测绘通报 ›› 2023, Vol. 0 ›› Issue (9): 107-112.doi: 10.13474/j.cnki.11-2246.2023.0273

• 学术研究 • 上一篇    下一篇

结合POI空间分布的深圳市道路网络结构特征量化

郭晗1, 马丁2,3,4, 叶艾温4, 马柯楠1, 朱维4   

  1. 1. 深圳市规划和自然资源数据管理中心, 广东 深圳 518172;
    2. 长安大学土地工程学院, 陕西 西安 710064;
    3. 西安市国土空间信息重点实验室, 陕西 西安 710064;
    4. 深圳大学建筑与城市规划学院智慧城市研究院, 广东 深圳 518060
  • 收稿日期:2022-12-06 发布日期:2023-10-08
  • 通讯作者: 马丁。E-mail:dingma@szu.edu.cn
  • 作者简介:郭晗(1989—),男,硕士,工程师,主要从事土地立体化利用、地理信息系统、遥感测绘、智慧城市等研究工作。E-mail:guohan@whu.edu.cn
  • 基金资助:
    国家自然科学基金青年科学基金(42001180);长安大学中央高校基本科研业务费专项(300102353509)

Quantifying the structural characteristics of Shenzhen road network by POI spatial distribution

GUO Han1, MA Ding2,3,4, YE Aiwen4, MA Kenan1, ZHU Wei4   

  1. 1. Shenzhen Data Management Center of Planning and Natural Resources, Shenzhen 518172, China;
    2. College of Land Engineering, Chang'an University, Xi'an 710064, China;
    3. Xi'an Key Laboratory of National Land Spatial Information, Xi'an 710064, China;
    4. Research Institute for Smart Cities, School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
  • Received:2022-12-06 Published:2023-10-08

摘要: 城市道路作为城市主要的基础设施,不仅刻画了城市空间的分布格局,也是人类政治、经济、文化及社会活动的最集中的场所之一。本文以深圳市为例,通过4种图中心性相关指标刻画城市道路的网络结构特征,同时使用深圳市POI数据与相关性模型相结合,对复杂道路网络结构及其联系进行分析。结果表明,4个路网结构中心性指标在不同角度上解释了城市路网的复杂特性,道路网络结构中心性和特征向量中心性对POI解释力度更大、相关性更高,中介中心性和临近中心性的解释稍弱。在全局城市尺度下,城市快速路多用于交通出行,社会活动较少,因此各项指标数据相对较低。而在街道尺度下,主要道路支撑了该区域的社会活动,因此各项指标及相关性相对较高。

关键词: 网络结构, POI, 空间分布, 深圳市

Abstract: Streets as the main infrastructure of a city,not only characterize the urban form,but also works as carriers of human political,economic,cultural and social activities. In the past,the exploration of urban roads mostly focused on the analysis of the relevant factors of geographical geometric space and the surrounded built environment,but seldom studied from topological network perspective. Taking Shenzhen as an example,this paper depicts the network structure characteristics of urban roads through four kinds of centrality indicators,and analyses the complex-network structure and its correlation with the distribution of Shenzhen POI data. The results show that those four structural centrality indicators help to explain the complex characteristics of urban road networks from different angles. Moreover,the degree centrality of road network structure and the eigenvector centrality have higher relevance to the interpretation of POI,but less for the betweenness centrality and closeness centrality. At the urban scale,we also find that expressways are mostly used for transportation but less social activities,so they have a lower correlation. At the street scale,the main roads in each community support the social activities,so both their centrality values and correlations are relatively higher.

Key words: network structure, POI, spatial distribution, Shenzhen

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