“交通—产业”耦合背景下的京津冀城市群空间发育特征

doi:10.18306/dlkxjz.2018.09.006

Abstract

Abstract:

The interaction of production factors among cities plays a significant role in the spatial expansion of urban agglomerations. Meanwhile, it drives the change of urban agglomerations from a single-level flat regional space into a multi-level network system. The shift of Chinese urban agglomerations from segregated regions to spatial networks has become the focus of academic research in recent years. Studies have advanced an argument that the relations of traffic and industry between each city-pair not only provide internal dynamics for the spatial expansion and hierarchical organization of urban agglomeration, but also describe the development state of urban agglomeration. Based on the perspective of coupling relationship between traffic and industry, this study identified the multi-level spatial structure and development scope of the Beijing-Tianjin-Hebei urban agglomeration by spatial network analysis, gravity model, and Multi-level Spatial Structure Tree (MSS-Tree), using socioeconomic data, traffic volume data, and enterprise network data. We first selected the municipal districts of Beijing, Tianjin, Shijiazhuang, and Tangshan cities as four radiation centers based on the result of comprehensive strength calculated by factor analysis. Then we combined the gravity model with the MSS-Tree algorithm, and the result shows that continuity, hierarchy, and difference coexist in the theoretical spatial structure of the urban agglomeration. Meanwhile, we applied traffic volume data and enterprise network data to the MSS-Tree algorithm, and the result shows that current spatial structure presents the characteristics of fragmentation, hollow, and jumping, which is quite different from the theoretical structure. According to the comparison between the current scope and the theoretical scope, the current development scope is smaller, and there is obvious an "island and cave" phenomenon in the radiation area of radiation centers, which show contiguous distribution of metropolitan shadow areas. For the four radiation centers, there is a lack of mature sub-centers around Beijing; the spatial scale of radiation area around Tianjin is shrinking greatly because of the polarization effect of Beijing; and the radiation areas around Shijiazhuang and Tangshan are poorly developed, indicating that the two cities need to strengthen their own economic construction. Further, the comparison between traffic and industry radiation areas reveals the phenomenon that traffic develops first while industry lags behind. The unbalanced coupling relationship between traffic and industry leads to low coincidence degree in radiation areas of these two factors. The leading role of traffic accelerates loss of production factors from small or medium-sized cities, thus forms the poverty belt around Beijing and Tianjin. From the perspective of traffic-industry coupling relationship, this study explored the existing problems and their mechanism, which is significant for efficient synergy in the spatial development of urban agglomerations. Finally. Based on the perspective of local government, this article proposed regional development strategies of integration from bottom to top and expansion from inside to outside.

Key words: urban agglomeration, coupling relation, spatial structure, development scope, MSS-Tree, network analysis, Beijing-Tianjin-Hebei urban agglomeration

Xiaomeng WANG, Jin WANG, Dianting WU. Spatial development of the Beijing-Tianjin-Hebei urban agglomeration from the perspective of traffic-industry coupling relation[J].PROGRESS IN GEOGRAPHY, 2018, 37(9): 1231-1244.

