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Visualizing road connectivity under traffic influence: a CiteSpace-based method

文献类型：期刊论文

作者Jiang, Linfeng6; Jiang, Jingyu5,6; Liu, Xiaohan4,6; Fang, Zidong4,6; Liu, Tianyu4,6; Wang, Xi4,6; Gao, Meng6; Shu, Hua3; Pei, Tao2,4,6
刊名CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE
出版日期2024-02-23
卷号N/A
关键词CiteSpace visualization connectivity traffic pattern road network
DOI10.1080/15230406.2024.2310884
产权排序2
文献子类Article ; Early Access
英文摘要The connectivity of roads under the influence of traffic is determined by the topological connections established by the road network and the transport connections formed by moving vehicles between two roads simultaneously. A thorough examination of this connectivity is crucial for comprehending traffic patterns and providing guidance to address transportation issues such as traffic congestion. However, existing methods ignore the intuitive representation and explanation of this connectivity, limiting the understanding of actual traffic patterns. This study aimed to intuitively visualize the connectivity of roads under the influence of traffic using CiteSpace, a bibliometric tool for analyzing the relationship between literature keywords. Here, the literature was replaced by trajectory, and keywords were replaced by roads. We then presented the connectivity of roads under the influence of traffic in a network, where nodes represented roads and edges represented the topological and transport connections between roads. A case study was conducted in Beijing, demonstrating the dynamic connectivity of roads under the influence of traffic in the visualized network. By comparing the visualized network with the topological road network, we identified three types of road connectivity under the influence of traffic: roads with topological connections but lacking transport connections, roads with transport connections but lacking topological connections, and roads with both topological and transport connections. This finding further revealed the traffic relationship between roads. Additionally, we simultaneously presented the multidimensional traffic characteristics in the visualized network, aiding in predicting traffic states. Road connectivity was visualized considering topological and transport connections simultaneously.Three types of road connectivity under traffic influence were revealed using CiteSpace.Association rules predicted relationships of traffic characteristics to congestion.
WOS关键词NETWORK ; CENTRALITY ; SELECTION ; WUHAN ; FLOW
WOS研究方向Geography
语种英语
WOS记录号WOS:001178069700001
出版者TAYLOR & FRANCIS INC
源URL[http://ir.igsnrr.ac.cn/handle/311030/203335]  
专题资源与环境信息系统国家重点实验室_外文论文
作者单位1.Jiangsu Ctr Collaborat Innovat, Geog Informat Resource Dev & Applicat, Nanjing, Peoples R China
2.Hubei Univ, Sch Comp Sci & Informat Engn, Wuhan, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Nanjing Univ, Sch Geog & Ocean Sci, Nanjing, Peoples R China
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
6.Lanzhou Univ, Coll Earth & Environm Sci, Lanzhou, Peoples R China
推荐引用方式
GB/T 7714		 Jiang, Linfeng,Jiang, Jingyu,Liu, Xiaohan,et al. Visualizing road connectivity under traffic influence: a CiteSpace-based method[J]. CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE,2024,N/A.
APA Jiang, Linfeng.,Jiang, Jingyu.,Liu, Xiaohan.,Fang, Zidong.,Liu, Tianyu.,...&Pei, Tao.(2024).Visualizing road connectivity under traffic influence: a CiteSpace-based method.CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE,N/A.
MLA Jiang, Linfeng,et al."Visualizing road connectivity under traffic influence: a CiteSpace-based method".CARTOGRAPHY AND GEOGRAPHIC INFORMATION SCIENCE N/A(2024).

入库方式： OAI收割

来源：地理科学与资源研究所

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