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干旱区地理 ›› 2023, Vol. 46 ›› Issue (8): 1333-1343.doi: 10.12118/j.issn.1000-6060.2022.450

• 城市地理 • 上一篇    下一篇

兰州市主城区路网形态对城市活力的影响分析

卢北1(),曾俊伟1,钱勇生1(),魏谞婷1,杨民安2,李海军1   

  1. 1.兰州交通大学交通运输学院,甘肃 兰州 730070
    2.兰州交通大学建筑与城市规划学院,甘肃 兰州 730070
  • 收稿日期:2022-09-08 修回日期:2022-12-17 出版日期:2023-08-25 发布日期:2023-09-21
  • 通讯作者: 钱勇生(1970-),男,教授,主要从事交通运输规划与管理、安全技术与工程研究等方面的研究. E-mail: qianyongsheng@mail.lzjtu.cn
  • 作者简介:卢北(1997-),女,硕士研究生,主要从事交通运输规划与管理等方面的研究. E-mail: lubei0825@163.com
  • 基金资助:
    甘肃省教育厅“双一流”科研重点项目(GSSYLXM-04);甘肃省哲学社会科学规划项目(2021YB058);甘肃省高等学校创新基金项目(2020B-113);国家社科基金一般项目(15BJY037);中央引导地方科技发展资金项目(22ZY1QA005)

Influence of road network form on urban vitality in the main urban area of Lanzhou City

LU Bei1(),ZENG Junwei1,QIAN Yongsheng1(),WEI Xuting1,YANG Min’an2,LI Haijun1   

  1. 1. School of Transportation, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
    2. School of Architecture and Urban Planning, Lanzhou Jiaotong University, Lanzhou 730070, Gansu, China
  • Received:2022-09-08 Revised:2022-12-17 Online:2023-08-25 Published:2023-09-21

摘要:

便捷发达的交通有利于提升城市活力,从而促进城市的高质量发展。为深入挖掘城市活力变化机理,以兰州市主城区为例,基于路网形态和地理大数据,使用空间设计网络分析方法和地理加权回归模型分析路网对城市活力的影响。结果表明:(1)城市活力随着路网向外逐渐降低,变化规律与路网接近度呈现高度一致性。(2)在提升兰州市主城区城市活力方面,穿行度作用较为微弱,但有利于发挥兰州市在兰西城市群中的联通作用。(3)街道和城区的衔接处和边缘接近度较高,黄河两岸城市活力值受地理限制存在较强的差异性。(4)路网形态布局合理的地区往往会吸引更多的商业和服务活动,具有更大的市场潜力和更多的经济机会。研究结果可以明确路网形态对城市活力的影响,为兰州市主城区提升城市活力提供参考,有助于促进城市活力的提升。

关键词: 路网形态, 城市活力, 路网拓扑结构, 地理加权回归模型, 空间设计网络分析, 空间异质性

Abstract:

Flexible transportation is conducive to enhancing urban vitality and thus drives the high-quality development of cities. In order to characterize urban vitality in a more practical way, the impact of its influencing factors such as road network morphology, the spatial heterogeneity of these factors, and its mechanisms of change must be explored to provide a basis for future planning and lay a theoretical foundation for further urban vitality improvement. This paper uses the raster calculator in ArcGIS to quantify the city of Baidu’s population heat map and characterize its urban vitality. Based on road network morphology and geographic big data, sDNA is used to calculate the topological structure index of the road network, and the GWR model is used to analyze the spatial heterogeneity of the impact of road network morphology and other factors on urban vitality. sDNA emphasizes the integration and coordination of the urban transportation network. It can better reflect actual traffic location and has advantages in the analysis of multi-level traffic networks. The GWR model can explore the spatial heterogeneity of the impact of urban vitality influencing factors. The results demonstrate the following. (1) Urban vitality gradually decreases as the road network spreads outward, and the change rule is highly consistent with the network quantity penalized by euclidean distace (NQPDE). (2) Two phase betweenness has little effect on improving the urban vitality of Lanzhou City, but it plays a key node and connectivity role in the Lanzhou-Xining urban agglomeration. (3) The NQPDE value of the intersection and edge of the street and the city are high, but the urban vitality values on both sides of the Yellow River are markedly different due to geographical restrictions. For areas with relatively low urban vitality, the key to enhancing vitality lies in the establishment of basic service facilities and the rational allocation of branches. The rational planning of the bridges connecting the two sides will bring new changes to the urban vitality of Lanzhou City. In summary, areas with rational network layouts tend to attract more business and service activities, have greater market potential, and more economic opportunities. The research results can help clarify the influence of road network form on urban vitality, provide a reference for improving urban vitality in the main urban area of Lanzhou City, and help promote and improve urban vitality in general.

Key words: road network form, urban vitality, road network topology, geographically weighted regression, spatial design network analysis, spatial heterogeneity