Figures/Tables 10

Tab.1

Fig.1

Tab.2

Two-hour commuting range of Beijing, Tianjin, Shijiazhuang and Tangshan

核心城市	两小时通勤圈
北京市中心城区(东城区、西城区、海淀区、朝阳区、丰台区、石景山区)	昌平区、通州区、顺义区、大兴区、大厂回族自治县、固安县、涿州市、三河市、香河县、门头沟区、平谷区、怀来县、武清区、廊坊市城区、延庆区、房山区、密云区、永清县、北辰区、定兴县、高碑店市、蓟州区、雄县、霸州市、玉田县、怀柔区、容城县、宝坻区、东丽区、天津市城区、易县、西青区、宁河区、安新县、静海区、涿鹿县、文安县、津南区、任丘市、大城县、保定城区、滨海新区、张家口城区、高阳县、滦平县、遵化市、承德市城区、涞水县、兴隆县、蔚县
天津市中心城区(河东区、河西区、和平区、南开区、河北区、红桥区)	北辰区、东丽区、西青区、津南区、武清区、静海区、滨海新区、宁河区、霸州市、宝坻区、青县、永清县、廊坊市城区、玉田县、香河县、黄骅市、大城县、文安县、沧县、通州区、唐山市城区、固安县、沧州市城区、雄县、大厂回族自治县、容城县、大兴区、蓟州区、北京市城区、海兴县、三河市、高碑店市、顺义区、孟村回族自治县、安新县、滦南县、平谷区、南皮县、任丘市、涿州市、滦县、献县、盐山县、定兴县、高阳县、泊头市、遵化市、昌平区、乐亭县、河间市、东光县、肃宁县、吴桥县、房山区、迁安市、门头沟区、昌黎县、怀柔区
石家庄市中心城区(新华区、桥西区、长安区、裕华区)	正定县、新乐市、井陉县、赵县、元氏县、高邑县、无极县、行唐县、平山县、宁晋县、晋州市、定州市、深泽县、赞皇县、深州市、柏乡县、望都县、新河县、隆尧县、曲阳县、辛集市、临城县、安平县、南宫市、灵寿县、安国市、内丘县、顺平县、博野县、武强县、保定市城区、巨鹿县、南和县、唐县、饶阳县、衡水市城区、任县、威县、武邑县、永年县、献县、高阳县、清河县、广宗县、阜平县、鸡泽县、肃宁县、平乡县、容城县、邢台市城区、邯郸县、蠡县、枣强县、定兴县、沙河市、景县、任丘市、成安县、河间市、高碑店市
唐山市中心城区(路南区、路北区、古冶区、开平区、丰南区、丰润区)	霸州市、宝坻区、北辰区、滨海新区、昌黎县、承德市城区、大厂回族自治县、东丽区、蓟州区、津南区、静海区、廊坊市城区、乐亭县、卢龙县、滦南县、滦县、宁河区、平谷区、迁安市、迁西县、秦皇岛市城区、青龙满族自治县、青县、三河市、天津市城区、通州区、武清区、西青区、香河县、兴隆县、玉田县、遵化市

