PROGRESS IN GEOGRAPHY ›› 2021, Vol. 40 ›› Issue (5): 759-773.doi: 10.18306/dlkxjz.2021.05.004
• Articles • Previous Articles Next Articles
ZHANG Rong(), PAN Jinghu*(
), LAI Jianbo
Received:
2020-05-23
Revised:
2020-10-14
Online:
2021-05-28
Published:
2021-07-28
Contact:
PAN Jinghu
E-mail:zr420728@163.com;panjh_nwnu@nwnu.edu.cn
Supported by:
ZHANG Rong, PAN Jinghu, LAI Jianbo. Characteristics of intercity trip network structure of residents under different traffic modes: A case study of Spring Festival travel rush[J].PROGRESS IN GEOGRAPHY, 2021, 40(5): 759-773.
Tab.2
Top 10 cities and flow routes by the level of population flow distribution under different travel modes
方式 | 集散规模前10名城市(人数/万人) | 集散人数占比 | 出行前10位路线(承载人数/万人) | 承载人口占比 |
---|---|---|---|---|
航空 | 上海(7189.50)、重庆(6774.25)、北京(5769.37)、深圳(4682.73)、成都(4456.12)、广州(3540.94)、杭州(1969.88)、南京(1875.26)、西安(1566.18)、贵阳(1541.59) | 总计39365.82万人,占航空集散总人数的49.72% | 上海至重庆(561.97)、重庆至上海(561.79)、重庆至北京(531.66)、北京至重庆(495.89)、深圳至成都(391.39)、成都至深圳(353.64)、上海至北京(335.05)、北京至上海(330.75)、深圳至上海(326.07)、广州至上海(286.53) | 总计4174.76万人,占航空承载总量的10.54% |
铁路 | 北京(13411.76)广州(8839.29)、上海(8239.52)、重庆(7946.69)、深圳(7470.20)、成都(6847.17)、武汉(4567.47)、西安(4170.78)、郑州(3553.10)、南京(3377.23) | 总计68423.22万人,占铁路集散总人数的29.71% | 上海至重庆(398.96)、重庆至上海(384.79)、佛山至广州(309.32)、广州至佛山(307.67)、重庆至北京(296.40)、长沙至北京(296.39)、北京至重庆(260.11)、武汉至北京(246.53)、北京至上海(244.27)、成都至南京(238.58) | 总计2983.01万人,占铁路承载总量的2.60% |
公路 | 广州(4524.70)、深圳(4298.90)、重庆(3947.29)、北京(3685.43)、成都(3496.08)、东莞(3490.96)、上海(3489.91)、苏州(2917.86)、佛山(2101.89)、郑州(1858.93) | 总计33811.94万人,占公路集散总人数的21.07% | 深圳至东莞(377.45)、东莞至深圳(374.35)、上海至苏州(270.93)、苏州至上海(263.99)、佛山至广州(256.25)、广州至佛山(250.17)、咸阳至西安(203.18)、北京至廊坊(202.05)、西安至咸阳(201.19)、深圳至惠州(188.14) | 总计2587.72万人,占公路承载总量的3.23% |
Tab.3
Top 10 and bottom 10 cities of alter-based centrality (AC) and alter-based power (AP) under different travel modes
位序 | 航空 | 铁路 | 公路 | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
城市 | AC | AP | 城市 | AC | AP | 城市 | AC | AP | |||
1 | 重庆 | 1.000 | 0.808 | 北京 | 1.000 | 1.000 | 深圳 | 1.000 | 0.932 | ||
2 | 上海 | 0.938 | 1.000 | 重庆 | 0.941 | 0.481 | 广州 | 0.977 | 0.951 | ||
3 | 北京 | 0.656 | 0.778 | 上海 | 0.801 | 0.559 | 东莞 | 0.960 | 0.644 | ||
4 | 深圳 | 0.630 | 0.716 | 广州 | 0.720 | 0.643 | 重庆 | 0.812 | 0.891 | ||
5 | 广州 | 0.464 | 0.545 | 深圳 | 0.645 | 0.564 | 上海 | 0.774 | 0.733 | ||
6 | 成都 | 0.443 | 0.741 | 成都 | 0.633 | 0.564 | 苏州 | 0.717 | 0.680 | ||
7 | 杭州 | 0.270 | 0.261 | 武汉 | 0.486 | 0.286 | 北京 | 0.697 | 0.856 | ||
8 | 西安 | 0.241 | 0.118 | 西安 | 0.441 | 0.273 | 成都 | 0.597 | 1.000 | ||
9 | 南京 | 0.203 | 0.163 | 郑州 | 0.329 | 0.261 | 佛山 | 0.566 | 0.390 | ||
10 | 咸阳 | 0.185 | 0.085 | 杭州 | 0.324 | 0.209 | 惠州 | 0.419 | 0.155 | ||
… | … | … | … | … | … | … | … | … | … | ||
337 | 淮北 | <0.001 | <0.001 | 大兴安岭 | 0.001 | 0.002 | 果洛 | 0.002 | 0.006 | ||
338 | 郴州 | <0.001 | <0.001 | 克州 | 0.001 | 0.004 | 山南 | 0.002 | 0.004 | ||
339 | 玉树州 | <0.001 | <0.001 | 怒江 | 0.001 | 0.001 | 玉树州 | 0.002 | 0.005 | ||
340 | 云浮 | <0.001 | <0.001 | 和田 | 0.001 | 0.002 | 阿勒泰 | 0.002 | 0.011 | ||
341 | 韶关 | <0.001 | <0.001 | 黄南州 | 0.001 | 0.001 | 琼海 | 0.002 | 0.017 | ||
342 | 贺州 | <0.001 | <0.001 | 神农架 | 0.001 | 0.001 | 克州 | 0.002 | 0.013 | ||
343 | 亳州 | <0.001 | <0.001 | 昌都 | 0.001 | <0.001 | 大兴安岭 | 0.001 | 0.002 | ||
344 | 神农架 | <0.001 | <0.001 | 阿勒泰 | <0.001 | 0.001 | 那曲 | 0.001 | 0.003 | ||
345 | 果洛 | <0.001 | <0.001 | 果洛 | <0.001 | 0.001 | 日喀则 | 0.001 | 0.005 | ||
346 | 梧州 | <0.001 | <0.001 | 阿里 | <0.001 | <0.001 | 阿里 | <0.001 | 0.002 |
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