Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China
In recent years, the emergence of dockless bike-sharing has brought new ways of transportation, while also providing support for observing urban dynamics at a finer granularity. This study uses dockless bike-sharing data, combined with point of interest (POI) data, to explore intra-urban human mobil...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-08-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223002662 |
| _version_ | 1797738009355878400 |
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| author | Xijie Xu Jie Wang Stefan Poslad Xiaoping Rui Guangyuan Zhang Yonglei Fan |
| author_facet | Xijie Xu Jie Wang Stefan Poslad Xiaoping Rui Guangyuan Zhang Yonglei Fan |
| author_sort | Xijie Xu |
| collection | DOAJ |
| description | In recent years, the emergence of dockless bike-sharing has brought new ways of transportation, while also providing support for observing urban dynamics at a finer granularity. This study uses dockless bike-sharing data, combined with point of interest (POI) data, to explore intra-urban human mobility and daily activity patterns, using Beijing as a case study. Here, we employ spatial statistics and graph network to quantify the characteristics of travel behavior. Firstly, spatiotemporal statistics analysis was conducted to investigate the travel patterns and spatiotemporal differences of bike-sharing in Beijing. It was found that bike trips have clear peak hours and highly overlap with the subway lines, indicating that the bike-sharing system effectively completes the ‘last mile’ of travel in Beijing. Secondly, graph networks were used to reveal the core patterns and community structures of human mobility in Beijing and their connections to daily activities. Our findings indicate that there are different core structures of human mobility in Beijing, some dominated by a single core node, while others are formed by the aggregation of multiple cores. Finally, POI data was used to analyze human daily activity patterns. We analyzed the temporal characteristics and the hotspot areas of each daily activity in Beijing and found that transferring to other transportation modes is the most popular activity for people riding bikes, followed by shopping, working, and eating out. These findings provide a reference for understanding urban human dynamics and urban structure from the perspective of dockless bike-sharing. |
| first_indexed | 2024-03-12T13:37:42Z |
| format | Article |
| id | doaj.art-ccee7e144c37458fbb7877f190b57cca |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-12T13:37:42Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-ccee7e144c37458fbb7877f190b57cca2023-08-24T04:34:21ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-08-01122103442Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, ChinaXijie Xu0Jie Wang1Stefan Poslad2Xiaoping Rui3Guangyuan Zhang4Yonglei Fan5School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UKSchool of Life Sciences, Technical University of Munich, Freising 85354, GermanySchool of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UKSchool of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China; Corresponding author.College of Engineering, Peking University, Beijing 100871, ChinaSchool of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UKIn recent years, the emergence of dockless bike-sharing has brought new ways of transportation, while also providing support for observing urban dynamics at a finer granularity. This study uses dockless bike-sharing data, combined with point of interest (POI) data, to explore intra-urban human mobility and daily activity patterns, using Beijing as a case study. Here, we employ spatial statistics and graph network to quantify the characteristics of travel behavior. Firstly, spatiotemporal statistics analysis was conducted to investigate the travel patterns and spatiotemporal differences of bike-sharing in Beijing. It was found that bike trips have clear peak hours and highly overlap with the subway lines, indicating that the bike-sharing system effectively completes the ‘last mile’ of travel in Beijing. Secondly, graph networks were used to reveal the core patterns and community structures of human mobility in Beijing and their connections to daily activities. Our findings indicate that there are different core structures of human mobility in Beijing, some dominated by a single core node, while others are formed by the aggregation of multiple cores. Finally, POI data was used to analyze human daily activity patterns. We analyzed the temporal characteristics and the hotspot areas of each daily activity in Beijing and found that transferring to other transportation modes is the most popular activity for people riding bikes, followed by shopping, working, and eating out. These findings provide a reference for understanding urban human dynamics and urban structure from the perspective of dockless bike-sharing.http://www.sciencedirect.com/science/article/pii/S1569843223002662Dockless bike-sharingHuman mobilityHuman daily activityGraph network |
| spellingShingle | Xijie Xu Jie Wang Stefan Poslad Xiaoping Rui Guangyuan Zhang Yonglei Fan Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China International Journal of Applied Earth Observations and Geoinformation Dockless bike-sharing Human mobility Human daily activity Graph network |
| title | Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China |
| title_full | Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China |
| title_fullStr | Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China |
| title_full_unstemmed | Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China |
| title_short | Exploring intra-urban human mobility and daily activity patterns from the lens of dockless bike-sharing: A case study of Beijing, China |
| title_sort | exploring intra urban human mobility and daily activity patterns from the lens of dockless bike sharing a case study of beijing china |
| topic | Dockless bike-sharing Human mobility Human daily activity Graph network |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223002662 |
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