Tab.2

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Tab.3

References 51

[1]	彼得·霍尔, 凯西·佩恩. 2010.多中心大都市: 来自欧洲巨型城市区域的经验[M]. 罗震东, 等, 译. 北京: 中国建筑工业出版社.
	[Hall P, Penn C.2010.Polycentric metropolis: Experience from a large urban area in Europe[M]. Luo Z D, et al, Trans. Beijing, China: China Architecture & Building Press.]
[2]	毕秀晶, 宁越敏. 2013. 长三角大都市区空间溢出与城市群集聚扩散的空间计量分析[J]. 经济地理, 33(1): 46-53.
	[Bi Q J, Ning Y M.2013. Empirical research on spatial spillover of metropolitan and the spatial agglomeration and dispersion in Yangtze River Delta urban agglomeration[J]. Economic Geography, 33(1): 46-53.]
[3]	党彦龙, 白永亮. 2014. 长江中游城市群经济空间辐射范围和空间结构研究[J]. 开发研究, (5): 53-57.
	[Dang Y L, Bai Y L.2014. Study on the spatial radiation range and spatial structure of urban agglomeration in the middle reaches of Yangtze River[J]. Research on Development, (5): 53-57.]
[4]	丁睿, 顾朝林, 庞海峰, 等. 2006. 2020年中国城市等级规模结构预测[J]. 经济地理, 26(S1): 218-221.
	[Ding R, Gu C L, Pang H F, et al.2006. Forecast for rank-size of China' s urban system in 2020[J]. Economic Geography, 26(S1): 218-221.]
[5]	方创琳. 2009. 城市群空间范围识别标准的研究进展与基本判断[J]. 城市规划学刊, (4): 1-6.
	[Fang C L.2009. Research progress and general definition about identification standards of urban agglomeration space[J]. Urban Planning Forum, (4): 1-6.]
[6]	方大春, 孙明月. 2015. 高铁时代下长三角城市群空间结构重构: 基于社会网络分析[J]. 经济地理, 35(10): 50-56.
	[Fang D C, Sun M Y.2015. The reconstruction of the spatial structure of the Yangtze River Delta city group in the high-speed era: Based on the social network analysis[J]. Economic Geography, 35(10): 50-56.]
[7]	高晓路, 许泽宁, 牛方曲. 2015. 基于“点—轴系统”理论的城市群边界识别[J]. 地理科学进展, 34(3): 280-289.
	[Gao X L, Xu Z N, Niu F Q.2015. Delineating the scope of urban agglomerations based upon the Pole-Axis theory[J]. Progress in Geography, 34(3): 280-289.]
[8]	顾朝林. 1991. 中国城市经济区划分的初步研究[J]. 地理学报, 1(2): 3-15.
	[Gu C L.1991. A perliminary study on the division of urban economic regions in China[J]. Acta Geographica Sinica, 1(2): 3-15.]
[9]	顾朝林. 1992. 城市实力综合评价方法初探[J]. 地域研究与开发, (1): 5-11.
	[Gu C L, 1992. Methods of evaluting the urban comprehensive strength index[J]. Areal Research and Development, (1): 5-11.]
[10]	顾朝林. 2011. 城市群研究进展与展望[J]. 地理研究, 30(5): 771-784.
	[Gu C L.2011. Study on urban agglomeration: Progress and prospects[J]. Geographical Research, 30(5): 771-784.]
[11]	黄金川. 2016. 基于辐射扩散测度的中国城市群发育格局识别[J]. 经济地理, 36(11): 199-206.
	[Huang J C.2016. Dentification of urban agglomeration in China based on radiation diffusion measurement[J]. Economic Geography, 36(11): 199-206.]
[12]	黄金川, 林浩曦. 2017. 京津冀城市群多情景空间演化模拟[J]. 地理研究, 36(3): 506-517.
	[Huang J C, Lin H X.2017. Spatial evolution analysis and multi-scenarios simulation of Beijing-Tianjin-Hebei urban agglomeration[J]. Geographical Research, 36(3): 506-517.]
[13]	黄金川, 刘倩倩, 陈明. 2014. 基于GIS的中国城市群发育格局识别研究[J]. 城市规划学刊, (3): 37-44.
	[Huang J C, Liu Q Q, Chen M.2014. The identificatipn of urban agglomeration distribution in China based on GIS analysis[J]. Urban Planning Forum, (3): 37-44.]
[14]	李少星. 2009. 改革开放以来中国城市等级体系演变的基本特征[J]. 地理与地理信息科学, 25(3): 58-61.
	[Li S X.2009. Evolution characters of urban hierarchy system in China since the Reform and Opening-up[J]. Geography and Geo-Information Science, 25(3): 58-61.]
[15]	李震, 顾朝林, 姚士媒. 2006. 当代中国城镇体系地域空间结构类型定量研究[J]. 地理科学, 26(5): 544-550.
	[Li Z, Gu C L, Yao S M.2006. A quantitative study on regional spatial structure of urban system in contemporary China[J]. Scientia Geographica Sinica, 26(5): 544-550.]
[16]	梁经伟, 文淑惠, 方俊智. 2015. 中国-东盟自贸区城市群空间经济关联研究: 基于社会网络分析法的视角[J]. 地理科学, 35(5): 521-528.
	[Liang J W, Wen S H, Fang J Z.2015. The spatial economic association of city agglomeration on CAFTA based on the perspective of social network analysis[J]. Scientia Geographica Sinica, 35(5): 521-528.]
[17]	林平, 杜姗姗. 2015. 基于GIS和计量模型的首都城市群空间范围界定[J]. 北京联合大学学报, 29(3): 58-66.
