基于腾讯迁徙数据的中国“春运”城市间人口流动空间格局
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摘要
"腾讯迁徙"大数据基于位置服务,实时、动态、完整、系统地描述了用户日常出行活动的轨迹。通过采集"腾讯迁徙"数据平台中2018年春运期间中国346个地级及以上城市之间的逐日人口流动数据,分"节前、节中、节后"3个时间段,利用复杂网络分析方法,从人口流动的集散层级、集散体系分层集聚特征、人口流动空间格局、网络空间特征等角度分析各时间段城市间的人口流动特征与空间格局。结果表明,腾讯迁徙大数据直观地揭示了春运期间中国城市间人口流动空间格局,3个时段人口的净流入均呈现十字形骨架支撑的菱形分布,人流集散中心主要集中在京津冀、长三角、珠三角和成渝4大城市群,与城市等级有较强的一致性。人口流动集散体系呈明显的分层集聚,城市行政级别的高低与人口流动影响力存在一定的正相关关系,大部分城市人口流动处于"相对平衡"状态。人口流动网络呈现东密西疏的分布特征和东部并联、西部串联的网络关联特征。人口流动网络局部具有较明显的"社区"结构特征,聚为3个大区级、5个跨区域级和1个地区级社区。
The big data of "Tencent Migration" is attained based on LBS(Location Based Services) technology that records the daily flow trajectory of the population between cities in a full, dynamic, instant and intuitive manner. Through collecting daily mobility data of 346 cities during the 2018 Spring Festival travel rush on the "Tencent Migration" data platform, the three time periods. i.e. "travel period, journey period and return period" are marked, and via the complex network analysis methods, from the perspectives of the distribution level of population flow, this paper analyzed the layered clustering of the distributed network system,the spatial pattern of the population flow and the spatial characteristics of the network, the daily flow characteristics and spatial pattern of the population in different time periods. The main conclusions are as follows: "Tencent migration" big data clearly discovers the temporal-spatial pattern of population mobility and structural characteristics of city network in China during the period of Spring Festival travel rush. The net inflow of population showed a diamond shaped with cross frame support in each period, the four nodes of the diamond contain Beijing, Shanghai, Guangzhou and Chengdu-Chongqing.
The big data of "Tencent Migration" is attained based on LBS(Location Based Services) technology that records the daily flow trajectory of the population between cities in a full, dynamic, instant and intuitive manner. Through collecting daily mobility data of 346 cities during the 2018 Spring Festival travel rush on the "Tencent Migration" data platform, the three time periods. i.e. "travel period, journey period and return period" are marked, and via the complex network analysis methods, from the perspectives of the distribution level of population flow, this paper analyzed the layered clustering of the distributed network system,the spatial pattern of the population flow and the spatial characteristics of the network, the daily flow characteristics and spatial pattern of the population in different time periods. The main conclusions are as follows: "Tencent migration" big data clearly discovers the temporal-spatial pattern of population mobility and structural characteristics of city network in China during the period of Spring Festival travel rush. The net inflow of population showed a diamond shaped with cross frame support in each period, the four nodes of the diamond contain Beijing, Shanghai, Guangzhou and Chengdu-Chongqing.
引文
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[18]Li J, Ye Q, Deng X, et al. Spatial-temporal analysis on Spring Festival Travel Rush in China based on multisource big data[J]. Sustainability 2016,8(11):1184.
[19]魏冶,修春亮,刘志敏,等.春运人口流动透视的转型期中国城市网络结构[J].地理科学,2016,36(11):1654-1660.[Wei Ye, Xiu Chunliang, Liu Zhimin, et al. Spatial pattern of city network in transitional China based on the population flows in"Chunyun"period[J]. Scientia Geographica Sinica, 2016,36(11):1654-1660.]
[20]赵梓渝,魏冶,王士君,等.有向加权城市网络的转变中心性与控制力测度——以中国春运人口流动网络为例[J].地理研究,2017,36(4):647-660.[Zhao Ziyu, Wei Ye, Wang Shijun, et al. Measurement of directed alternative centricity and power of directed weighted urban network:A case of population flow network of China during"Chunyun"period[J]. Geographical Research, 2017,36(4):647-660.]
[21]赵梓渝,魏冶,庞瑞秋,等.基于人口省际流动的中国城市网络转变中心性与控制力研究——兼论递归理论用于城市网络研究的条件性[J].地理学报,2017,72(6):1032-1048.[Zhao Ziyu, Wei Ye,Pang Ruiqiu, et al. Alter-based centrality and power of Chinese city network using inter-provincial population flow[J]. Acta Geographica Sinica, 2017,72(6):1032-1048.]
