基于腾讯位置大数据的长江经济带人口流动空间分析
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摘要
在区域合作不断深化的背景下,人口在城市间高速流动,区域内城市的空间联系逐渐加强.城市间的人口流动具有动态性、时效性.目前基于统计年鉴的数据进行人口流动的分析具有迟滞性,因此基于腾讯位置大数据,运用Gephi复杂网络分析方法和GIS空间分析技术,对长江经济带的12个一线城市人口流动数据进行测度分析.结果表明,长江经济带城市人口联系度强度从东部向西部逐渐减弱,长江经济带城市人口流动量存在帕累托分布的"长尾分布"特征.长三角城市圈城市人口联系度高于武汉市城市圈和成渝城市圈,约为后面两个城市圈的2倍,区域地位优势明显.通过对长江经济带城市中心度分析,发现长江上、中、下游区域内存在不同的中心,长江上游主要以成都与重庆为区域中心城市,呈现双核心的空间结构;中游地区主要以武汉为中心,呈现一点多极的空间发展布局并有典型的"小世界"空间网络特点;下游主要呈现多中心集聚的空间分布特点.
The population is now flowing at high speed between cities, and the spatial connection between cities in the region is gradually strengthened. Various forms of communication are the key to leading urban connections. This kind of population movement is dynamic and time-sensitive. The research and analysis of population flow based on the data of the statistical yearbook lacks timeliness and has the effect of hysteresis. Based on Tencent Location Big Data, Gephi complex network analysis tools and GIS spatial analysis technology are applied to measure and analyze the population flow data of 12 first-tier cities in the Yangtze River Economic Belt. The results show that the intensity of urban population connection in the Yangtze River Economic Belt gradually weakens from the east to the west, and the urban population flow in the Yangtze River Economic Belt has the characteristics of "long tail distribution" of the Pareto distribution. The population connection degree of the Yangtze River Delta city circle is much higher than that of the Wuhan City Circle and the Chengdu-Chongqing City Circle, which is about twice that of the other two city circles. The regional status advantage is obvious. Through the analysis of the centrality of the Yangtze River Economic Belt, there are different centers in the upper, middle and lower reaches. The central cities in the upper reaches are mainly Chengdu and Chongqing, presenting a dual-core spatial structure. Multi-polar space development layout centered on Wuhan with the typical "small world" spatial network characteristics exhibits in the middle reaches. The downstream mainly features the spatial distribution of multi-center gathering in the Yangtze River Delta City Circle.
The population is now flowing at high speed between cities, and the spatial connection between cities in the region is gradually strengthened. Various forms of communication are the key to leading urban connections. This kind of population movement is dynamic and time-sensitive. The research and analysis of population flow based on the data of the statistical yearbook lacks timeliness and has the effect of hysteresis. Based on Tencent Location Big Data, Gephi complex network analysis tools and GIS spatial analysis technology are applied to measure and analyze the population flow data of 12 first-tier cities in the Yangtze River Economic Belt. The results show that the intensity of urban population connection in the Yangtze River Economic Belt gradually weakens from the east to the west, and the urban population flow in the Yangtze River Economic Belt has the characteristics of "long tail distribution" of the Pareto distribution. The population connection degree of the Yangtze River Delta city circle is much higher than that of the Wuhan City Circle and the Chengdu-Chongqing City Circle, which is about twice that of the other two city circles. The regional status advantage is obvious. Through the analysis of the centrality of the Yangtze River Economic Belt, there are different centers in the upper, middle and lower reaches. The central cities in the upper reaches are mainly Chengdu and Chongqing, presenting a dual-core spatial structure. Multi-polar space development layout centered on Wuhan with the typical "small world" spatial network characteristics exhibits in the middle reaches. The downstream mainly features the spatial distribution of multi-center gathering in the Yangtze River Delta City Circle.
引文
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[2] 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):35-46,127.JIANG X R,WANG S L.Research on China's urban population mobility network:based on Baidu Migration big data[J].Chinese Journal of Population Science,2017(2):35-46,127.(Ch).
[3] 柯文前,俞肇元,陈伟,等.人类时空间行为数据观测体系架构及其关键问题[J].地理研究,2015,34(2):373-383.KE W Q,YU Z Y,CHEN W,et al.Architecture and key issues for human space-time behavior data observation [J].Geographical Research,2015,34(2):373-383.(Ch).
[4] 张耀军,岑俏.中国人口空间流动格局与省际流动影响因素研究[J].人口研究,2014,38(5):54-71.ZHANG Y J,CEN Q.Spatial patterns of population mobility and determinants of inter-provincial migration in China[J].Population Research,2014,38(5):54-71.(Ch).
[5] 徐玉萍,唐青,付来美,等.高速铁路建设对长三角经济区城市化发展的影响研究[J].华东交通大学学报,2017,34(6):124-132.XU Y P,TANG Q,FU L M,et al.Research on influence of high-speed railway construction on urbanization development in Yangtze River Delta Economic Zone [J].Journal of East China Jiaotong University,2017,34(6):124-132.(Ch).
[6] 武文杰,董正斌,张文忠,等.中国城市空间关联网络结构的时空演变[J].地理学报,2011,66(4):435-445.WU W J,DONG Z B,ZHANG W Z,et al.Spatio-temporal evolution of the China's inter-urban organization network structure:based on aviation data from 1983 to 2006[J].Acta Geographica Sinica,2011,66(4):435-445.(Ch).
[7] CHI G Q.The impacts of highway expansion on population change:an integrated spatial approach[J].Rural Sociology,2010,75(1):58-89.
[8] 敖荣军.劳动力区际流动的选择性及其人力资本再分配效应——基于第5次全国人口普查数据的实证分析[J].华中师范大学学报(自然科学版),2007,41(3):469-472.AO R J.The selectivity of interregional labor migration and its effects on the interregional redistribution of human capital[J].Journal of Central China Normal University (Natural Sciences),2007,41(3):469-472.(Ch).
[9] KRINGS G,CALABRESE F,RATTI C,et al.Urban gravity:a model for inter-city telecommunication flows[J].Journal of Statistical Mechanics:Theory and Experiment,2009(7):L07003 (1-8).
[10] 刘望保,石恩名.“百度迁徙”下中国城市间的人日流动空间格局[J].华南师范大学学报,2016,48(5):67-73.LIU W B,SHI E M.The spatial pattern of population flow among cities based on “Baidu Migration” [J].Journal of South China Normal University,2016,48(5):67-73.(Ch).
[11] 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 W B,SHI E M.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.(Ch).
[12] 刘耀林,方飞国,王一恒.基于手机数据的城市内部就业人口流动特征及形成机制分析——以武汉市为例[J].武汉大学学报(信息科学版),2018,43(12):2212-2224.LIU Y L,FANG F G,WANG Y H.Characteristics and formation mechanism of intra-urban employment flows based on mobile phone data – taking Wuhan city as an example[J].Geomatics and Information Science of Wuhan University,2018,43(12):2212-2224.(Ch).
[13] 曾明星,张善余.中国人口再分布的社会经济合理性及其“多中心集聚”分析[J].南方人口,2013,28(5):71-80.ZENG M X,ZHANG S Y.Analysis of socio-economic rationality of China population redistribution and its polycentric agglomeration[J].South China Population,2013,28(5):71-80.(Ch).