流空间视角下的粤港澳大湾区空间网络格局——基于信息流与交通流的对比分析
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摘要
时空压缩背景下,城市间的空间作用转向关注要素联系视角,动态流空间主导着区域空间网络的新格局。文章从信息流和交通流出发,借助测度修正、空间计量、社会网络分析等方法,从内部与外部联系两个维度对粤港澳大湾区的网络结构特征进行识别与分析。结果发现:①湾区内部联系网络呈现以广深为双核心的结构,佛、莞、珠的中心性地位较突出,其中信息流格局具有沿东岸"弧形"轴线分布的特征,网络体系兼具多中心性和扁平性,而交通流则呈"N"字型沿中部延伸,等级性功能联系较明显;②香港是湾区外部联系网络的枢纽,深、广、澳为核心节点,区域格局深受全球非局域中心联系的影响,但整体的交通外部联系较为匮乏;③湾区综合网络格局以三大枢纽为核心,但制度差异下的空间融合联系受到地方化及地缘偏向的约束,对等级关系有一定的依赖,结构上存在主导性缺失。
In the context of time-space compression, the spatial interaction of intercity relationships turns to factor connection. The dynamic "Space of Flows" plays a dominant role on the regional network structure. Based on the two fundamental element(information flow and transportation flow) and with the compared analysis between internal and external relations of urban flow network, this article distinguishes and analyzes the characteristics of network structure in Guangdong-Hong Kong-Macao Greater Bay Area by such means as measurement modification, spatial quantitative and social network analysis methods. The results are as follows. 1) Internal connection network is characterized by a dualcore structure of Guangzhou and Shenzhen with outstanding nodes of Foshan, Dongguan and Zhuhai on centrality position. The information flow network presents a curve-type structure partial to east coast of the Pearl River estuary with poly-centrality and flatness. Transportation flow, in another way, shows "N"-type central diffusion with distinct hierarchical functional connection feature. 2) Hong Kong is the connection hub of external connection network,Shenzhen, Guangzhou and Macao are core nodes. The regional structure, in this way, is deeply influenced by global-scale non-local connection, whilst shows deficiency of external transportation connection overall. 3) Three hubs jointly construct the centrality of comprehensive network structure of the bay area, but it still lacks dominance and shows certain dependency on the rankings, for localization and geographical deviation turn out to hinder the deep-level integration into global city network and spatial connection under the background of institutional differences.
In the context of time-space compression, the spatial interaction of intercity relationships turns to factor connection. The dynamic "Space of Flows" plays a dominant role on the regional network structure. Based on the two fundamental element(information flow and transportation flow) and with the compared analysis between internal and external relations of urban flow network, this article distinguishes and analyzes the characteristics of network structure in Guangdong-Hong Kong-Macao Greater Bay Area by such means as measurement modification, spatial quantitative and social network analysis methods. The results are as follows. 1) Internal connection network is characterized by a dualcore structure of Guangzhou and Shenzhen with outstanding nodes of Foshan, Dongguan and Zhuhai on centrality position. The information flow network presents a curve-type structure partial to east coast of the Pearl River estuary with poly-centrality and flatness. Transportation flow, in another way, shows "N"-type central diffusion with distinct hierarchical functional connection feature. 2) Hong Kong is the connection hub of external connection network,Shenzhen, Guangzhou and Macao are core nodes. The regional structure, in this way, is deeply influenced by global-scale non-local connection, whilst shows deficiency of external transportation connection overall. 3) Three hubs jointly construct the centrality of comprehensive network structure of the bay area, but it still lacks dominance and shows certain dependency on the rankings, for localization and geographical deviation turn out to hinder the deep-level integration into global city network and spatial connection under the background of institutional differences.
引文
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[18]沈丽珍,席广亮,秦萧,等.基于快递物流测度的区域流动空间特征——以江苏省为例[J].人文地理,2018,33(1):102-108.
[19]陈浩,陆林,郑嬗婷.基于旅游流的城市群旅游地旅游空间网络结构分析——以珠江三角洲城市群为例[J].地理学报,2011,66(2):257-266.
[20]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.
[21]Laharotte P A,Billot R,Come E,et al.Spatiotemporal Analysis of Bluetooth Data:Application to a Large Urban Network[J].IEEE Transactions on Intelligent Transportation Systems,2015,16(3):1 439-1 448.
[22]Derudder B,Taylor P J,Witlox F,et al.Hierarchical Tendencies and Regional Patterns in the World City Network:A Global Urban Analysis of 234 Cities[J].Regional Studies,2003,37(9):875-886.
[23]刘正兵,戴特奇,廖聪,等.中国城际公路货运空间网络特征——基于“第一物流”网站数据[J].经济地理,2017,37(6):28-35.
[24]董超,修春亮,魏冶.基于通信流的吉林省流空间网络格局[J].地理学报,2014,69(4):510-519.
[25]Zhong C,Arisona S M,Huang X,et al.Detecting the Dynamics of Urban Structure through Spatial Network Analysis[J].International Journal of Geographical Information Science,2014,28(11):2 178-2 199.
[26]Taylor P J,Derudder B.World City Network:A Global Urban Analysis[J].International Social Science Journal,2004,31(4):641-642.
[27]Nystuen J D,Dacey M F.A Graph Theory Interpretation of Nodal Regions[J].Papers of the Regional Science Association,1961,7(1):29-42.
[28]Hanssens H,Derudder B,Stefan V A,et al.Assessing the Functional Polycentricity of the Mega-City-Region of Central Belgium Based on Advanced Producer Service Transaction Links[J].Regional Studies,2013,48(12):1 939-1 953.
