Volume 36 Issue 3
Jun.  2022
Turn off MathJax
Article Contents
HUANG Yanqiu, ZHENG Zhongtuan. Measurement of coordinated development level of Yangtze River Delta urban agglomeration under background of new urbanization based on SNA[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 332-340. doi: 10.12299/jsues.22-0026
Citation: HUANG Yanqiu, ZHENG Zhongtuan. Measurement of coordinated development level of Yangtze River Delta urban agglomeration under background of new urbanization based on SNA[J]. Journal of Shanghai University of Engineering Science, 2022, 36(3): 332-340. doi: 10.12299/jsues.22-0026

Measurement of coordinated development level of Yangtze River Delta urban agglomeration under background of new urbanization based on SNA

doi: 10.12299/jsues.22-0026
  • Received Date: 2022-02-15
  • Publish Date: 2022-06-30
  • New urbanization is an important part of the integrated and high-quality development of the Yangtze River Delta. Considering the factors affecting the level of new urbanization, an improved gravity model of population-economy-ecology-geography and social network analysis (SNA) method was used to explore the spatial coordinated development level of the Yangtze River Delta urban agglomeration from aspects of network density, centrality, core and periphery, cohesive subgroups and factors of high-speed rail. The results show that: 1) The spatial correlation network of new urbanization in the Yangtze River Delta urban agglomeration is relatively low, and Shanghai and Suzhou have the highest degree of nodal centrality. The difference of the ingress and egress of 8 cities including Shanghai and Hangzhou is positive, andits urbanization development has obvious spatial spillover effects on other cities in the Yangtze River Delta. 2) With Shanghai as the core city, Nanjing and Suzhou as important intermediary cities, the overall structure is from the inside to the outside and the degree of development connection decreases from the core to the peripheral city circle. 8 cities including Shanghai, Suzhou, Hangzhou as the core subgroup, it forms a city combination of "National Economic Center + Important Node Cities + Strongly Associated Provincial Capitals". 3) The high-speed rail factor has a significant impact on the spatial relevance of the new urbanization in the Yangtze River Delta urban agglomeration and the accessibility of the high-speed rail can promote the coordinated development of urbanization regions. Based on the analysis, it is proposed that core cities should play a radiating driving role to promote the development of peripheral cities, break through regional administrative divisions, improve the layout of the metropolitan area, coordinate and improve the level of new urbanization from the aspects of population, economy, ecology and other aspects. To optimize and increase the density of the high-speed rail network in the Yangtze River Delta and promote the integrated development of new urbanization in the Yangtze River Delta through resource circulation.
  • loading
  • [1]
    中国共产党中央委员会, 国务院. 中共中央、国务院印发《长江三角洲区域一体化发展规划纲要》[N]. 新华日报, 2019-12-02(1).
    [2]
    马奔, 薛阳. 京津冀城市群城镇质量评价研究[J] . 宏观经济研究,2019(4):73 − 83,170.
    [3]
    程如轩, 李澄清. 我国城市化水平及其预期分析[J] . 经济问题探索,2005(1):15 − 18. doi: 10.3969/j.issn.1006-2912.2005.01.004
    [4]
    张樨樨. 我国城市化水平综合评价指标体系研究[J] . 中国海洋大学学报,2010(1):60 − 64.
    [5]
    陈明星, 陆大道, 张华. 中国城市化水平的综合测度及其动力因子分析[J] . 地理学报,2009, 64(4):387 − 398. doi: 10.3321/j.issn:0375-5444.2009.04.001
    [6]
    邓韬, 张明斗. 新型城镇化的可持续发展及调控策略研究[J] . 宏观经济研究,2016(2):32 − 47.
    [7]
    赵天如. 都市圈新型城镇化质量测度、识别及提升策略研究: 以苏锡常都市圈与武汉都市圈为例[D]. 武汉: 华中科技大学, 2019.
    [8]
    郭政, 姚士谋, 陈爽, 等. 长三角城市群城市宜居水平时空演化及影响因素[J] . 经济地理,2020,40(2):79 − 88.
    [9]
    叶继红, 项金玉. 长三角城市群新型城镇化质量综合评价研究[J] . 山东行政学院学报,2021(4):73 − 84. doi: 10.3969/J.CNKJ.ISSN.2095-7238.2021.04.009
    [10]
    冷炳荣, 杨永春, 李英杰. 中国城市经济网络结构空间特征及其复杂性分析[J] . 地理学报,2011(2):199 − 211. doi: 10.11821/xb201102006
    [11]
    李敬, 陈澍, 万广华, 等. 中国区域经济增长的空间关联及其解释: 基于网络分析方法[J] . 经济研究,2014,49(11):4 − 16.
    [12]
    王方方, 杨焕焕. 粤港澳大湾区城市群空间经济网络结构及其影响因素研究: 基于网络分析法[J]. 华南师范大学学报(社会科学版), 2018(4): 110−120, 191.
    [13]
    安俞静, 刘静玉, 乔墩墩. 城市群城市空间联系网络格局分析: 基于综合交通信息流[J] . 地理科学,2019,39(12):1929 − 1937.
    [14]
    李永奎, 常诚, 郭英, 等. 高铁网络与城市关联的时空演化与相关性分析[J] . 华东经济管理,2019,33(3):5 − 11, 2.
    [15]
    于建峰. 不同交通方式对兰西城市群空间分布影响研究[J] . 铁道运输与经济,2019,41(10):7 − 13,40.
    [16]
    滕堂伟, 欧阳鑫. 长三角高质量一体化发展路径探究: 基于城市经济效率视角[J] . 工业技术经济,2019,38(7):152 − 160. doi: 10.3969/j.issn.1004-910X.2019.07.019
    [17]
    姚鹏, 王民, 鞠晓颖. 长江三角洲区域一体化评价及高质量发展路径[J] . 宏观经济研究,2020(4):117 − 125.
    [18]
    李博雅. 长三角城市群空间结构演化与溢出效应研究[J] . 宏观经济研究,2020(5):68 − 81.
    [19]
    田宝龙, 刘尚俊. 新疆新型城镇化发展协调度时空变化及动力因素分析[J] . 中国农业资源与区划,2018(5):193 − 199.
    [20]
    李雪涛, 吴清扬. 新型城镇化测度及其协调发展的空间差异分析[J] . 统计与决策,2020(8):67 − 71.
    [21]
    牟玲玲, 尹赛. 基于社会网络分析的京津冀新型城镇化发展水平研究: 以新沂市为例[J] . 现代城市研究,2019(6):95 − 101.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)  / Tables(7)

    Article Metrics

    Article views (161) PDF downloads(35) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return