Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data
Investigating human mobility patterns can help researchers and agencies understand the driving forces of human movement, with potential benefits for urban planning and traffic management. Recent advances in location-aware technologies have provided many new data sources (e.g., mobile phone and socia...
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| Format: | Article |
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MDPI AG
2016-09-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | http://www.mdpi.com/2220-9964/5/10/177 |
| _version_ | 1819056371055722496 |
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| author | Xiping Yang Zhixiang Fang Yang Xu Shih-Lung Shaw Zhiyuan Zhao Ling Yin Tao Zhang Yunong Lin |
| author_facet | Xiping Yang Zhixiang Fang Yang Xu Shih-Lung Shaw Zhiyuan Zhao Ling Yin Tao Zhang Yunong Lin |
| author_sort | Xiping Yang |
| collection | DOAJ |
| description | Investigating human mobility patterns can help researchers and agencies understand the driving forces of human movement, with potential benefits for urban planning and traffic management. Recent advances in location-aware technologies have provided many new data sources (e.g., mobile phone and social media data) for studying human space-time behavioral regularity. Although existing studies have utilized these new datasets to characterize human mobility patterns from various aspects, such as predicting human mobility and monitoring urban dynamics, few studies have focused on human convergence and divergence patterns within a city. This study aims to explore human spatial convergence and divergence and their evolutions over time using large-scale mobile phone location data. Using a dataset from Shenzhen, China, we developed a method to identify spatiotemporal patterns of human convergence and divergence. Eight distinct patterns were extracted, and the spatial distributions of these patterns are discussed in the context of urban functional regions. Thus, this study investigates urban human convergence and divergence patterns and their relationships with the urban functional environment, which is helpful for urban policy development, urban planning and traffic management. |
| first_indexed | 2024-12-21T13:22:21Z |
| format | Article |
| id | doaj.art-59aefc926acb40f79393fcdbc1c1d031 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-21T13:22:21Z |
| publishDate | 2016-09-01 |
| publisher | MDPI AG |
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| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-59aefc926acb40f79393fcdbc1c1d0312022-12-21T19:02:32ZengMDPI AGISPRS International Journal of Geo-Information2220-99642016-09-0151017710.3390/ijgi5100177ijgi5100177Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location DataXiping Yang0Zhixiang Fang1Yang Xu2Shih-Lung Shaw3Zhiyuan Zhao4Ling Yin5Tao Zhang6Yunong Lin7State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaSenseable City Laboratory, SMART Centre, 1 Create Way, Singapore 138602, SingaporeState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Road, Shenzhen 518005, ChinaBusiness Support Center, Hubei Mobile, 2 Jinyinhu Road, Wuhan 430040, ChinaSchool of Mathematical Sciences, Peking University, 5 Yiheyuan Road Haidian District, Beijing 100871, ChinaInvestigating human mobility patterns can help researchers and agencies understand the driving forces of human movement, with potential benefits for urban planning and traffic management. Recent advances in location-aware technologies have provided many new data sources (e.g., mobile phone and social media data) for studying human space-time behavioral regularity. Although existing studies have utilized these new datasets to characterize human mobility patterns from various aspects, such as predicting human mobility and monitoring urban dynamics, few studies have focused on human convergence and divergence patterns within a city. This study aims to explore human spatial convergence and divergence and their evolutions over time using large-scale mobile phone location data. Using a dataset from Shenzhen, China, we developed a method to identify spatiotemporal patterns of human convergence and divergence. Eight distinct patterns were extracted, and the spatial distributions of these patterns are discussed in the context of urban functional regions. Thus, this study investigates urban human convergence and divergence patterns and their relationships with the urban functional environment, which is helpful for urban policy development, urban planning and traffic management.http://www.mdpi.com/2220-9964/5/10/177human convergence and divergencemobile phone dataspatiotemporal patternshuman mobility patterns |
| spellingShingle | Xiping Yang Zhixiang Fang Yang Xu Shih-Lung Shaw Zhiyuan Zhao Ling Yin Tao Zhang Yunong Lin Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data ISPRS International Journal of Geo-Information human convergence and divergence mobile phone data spatiotemporal patterns human mobility patterns |
| title | Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data |
| title_full | Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data |
| title_fullStr | Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data |
| title_full_unstemmed | Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data |
| title_short | Understanding Spatiotemporal Patterns of Human Convergence and Divergence Using Mobile Phone Location Data |
| title_sort | understanding spatiotemporal patterns of human convergence and divergence using mobile phone location data |
| topic | human convergence and divergence mobile phone data spatiotemporal patterns human mobility patterns |
| url | http://www.mdpi.com/2220-9964/5/10/177 |
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