基于多源流数据的京津冀城市群网络结构研究
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摘要
基于腾讯位置大数据与百度指数的多源流数据,以京津冀地区13个城市为研究对象,运用GIS与社会网络分析方法对京津冀城市群网络结构进行量化研究。结果表明:交通流网络呈倒"L"型格局,形成了京保石、京津两条轴线,交通流受到交通基础设施的较强影响;信息流网络呈以北京为核心的放射型格局,知识创新能力成为影响信息流网络的重要因素。交通流网络密度为0.801,信息流网络密度为0.897,交通信息流整体网络呈现强连接状态。信息流网络有效覆盖城市群大部分城市,一般联系型城市占城市群的一小部分;交通流网络呈现明显的核心-边缘结构,北京、天津、廊坊形成交通流网络中的核心区域。京津冀城市群交通信息流网络分为4个子群,核心子群之间联系紧密,呈现北京带动全域、次级核心城市带动周边城市的嵌套式发展趋势。
Based on the multi-source flow data of Tencent location big data and Baidu index,this paper takes 13 cities in Beijing-Tianjin-Hebei region as the research object,and uses GIS and social network analysis method to conduct quantitative research on the network structure of Beijing-Tianjin-Hebei urban agglomeration.The results show that:the traffic flow network presents an inverted "L" pattern,forming the two axes of Beijing-Baoding-Shijiazhuang and Beijing-Tianjin,and the traffic flow is strongly influenced by the traffic infrastructure;the information flow network is radiated with Beijing as the core,and knowledge innovation ability becomes an important factor affecting the information flow network. The traffic flow network density is 0.801,the information flow network density is 0.897,the traffic information flow network as a whole is strongly connected. The information flow network effectively covers most cities in the urban agglomeration, and generally connected cities account for a small part of the urban agglomeration;the traffic flow network presents obvious core-edge structure,and Beijing, Tianjin and Langfang form the core area of the traffic flow network. The traffic information flow network of the Beijing-Tianjin-Hebei urban agglomeration is divided into four sub-groups, and the core sub-groups are closely related to each other,showing the nested development trend of Beijing driving the whole region and the secondary core cities driving the surrounding cities.
Based on the multi-source flow data of Tencent location big data and Baidu index,this paper takes 13 cities in Beijing-Tianjin-Hebei region as the research object,and uses GIS and social network analysis method to conduct quantitative research on the network structure of Beijing-Tianjin-Hebei urban agglomeration.The results show that:the traffic flow network presents an inverted "L" pattern,forming the two axes of Beijing-Baoding-Shijiazhuang and Beijing-Tianjin,and the traffic flow is strongly influenced by the traffic infrastructure;the information flow network is radiated with Beijing as the core,and knowledge innovation ability becomes an important factor affecting the information flow network. The traffic flow network density is 0.801,the information flow network density is 0.897,the traffic information flow network as a whole is strongly connected. The information flow network effectively covers most cities in the urban agglomeration, and generally connected cities account for a small part of the urban agglomeration;the traffic flow network presents obvious core-edge structure,and Beijing, Tianjin and Langfang form the core area of the traffic flow network. The traffic information flow network of the Beijing-Tianjin-Hebei urban agglomeration is divided into four sub-groups, and the core sub-groups are closely related to each other,showing the nested development trend of Beijing driving the whole region and the secondary core cities driving the surrounding cities.
引文
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[19]张贵,李涛,原慧华.京津冀协同发展视阈下创新创业生态系统构建研究[J].经济与管理,2017,31(6):5-11.
[20]叶强,张俪璇,彭鹏,等.基于百度迁徙数据的长江中游城市群网络特征研究[J].经济地理,2017,37(8):53-59.
[2]DERUDDER B,WITLOX F.Mapping world city networks through airline flows:context,relevance,and problems[J].Journal of transport geography,2008,16(5):305-312.
[3]TAYLOR P J,DERUDDER B.World city network:a global urban analysis[M].New York:Routledge,2015.
[4]关溪媛.长江三角洲城市体系网络化演进研究---基于企业关联方法[J].现代城市研究,2017(10):95-100.
[5]赵映慧,初楠臣,郭晶鹏,等.中国三大城市群高速铁路网络结构与特征[J].经济地理,2017,37(10):68-73.
[6]熊丽芳,甄峰,王波,等.基于百度指数的长三角核心区城市网络特征研究[J].经济地理,2013,33(7):67-73.
[7]赵金丽,张璐璐,宋金平.京津冀城市群城市体系空间结构及其演变特征[J].地域研究与开发,2018,37(2):9-13,24.
[8]CASTELLS M.Rise of the network society[M].Blackwell Publishers,2000.
[9]CASTELLS M.Grassrooting the space of flows[J].Urban geography,1999,20(4):294-302.
[10]修春亮,魏冶等.“流空间”视角的城市与区域结构[M].北京:科学出版社,2015.
[11]TAYLOR P J.Urban economics in thrall to Christaller:a misguided search for city hierarchies in external urban relations[J].Environment and planning A,2009,41(11):2550-2555.
[12]林晓言,罗燊.知识流空间与高速铁路[J].吉首大学学报(社会科学版),2017,38(3):51-58.
[13]GRAHAM S,MARVIN S.Telecommunications and the city:electronic spaces,urban places[M].New York:Routledge,1996.
[14]GRAHAM S,MARVIN S.Splintering urbanism:networked infrastructures,technological mobilities and the urban condition[M].New York:Routledge,2001.
[15]史雅娟,朱永彬,冯德显,等.中原城市群多中心网络式空间发展模式研究[J].地理科学,2012,32(12):1430-1438.
[16]B ATTEN D.Network cities:creative urban agglomerations for the 21st century[J].Urban studies,1995,32(2):313-327.
[17]王珺,周均清.从“单中心区域”到“网络城市”---武汉城市圈空间格局优化战略研究[J].国际城市规划,2008(5):88-91.
[18]初钊鹏.河北沿海承接北京世界城市功能拓展的空间发展模式---以秦皇岛市为例[J].经济地理,2015,35(1):53-60.
[19]张贵,李涛,原慧华.京津冀协同发展视阈下创新创业生态系统构建研究[J].经济与管理,2017,31(6):5-11.
[20]叶强,张俪璇,彭鹏,等.基于百度迁徙数据的长江中游城市群网络特征研究[J].经济地理,2017,37(8):53-59.