[22]汪小帆,李翔,陈关荣.复杂网络理论及其应用[M].北京:清华大学出版社,2006:3-42.[Wang Xiaofan, Li Xiang, Chen Guanrong.Complex Network:Theory and Application[M]. Beijing:Tsinghua University Press, 2006:3-42.]
[23]丁金宏.中国人口省际迁移的原因别流场特征探析[J].人口研究,1994,18(1):14-21.[Ding Jinhong. A study on the characteristics of inter-provincial migration fields by reasons[J]. Population Research, 1994,18(1):14-21.]
[24]臧玉珠,周生路,周兵兵,等.1995—2010年中国省际人口迁移态势与空间格局演变——基于社会网络分析的视角[J].人文地理,2016,31(4):112-118.[Zang Yuzhu, Zhou Shenglu, Zhou Bingbing,et al. The volume changes and spatial pattern dynamics of China's interprovincial migration:A perspective of social network analysis[J]. Human Geography, 2016,31(4):112-118.]
[25]Xu J, Li A Y, Li D, et al. Difference of urban development in China from the perspective of passenger transport around Spring Festival[J]. Applied Geography, 2017,87:85-96.
[26]Zhu D, Wang D, Hassan S U, et al. Small-world phenomenon of keywords network based on complex network[J]. Scientometrics,2013,97(2):435-442.
[27]Newman M E J. Modularity and community structure in networks[J]. Proceedings of the National Academy of Sciences, 2006,103(23):8577-8582.
[2] Castells M. Globalisation, networking, urbanisation:Reflections on the spatial dynamics of the information age[J]. Urban Studies, 2010,47(13):2737-2745.
[3] Camagni R,Capello R. The City Network Paradigm:Theory and Empirical Evidence[M]. Netherlands:Elsevier BV, 2004:508-520.
[4]蒋小荣,杨永春,汪胜兰,等.基于上市公司数据的中国城市网络空间结构[J].城市规划,2017,41(6):18-26.[Jiang Xiaorong, Yang Yongchun, Wang Shenglan, et al. Spatial structure of Chinese intercity network based on the data of listed companies[J]. City Planning Review, 2017,41(6):18-26.]
[5] Capello R, Nijkamp P. The city network paradigm:Theory and empirical evidence[J]. Contributions to Economic Analysis, 2004,266:495-529.
[6] Castells M. Grassrooting the space of flows[J]. Urban Geography,1999,20(4):294-302.
[7] Taylor P J, Hoyler M, Verbruggen R. External urban relational process:Introducing central flow theory to complement to central place theory[J]. Urban Studies, 2010,47(13):2803-2818.
[8] De Haas H. Migration and development:A theoretical perspective[J]. International Migration Review, 2010,44(1):227-264.
[9] Liu X, Neal Z, Derudder B. Featured graphic:City networks in the United States:A comparison of four models[J]. Environment and Planning A, 2012,44(2):255-256.
[10]甄峰,王波,陈映雪.基于网络社会空间的中国城市网络特征:以新浪微博为例[J].地理学报,2012,67(8):1031-1043.[Zhen Feng, Wang Bo, Chen Yingxue. China's city network characteristics based on social network space:An empirical analysis of Sina micro-blog[J].Acta Geographica Sinica, 2012,67(8):1031-1043.]
[11]郑思齐,张晓楠,宋志达,等.空气污染对城市居民户外活动的影响机制:利用点评网外出就餐数据的实证研究[J].清华大学学报:自然科学版,2016,56(1):89-96.[Zheng Siqi, Zhang Xiaonan, Song Zhida, et al. Influence of air pollution on urban residents'outdoor activity:Empirical study based on dining out data from the Dianping website[J]. Journal of Tsinghua University(Scoial&Technol), 2016,56(1):89-96.]
[12]邓楚雄,宋雄伟,谢炳庚,等.基于百度贴吧数据的长江中游城市群城市网络联系分析[J].地理研究,2018,37(6):1181-1192.[Deng Chuxiong, Song Xiongwei, Xie Binggeng, et al. City network link analysis of urban agglomeration in the middle Yangtze River basin based on the Baidu Post Bar data[J]. Geographical Research, 2018,37(6):1181-1192.]
[13]Wei Y, Song W, Xiu C L, et al. The rich-club phenomenon of China's population flow network during the country's Spring Festival[J]. Applied Geography, 2018,96:77-85.
