Uncovering spatial and social gaps in rural mobility via mobile phone big data
Abstract Rural mobility inequality is an important aspect of inequality-focused Sustainable Development Goals. To reduce inequality and promote global sustainable development, more insight is needed into human mobility patterns in rural areas. However, studies on rural human mobility are scarce, lim...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-33123-0 |
| _version_ | 1797841038931394560 |
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| author | Zhengying Liu Pengjun Zhao Qiyang Liu Zhangyuan He Tingting Kang |
| author_facet | Zhengying Liu Pengjun Zhao Qiyang Liu Zhangyuan He Tingting Kang |
| author_sort | Zhengying Liu |
| collection | DOAJ |
| description | Abstract Rural mobility inequality is an important aspect of inequality-focused Sustainable Development Goals. To reduce inequality and promote global sustainable development, more insight is needed into human mobility patterns in rural areas. However, studies on rural human mobility are scarce, limiting our understanding of the spatial and social gaps in rural human mobility and our ability to design policies for social equality and global sustainable development. This study, therefore, explores human mobility patterns in rural China using mobile phone data. Mapping the relative frequency of short-distance trips across rural towns, we observed that geographically peripheral populations tend to have a low percentage of short-distance flows. We further revealed social gaps in mobility by fitting statistical models: as travel distances increased, human movements declined more rapidly among vulnerable groups, including children, older people, women, and low-income people. In addition, we found that people living with low street density, or in rural towns in peripheral cities with long distances to city borders, are more likely to have low intercity movement. Our results show that children, older adults, women, low-income individuals, and geographically peripheral populations in rural areas are mobility-disadvantaged, providing insights for policymakers and rural planners for achieving social equality by targeting the right groups. |
| first_indexed | 2024-04-09T16:24:27Z |
| format | Article |
| id | doaj.art-d8ffce10c4db48b0b5dc1fd65feb8b53 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T16:24:27Z |
| publishDate | 2023-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-d8ffce10c4db48b0b5dc1fd65feb8b532023-04-23T11:17:32ZengNature PortfolioScientific Reports2045-23222023-04-0113111310.1038/s41598-023-33123-0Uncovering spatial and social gaps in rural mobility via mobile phone big dataZhengying Liu0Pengjun Zhao1Qiyang Liu2Zhangyuan He3Tingting Kang4School of Urban Planning and Design, Peking University Shenzhen Graduate SchoolSchool of Urban Planning and Design, Peking University Shenzhen Graduate SchoolSchool of Urban Planning and Design, Peking University Shenzhen Graduate SchoolSchool of Urban Planning and Design, Peking University Shenzhen Graduate SchoolSchool of Urban Planning and Design, Peking University Shenzhen Graduate SchoolAbstract Rural mobility inequality is an important aspect of inequality-focused Sustainable Development Goals. To reduce inequality and promote global sustainable development, more insight is needed into human mobility patterns in rural areas. However, studies on rural human mobility are scarce, limiting our understanding of the spatial and social gaps in rural human mobility and our ability to design policies for social equality and global sustainable development. This study, therefore, explores human mobility patterns in rural China using mobile phone data. Mapping the relative frequency of short-distance trips across rural towns, we observed that geographically peripheral populations tend to have a low percentage of short-distance flows. We further revealed social gaps in mobility by fitting statistical models: as travel distances increased, human movements declined more rapidly among vulnerable groups, including children, older people, women, and low-income people. In addition, we found that people living with low street density, or in rural towns in peripheral cities with long distances to city borders, are more likely to have low intercity movement. Our results show that children, older adults, women, low-income individuals, and geographically peripheral populations in rural areas are mobility-disadvantaged, providing insights for policymakers and rural planners for achieving social equality by targeting the right groups.https://doi.org/10.1038/s41598-023-33123-0 |
| spellingShingle | Zhengying Liu Pengjun Zhao Qiyang Liu Zhangyuan He Tingting Kang Uncovering spatial and social gaps in rural mobility via mobile phone big data Scientific Reports |
| title | Uncovering spatial and social gaps in rural mobility via mobile phone big data |
| title_full | Uncovering spatial and social gaps in rural mobility via mobile phone big data |
| title_fullStr | Uncovering spatial and social gaps in rural mobility via mobile phone big data |
| title_full_unstemmed | Uncovering spatial and social gaps in rural mobility via mobile phone big data |
| title_short | Uncovering spatial and social gaps in rural mobility via mobile phone big data |
| title_sort | uncovering spatial and social gaps in rural mobility via mobile phone big data |
| url | https://doi.org/10.1038/s41598-023-33123-0 |
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