Fig 1.
Location map of the study area.
Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].
Fig 2.
Research framework of urban network resilience.
Fig 3.
Spatial patterns of population flow over the year.
Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].
Table 1.
Top 25 city pairs in terms of intensity of population flow in one year.
Table 2.
Top 10 city pairs in terms of intensity of population flow during the Spring Festival and daily period.
Fig 4.
Spatial patterns of population flow during the Spring Festival (a) and daily period
(b). Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].
Fig 5.
Spatial distribution of network degree centrality(a), betweenness centrality(b), closeness centrality(c), and integrated centrality(d).
Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].
Fig 6.
Degree Distribution.
Fig 7.
Spatial distribution of local clustering coefficients.
Reprinted from [(http://www.resdc.cn/DOI),2023.DOI:10.12078/2023010101] under a CC BY license, with permission from [Xu Xinliang], original copyright [January 2023].
Fig 8.
The shortest path length between network nodes.
Fig 9.
Changes of network structure resilience under disruption scenario simulation.
Table 3.
Core network, relatively complete network and edge node identification.