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Human mobility models reveal the underlying mechanism of seasonal movements across China

Human mobility models reveal the underlying mechanism of seasonal movements across China
Human mobility models reveal the underlying mechanism of seasonal movements across China
Understanding the spatial interactions of human mobility is crucial for urban planning, traffic engineering, as well as for the prevention and control of infectious diseases. Although many models have been developed to model human mobility, it is not clear whether such models could also capture the traveling mechanisms across different time periods (e.g. workdays, weekends or holidays). With one-year long nationwide location-based service (LBS) data in China, we investigate the spatiotemporal characteristics of population movements during different time periods, and make thorough comparisons for the applicability of five state-of-the-art human mobility models. We find that population flows show significant periodicity and strong inequality across temporal and spatial distribution. A strong ?backflow? effect is found for cross-city movements before and after holidays. Parameter fitting of gravity models reveals that travels in different type of days consider the attractiveness of destinations and cost of distance differently. Surprisingly, the comparison indicates that the parameter-free opportunity priority selection (OPS) model outperforms other models and is the best to characterize human mobility in China across all six different types of days. However, there is still an urgent need for development of more dedicated models for human mobility on weekends and different types of holidays.
Population movement, human mobility, human mobility models, seasonal migration
0129-1831
Song, Bing
c6a0f385-82f2-46e7-b734-04d22ffc3a80
Yan, Xiao-Yong
a18abb8d-4a3a-44ea-99a0-0c838c78053c
Tan, Suoyi
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Sai, Bin
bc34adc0-d234-4cbe-a3b3-8afe5422692b
Lai, Shengjie
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Yu, Hongjie
7921cb68-f4a2-4128-8406-eb0f6872bae7
Ou, Chaomin
3dc44fb0-6a83-4d6c-aad3-ee165da5c414
Lu, Xin
a681bac0-d6d1-4e8e-a642-4ce42ae2cc9d
Song, Bing
c6a0f385-82f2-46e7-b734-04d22ffc3a80
Yan, Xiao-Yong
a18abb8d-4a3a-44ea-99a0-0c838c78053c
Tan, Suoyi
0b20da84-a5b5-4983-b243-c553f6b77d7f
Sai, Bin
bc34adc0-d234-4cbe-a3b3-8afe5422692b
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Yu, Hongjie
7921cb68-f4a2-4128-8406-eb0f6872bae7
Ou, Chaomin
3dc44fb0-6a83-4d6c-aad3-ee165da5c414
Lu, Xin
a681bac0-d6d1-4e8e-a642-4ce42ae2cc9d

Song, Bing, Yan, Xiao-Yong, Tan, Suoyi, Sai, Bin, Lai, Shengjie, Yu, Hongjie, Ou, Chaomin and Lu, Xin (2021) Human mobility models reveal the underlying mechanism of seasonal movements across China. International Journal of Modern Physics C, 33 (04), [2250054]. (doi:10.1142/S0129183122500541).

Record type: Article

Abstract

Understanding the spatial interactions of human mobility is crucial for urban planning, traffic engineering, as well as for the prevention and control of infectious diseases. Although many models have been developed to model human mobility, it is not clear whether such models could also capture the traveling mechanisms across different time periods (e.g. workdays, weekends or holidays). With one-year long nationwide location-based service (LBS) data in China, we investigate the spatiotemporal characteristics of population movements during different time periods, and make thorough comparisons for the applicability of five state-of-the-art human mobility models. We find that population flows show significant periodicity and strong inequality across temporal and spatial distribution. A strong ?backflow? effect is found for cross-city movements before and after holidays. Parameter fitting of gravity models reveals that travels in different type of days consider the attractiveness of destinations and cost of distance differently. Surprisingly, the comparison indicates that the parameter-free opportunity priority selection (OPS) model outperforms other models and is the best to characterize human mobility in China across all six different types of days. However, there is still an urgent need for development of more dedicated models for human mobility on weekends and different types of holidays.

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More information

Submitted date: 12 August 2021
Accepted/In Press date: 19 September 2021
e-pub ahead of print date: 10 November 2021
Additional Information: Publisher Copyright: © 2022 World Scientific Publishing Company. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: Population movement, human mobility, human mobility models, seasonal migration

Identifiers

Local EPrints ID: 453611
URI: http://eprints.soton.ac.uk/id/eprint/453611
ISSN: 0129-1831
PURE UUID: 550dae95-80d2-428f-9e5e-72402d8e95c7
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148

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Date deposited: 20 Jan 2022 17:38
Last modified: 06 Jun 2024 04:10

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Contributors

Author: Bing Song
Author: Xiao-Yong Yan
Author: Suoyi Tan
Author: Bin Sai
Author: Shengjie Lai ORCID iD
Author: Hongjie Yu
Author: Chaomin Ou
Author: Xin Lu

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