Journal of Geo-information Science >
Delineating China's Urban Traffic Layout by Integrating Complex Graph Theory and Road Network Data
Received date: 2020-07-01
Request revised date: 2020-10-26
Online published: 2021-07-25
Supported by
National Key Research and Development Program of China(2019YFB2102903)
National Natural Science Foundation of China(41801306)
National Natural Science Foundation of China(41671408)
National Natural Science Foundation of China(41901332)
Open Fund of State Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University(18S01)
Natural Science Fund of Hubei Province(2017CFA041)
Copyright
The rapid development of urbanization has promoted China's urban road network's continuous expansion and growth. The urban road network is a dynamic, open, and self-organized spatial complex network, which constitutes a city's structural framework. The study on urban road networks' structural characteristics can provide a significant application value for road network planning and urban construction. In the related studies of the structural characteristics of urban road networks, few scholars have paid attention to the whole urban road network structure from the perspective of road alignment in China. Besides, recent studies lack an overall evaluation on the road network of major cities in China. In this paper, 49 cities, including the first- and second-tier and first-tier new cities in China, are selected as study areas and the urban road network data in February 2020 are taken as experimental data. Firstly, we use the graph theory and rose diagrams to visualize the road network's directional characteristics in 49 cities. The complex structure of the urban road network is qualitatively analyzed. Then, we select five road network indicators including the maximum ratio R, the road primacy degree S, the ratio over threshold T, the orientation-order φ, and the road network density δ. Based on the five indicators, cluster analysis is carried out for the road networks of 49 cities in this paper. And the characteristics of the spatial distribution of urban road network in China are explored. The results show that the north-south and east-west roads are the main alignment of urban roads in China. Because of the influence of terrain, some cities plan routes along the direction, which is favorable to traffic and resident's living. Based on the clustering of road network indicators, four types of the urban road network are obtained, including cross orthogonal type, cross to windmill type, windmill to arc type, and mixed complex type. There are significant differences among four types of the urban road network in directional characteristics highlighted in complexity and order. In view of the spatial distribution of road network types, road networks of cross orthogonal type and cross to windmill type are mainly distributed in China's inland areas. In contrast, road networks of the windmill to arc type and mixed complex type are mainly distributed in coastal areas. This paper explores the current traffic layout in major cities in China by analyzing the characteristics of road network's distribution in the first- and second-tier and first-tier new cities in China. This study can provide a reference for road planning and optimization of road network layout in new urban districts.
KOU Shihao , YAO Yao , ZHENG Hong , ZHOU Jianfeng , ZHANG Jiaqi , REN Shuliang , WANG Ruifan , GUAN Qingfeng . Delineating China's Urban Traffic Layout by Integrating Complex Graph Theory and Road Network Data[J]. Journal of Geo-information Science, 2021 , 23(5) : 812 -824 . DOI: 10.12082/dqxxkx.2021.200340
表1 基于路网指标的一、二线及新一线城市的K-means聚类中心结果Tab. 1 Cluster center results of the K-means in in the first and second-tier and first-tier new cities based on road network indicators |
类别 | 最值比R | 首位度S | 过阈值比T | 走向顺序φ | 路网密度δ |
---|---|---|---|---|---|
1 | 0.627 | 0.692 | 0.022 | 0.795 | 0.233 |
2 | 0.218 | 0.175 | 0.217 | 0.303 | 0.213 |
3 | 0.074 | 0.117 | 0.643 | 0.139 | 0.698 |
4 | 0.062 | 0.072 | 0.813 | 0.090 | 0.162 |
表2 本研究选取的一、二线及新一线城市的路网指标聚类结果Tab. 2 Clustering results of road network indicators in the first and second-tier and first-tier new cities selected in this study |
类别 | 城市 |
---|---|
Ⅰ | 郑州、北京、石家庄、西安、合肥、太原、长春 |
Ⅱ | 苏州、常州、天津、南通、青岛、成都、保定、廊坊、杭州济南、绍兴、长沙、烟台、兰州、徐州、哈尔滨、南宁 |
Ⅲ | 深圳、东莞、佛山、珠海、上海、中山、厦门、广州、无锡 |
Ⅳ | 南京、宁波、武汉、嘉兴、南昌、福州、台州、金华、大连沈阳、温州、贵阳、泉州、惠州、昆明、重庆 |
图6 典型城市的部分道路网、玫瑰图及指标均值和标准差Fig. 6 Part of road network, rose diagrams, index mean and standard deviation of typical cities |
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