依据。

关键词: 城乡融合, 城乡关系, 乡村振兴, 地理探测器, 中国

Abstract:

Urban-rural integration (URI) is a new idea to guide the urban-rural transformation in China, and exploring the spatio-temporal characteristics and driving mechanism of URI in China is an urgent need to overcome the dilemmas of insufficient rural development and unbalanced urban and rural development. Based on the process framework of "foundation-motivation-result" of URI, an evaluation indicator system was constructed. The improved entropy evaluation model and the kernel density estimation method were used to quantitatively measure the spatiotemporal evolution characteristics of URI level of 31 provinces, autonomous regions, and municipalities in China's mainland from 2000 to 2020. This study further used the Geodetector to explore the heterogeneous evolution of driving factors for URI level in different regions of China. The main conclusions are as follows: 1) From 2000 to 2020, the URI level in China decreased first and then increased, showing a √-shaped trend, and its spatial differences narrowed. 2) The URI level in China presented a spatial pattern of high in the east and low in the west, divided by the Hu Huanyong Line. The high-value centers showed prominent polarization characteristics and presented a zonal aggregation trend. The medium-value areas were clustered but weakened,and showed a spreading trend from the eastern to the central and western parts. 3) At the national scale, the core influencing factors of URI level were population mobility, economic development level, urban-rural income gap, and educational supports, potential factors were the optimization of industrial structure and the opening-up level, and threshold effect existed in investment benefit and government intervention. At the regional scale, the core driving forces of URI level in China showed obvious spatial heterogeneity, and in 2020 they were economic development level, investment benefit, and government intervention in the eastern region, investment benefit, opening-up level, and urban-rural income gap in the central region, are educational supports, government intervention, and the optimization of industrial structure in the western region. The interaction of driving factors had far more influence on URI level in China than individual factors, and the interaction between traffic accessibility and other socioeconomic factors had been significantly enhanced. Research on the spatio-temporal evolution and mechanism of URI in China can provide theoretical basis for rural revitalization and high-quality urban and rural development.

Key words: urban-rural integration, urban-rural relationship, rural revitalization, Geodetector, China