[14]蒋小荣,汪胜兰.中国地级以上城市人口流动网络研究——基于百度迁徙大数据的分析[J].中国人口科学,2017(2):35-46.[Jiang Xiaorong, Wang Shenglan. Research on China's urban population mobility network:Based on Baidu migration big data[J]. Chinese Journal of Population Science, 2017(2):35-46.]
[15]刘望保,石恩名.基于ICT的中国城市间人口日常流动空间格局——以百度迁徙为例[J].地理学报,2016,71(10):1667-1679.[Liu Wangbao, Shi Enming. Spatial pattern of population daily flow among cities based on ICT:A case study of"Baidu Migration"[J].Acta Geographica Sinica, 2016,71(10):1667-1679.]
[16]赵梓渝,魏冶,庞瑞秋,等.中国春运人口省际流动的时空与结构特征[J].地理科学进展,2017,36(8):952-964.[Zhao Ziyu, Wei Ye,Pang Ruiqiu, et al. Spatiotemporal and structural characteristics of interprovincial population flow during the 2015 Spring Festival travel rush[J]. Progress in Geography, 2017,36(8):952-964.]
[17]赵落涛,曹卫东,魏冶,等.泛长三角人口流动网络及其特征研究[J].长江流域资源与环境,2018,27(4):705-710.[Zhao Luotao, Cao Weidong, Wei Ye, et al. A study on population flow network and its characteristics in Pan-Yangtze River Delta[J]. Resources and Environment in the Yangtze Basin, 2018,27(4):705-710.]
[18]Li J, Ye Q, Deng X, et al. Spatial-temporal analysis on Spring Festival Travel Rush in China based on multisource big data[J]. Sustainability 2016,8(11):1184.
[19]魏冶,修春亮,刘志敏,等.春运人口流动透视的转型期中国城市网络结构[J].地理科学,2016,36(11):1654-1660.[Wei Ye, Xiu Chunliang, Liu Zhimin, et al. Spatial pattern of city network in transitional China based on the population flows in"Chunyun"period[J]. Scientia Geographica Sinica, 2016,36(11):1654-1660.]
[20]赵梓渝,魏冶,王士君,等.有向加权城市网络的转变中心性与控制力测度——以中国春运人口流动网络为例[J].地理研究,2017,36(4):647-660.[Zhao Ziyu, Wei Ye, Wang Shijun, et al. Measurement of directed alternative centricity and power of directed weighted urban network:A case of population flow network of China during"Chunyun"period[J]. Geographical Research, 2017,36(4):647-660.]
[21]赵梓渝,魏冶,庞瑞秋,等.基于人口省际流动的中国城市网络转变中心性与控制力研究——兼论递归理论用于城市网络研究的条件性[J].地理学报,2017,72(6):1032-1048.[Zhao Ziyu, Wei Ye,Pang Ruiqiu, et al. Alter-based centrality and power of Chinese city network using inter-provincial population flow[J]. Acta Geographica Sinica, 2017,72(6):1032-1048.]
[22]汪小帆,李翔,陈关荣.复杂网络理论及其应用[M].北京:清华大学出版社,2006:3-42.[Wang Xiaofan, Li Xiang, Chen Guanrong.Complex Network:Theory and Application[M]. Beijing:Tsinghua University Press, 2006:3-42.]
[23]丁金宏.中国人口省际迁移的原因别流场特征探析[J].人口研究,1994,18(1):14-21.[Ding Jinhong. A study on the characteristics of inter-provincial migration fields by reasons[J]. Population Research, 1994,18(1):14-21.]
[24]臧玉珠,周生路,周兵兵,等.1995—2010年中国省际人口迁移态势与空间格局演变——基于社会网络分析的视角[J].人文地理,2016,31(4):112-118.[Zang Yuzhu, Zhou Shenglu, Zhou Bingbing,et al. The volume changes and spatial pattern dynamics of China's interprovincial migration:A perspective of social network analysis[J]. Human Geography, 2016,31(4):112-118.]
[25]Xu J, Li A Y, Li D, et al. Difference of urban development in China from the perspective of passenger transport around Spring Festival[J]. Applied Geography, 2017,87:85-96.
[26]Zhu D, Wang D, Hassan S U, et al. Small-world phenomenon of keywords network based on complex network[J]. Scientometrics,2013,97(2):435-442.
[27]Newman M E J. Modularity and community structure in networks[J]. Proceedings of the National Academy of Sciences, 2006,103(23):8577-8582.