VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data
In urban cities, multiple intelligent transportation systems generate a large amount of traffic data. Researchers can make well use of these data to provide solutions for solving numerous existing traffic problems, such as traffic congestions and urban transportation resource allocating. Thus, it is...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8417413/ |
| _version_ | 1819171918469660672 |
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| author | Tao Tang Xiangjie Kong Menglin Li Jinzhong Wang Guojiang Shen Xinshuang Wang |
| author_facet | Tao Tang Xiangjie Kong Menglin Li Jinzhong Wang Guojiang Shen Xinshuang Wang |
| author_sort | Tao Tang |
| collection | DOAJ |
| description | In urban cities, multiple intelligent transportation systems generate a large amount of traffic data. Researchers can make well use of these data to provide solutions for solving numerous existing traffic problems, such as traffic congestions and urban transportation resource allocating. Thus, it is meaningful and feasible for traffic researchers to collect these data and analyze the concealed human mobility based on them. In this paper, we propose a visual interactive subway system (VISOS). The system incorporates subway data visualization module, spatial-temporal exploration module, and station clustering module. VISOS utilizes k-means clustering algorithm to explore the subway data interactively, analyze human mobility pattern responsively, and identify functional characteristics of subway stations precisely. In addition, in this paper, we provide a comprehensive spatial-temporal exploration based on the real Shanghai subway data to analyze the importance level of subway stations. |
| first_indexed | 2024-12-22T19:58:55Z |
| format | Article |
| id | doaj.art-49b6046ac8b842ea9b01ee8979b2c67e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-22T19:58:55Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-49b6046ac8b842ea9b01ee8979b2c67e2022-12-21T18:14:19ZengIEEEIEEE Access2169-35362018-01-016421314214110.1109/ACCESS.2018.28582608417413VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway DataTao Tang0Xiangjie Kong1https://orcid.org/0000-0003-2698-3319Menglin Li2Jinzhong Wang3Guojiang Shen4Xinshuang Wang5Chengdu College, University of Electronic Science and Technology of China, Chengdu, ChinaKey Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian, ChinaKey Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian, ChinaKey Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian, ChinaCollege of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, ChinaKey Laboratory for Ubiquitous Network and Service Software of Liaoning Province, School of Software, Dalian University of Technology, Dalian, ChinaIn urban cities, multiple intelligent transportation systems generate a large amount of traffic data. Researchers can make well use of these data to provide solutions for solving numerous existing traffic problems, such as traffic congestions and urban transportation resource allocating. Thus, it is meaningful and feasible for traffic researchers to collect these data and analyze the concealed human mobility based on them. In this paper, we propose a visual interactive subway system (VISOS). The system incorporates subway data visualization module, spatial-temporal exploration module, and station clustering module. VISOS utilizes k-means clustering algorithm to explore the subway data interactively, analyze human mobility pattern responsively, and identify functional characteristics of subway stations precisely. In addition, in this paper, we provide a comprehensive spatial-temporal exploration based on the real Shanghai subway data to analyze the importance level of subway stations.https://ieeexplore.ieee.org/document/8417413/Spatial-temporal explorationstation clusteringvisual explorationsubway visualization interactive system |
| spellingShingle | Tao Tang Xiangjie Kong Menglin Li Jinzhong Wang Guojiang Shen Xinshuang Wang VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data IEEE Access Spatial-temporal exploration station clustering visual exploration subway visualization interactive system |
| title | VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data |
| title_full | VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data |
| title_fullStr | VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data |
| title_full_unstemmed | VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data |
| title_short | VISOS: A Visual Interactive System for Spatial-Temporal Exploring Station Importance Based on Subway Data |
| title_sort | visos a visual interactive system for spatial temporal exploring station importance based on subway data |
| topic | Spatial-temporal exploration station clustering visual exploration subway visualization interactive system |
| url | https://ieeexplore.ieee.org/document/8417413/ |
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