[29]沈丽珍,顾朝林.区域流动空间整合与全球城市网络构建[J].地理科学,2009,29(6):787-793.
(1)借用知名市场研究公司StatCounter公布的各地区2018年上半年搜索引擎使用份额比来加权,并参考百度指数和Google Trends进行测度修正。
(2)参考各市(特别行政区)政府的相关统计数据进行修正,并借用交通部公布的2017年全国公路、铁路运输旅客周转量比例来加权,没有直达班次的城市对通过考察间接联系转化为流强度。
(1)交通流以直达航班联系为数据源,对湾区内广州、深圳、珠海、香港、澳门等地的五大机场进行测度。
[2]Taylor P J,Hoyler M,Verbruggen R.External Urban Relational Process:Introducing Central Flow Theory to Complement Central Place Theory[J].Urban Studies,2010,47(13):2 803-2 818.
[3]Castells M.The Informational City:Information Technology,Economic Restructuring and the Urban-Regional Progress[M].Oxford UK&Cambridge USA:Blackwell,1989.
[4]Castells M.The Rise of the Network Society(The Information Age:Economy,Society and Culture,Volume 1)[M].Cambridge,MA:Blackwell Publishers,1996.
[5]Townsend A M.Network Cities and the Global Structure of the Internet[J].American Behavioral Scientist,2001,44(10):1 697-1 716.
[6]Derudder B.Mapping Global Urban Networks:A Decade of Empirical World Cities Research[J].Geography Compass,2010,2(2):559-574.
[7]马学广,李贵才.全球流动空间中的当代世界城市网络理论研究[J].经济地理,2011,31(10):1 630-1 637.
[8]Castells M.Globalisation,Networking,Urbanisation:Reflections on the Spatial Dynamics of the Information Age[J].Urban Studies,2010,47(13):2 737-2 745.
[9]Pflieger G,Rozenblat C.Urban Networks and Network Theory:The City as the Connector of Multiple Networks[J].Urban Studies,2010,47(13):2 723-2 735.
[10]Taylor P J,Catalano G,Walker D R F.Measurement of the World City Network[J].Urban Studies,2002,39(39):2 367-2 376.
[11]Kr?tke S.How Manufacturing Industries Connect Cities across the World:Extending Research on‘Multiple Globalizations’[J].Global Networks,2014,14(2):121-147.
[12]Matsumoto H.International Urban Systems and Air Passenger and Cargo Flows:Some Calculations[J].Journal of Air Transport Management,2004,10(4):239-247.
[13]孙中伟,路紫.流空间基本性质的地理学透视[J].地理与地理信息科学,2005,21(1):111-114.
[14]高鑫,修春亮,魏冶.城市地理学的“流空间”视角及其中国化研究[J].人文地理,2012,27(4):32-36.
[15]孙中伟,路紫,贺军亮.世界互联网信息流的空间格局及其组织机理[J].人文地理,2009,24(4):43-49.
[16]陈伟,修春亮,陈金星,等.中国城市间交通流强度的空间格局[J].人文地理,2015,30(4):116-122.
[17]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.
[18]沈丽珍,席广亮,秦萧,等.基于快递物流测度的区域流动空间特征——以江苏省为例[J].人文地理,2018,33(1):102-108.
[19]陈浩,陆林,郑嬗婷.基于旅游流的城市群旅游地旅游空间网络结构分析——以珠江三角洲城市群为例[J].地理学报,2011,66(2):257-266.
[20]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.
[21]Laharotte P A,Billot R,Come E,et al.Spatiotemporal Analysis of Bluetooth Data:Application to a Large Urban Network[J].IEEE Transactions on Intelligent Transportation Systems,2015,16(3):1 439-1 448.
[22]Derudder B,Taylor P J,Witlox F,et al.Hierarchical Tendencies and Regional Patterns in the World City Network:A Global Urban Analysis of 234 Cities[J].Regional Studies,2003,37(9):875-886.
[23]刘正兵,戴特奇,廖聪,等.中国城际公路货运空间网络特征——基于“第一物流”网站数据[J].经济地理,2017,37(6):28-35.
[24]董超,修春亮,魏冶.基于通信流的吉林省流空间网络格局[J].地理学报,2014,69(4):510-519.
[25]Zhong C,Arisona S M,Huang X,et al.Detecting the Dynamics of Urban Structure through Spatial Network Analysis[J].International Journal of Geographical Information Science,2014,28(11):2 178-2 199.
[26]Taylor P J,Derudder B.World City Network:A Global Urban Analysis[J].International Social Science Journal,2004,31(4):641-642.
[27]Nystuen J D,Dacey M F.A Graph Theory Interpretation of Nodal Regions[J].Papers of the Regional Science Association,1961,7(1):29-42.
[28]Hanssens H,Derudder B,Stefan V A,et al.Assessing the Functional Polycentricity of the Mega-City-Region of Central Belgium Based on Advanced Producer Service Transaction Links[J].Regional Studies,2013,48(12):1 939-1 953.
[29]沈丽珍,顾朝林.区域流动空间整合与全球城市网络构建[J].地理科学,2009,29(6):787-793.
(1)借用知名市场研究公司StatCounter公布的各地区2018年上半年搜索引擎使用份额比来加权,并参考百度指数和Google Trends进行测度修正。
(2)参考各市(特别行政区)政府的相关统计数据进行修正,并借用交通部公布的2017年全国公路、铁路运输旅客周转量比例来加权,没有直达班次的城市对通过考察间接联系转化为流强度。
(1)交通流以直达航班联系为数据源,对湾区内广州、深圳、珠海、香港、澳门等地的五大机场进行测度。
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