	[Lin P, Du S S.2015. Definition of space range of capital city group based on GIS and measurement model[J]. Journal of Beijing Union University, 29(3): 58-66.]
[18]	刘飞, 郑新奇, 黄晴. 2017. 基于空间分形特征的城市群实体空间识别方法[J]. 地理科学进展, 36(6): 677-684.
	[Liu F, Zheng X Q, Huang Q.2017. Identification of the physical space of urban systems based on fractal analysis[J]. Progress in Geography, 36(6): 677-684.]
[19]	陆大道. 2012. 关于避免中国交通建设过度超前的建议[J]. 地理科学, 32(1): 2-11.
	[Lu D D.2012. The proposition to avoid the over advance and inappropriate construction of China′s transport infrastructures[J]. Scientia Geographica Sinica, 32(1): 2-11.]
[20]	毛汉英. 2017. 京津冀协同发展的机制创新与区域政策研究[J]. 地理科学进展, 36(1): 2-14.
	[Mao H Y.2017. Innovation of mechanism and regional policy for promoting coordinated development of the Beijing-Tianjin-Hebei[J]. Progress in Geography, 36(1): 2-14.]
[21]	毛晓汶. 2014. 基于手机信令技术的区域交通出行特征研究[D]. 重庆: 重庆交通大学.
	[Mao X W.2014. Research of regional traffic characteristics based on mobile signaling technology[D]. Chongqing, China: Chongqing Jiaotong University.]
[22]	苗长虹, 王海江. 2005. 中国城市群发展态势分析[J]. 城市发展研究, 12(4): 11-14.
	[Miao C H, Wang H J.2005. The analysis on developmental situations of China's urban agglomerations[J]. Urban Studies, 12(4): 11-14.]
[23]	宁越敏. 2011. 中国都市区和大城市群的界定: 兼论大城市群在区域经济发展中的作用[J]. 地理科学, 31(3): 257-263.
	[Ning Y M.2011. Definition of Chinese metropolitan areas and large urban agglomerations: Role of large urban agglomerations in regional development[J]. Scientia Geographica Sinica, 31(3): 257-263.]
[24]	牛方曲, 刘卫东. 2016. 基于互联网大数据的区域多层次空间结构分析研究[J]. 地球信息科学学报, 18(6): 719-726. doi: 10.3724/SP.J.1047.2016.00719
	[Niu F Q, Liu W D.2016. Identifying the hierarchical regional spatial structure using internet big data[J]. Journal of Geo-information Science, 18(6): 719-726.] doi: 10.3724/SP.J.1047.2016.00719
[25]	牛方曲, 刘卫东, 宋涛, 等. 2015. 城市群多层次空间结构分析算法及其应用: 以京津冀城市群为例[J]. 地理研究, 34(8): 1447-1460.
	[Niu F Q, Liu W D, Song T, et al.2015. A multi-level spatial structure analysis algorithm for urban agglomeration study in China[J]. Geographical Research, 34(8): 1447-1460.]
[26]	潘竟虎, 戴维丽. 2017. 基于网络分析的城市影响区和城市群空间范围识别[J]. 地理科学进展, 36(6): 667-676.
	[Pan J H, Dai W L.2017. Identification of urban hinterlands and urban agglomerations in China based on network analysis[J]. Progress in Geography, 36(6): 667-676.]
[27]	秦晴晴. 2013. 城际轨道交通对城市群产业竞争力的作用评价研究[D]. 北京: 北京交通大学.
	[Qin Q Q.2013. Research on effece of intercity rail transit on industrial competitiveness of urban agglomeration[D]. Beijing, China: Beijing Jiaotong University.]
[28]	舒松. 2013. 基于稳定夜间灯光遥感数据的城市群空间模式识别方法研究[D]. 上海: 华东师范大学.
	[Shu S.2013. Spatial cluster analysis of urban landscape pattern using stable nighttime light satellite images[D]. Shanghai, China: East China Normal University.]
[29]	苏睿先. 2012. 基于可持续发展理念的区域产业安全评估: 以天津滨海新区为例[J]. 经济地理, 32(10): 89-94.
	[Su R X.2012. Evaluation of regional industry security based on sustainable development theory: A case study of Binhai New Area,Tianjin[J]. Economic Geography, 32(10): 89-94.]
[30]	吴殿廷. 1992. 国力综合评估中的几个问题[J]. 人文地理, (2): 59-65.
	[Wu D T.1992. Some problems in the comprehensive evaluation of the national power[J]. Human Geography, (2): 59-65.]
[31]	夏国恩, 兰政海. 2009. 基于因子分析的广西区各城市综合经济实力评价[J]. 特区经济, (12): 211-213.
	[Xia G N, Lan Z H.2009. The evalution of urban comprehensive economic strength in Guangxi District based on factor analysis[J]. Special Zone Economy, (12): 211-213.]
[32]	徐玉静, 王帅民, 赵明月. 2017. 天津滨海新区土地利用变化及驱动因子分析[J]. 测绘与空间地理信息, 40(4): 220-224.
	[Xu Y J, Wang S M, Zhao M Y.2017. Analysis of land use change and driving factors in Tianjin Binhai New Area[J]. Geomatics & Spatial Information Technology, 40(4): 220-224.]
[33]	伊利尔·沙里宁. 1986.城市: 它的发展、衰败与未来[M]. 顾启元, 译. 北京: 中国建筑工业出版社.
	[Saarinen E.1986.City: Its development, decline and future[M]. Gu Q Y, Trans. Beijing, China: China Architecture & Building Press.]
[34]	虞虎, 陈田, 陆林, 等. 2014. 江淮城市群旅游经济网络空间结构与空间发展模式[J]. 地理科学进展, 33(2): 169-180. doi: 10.11820/dlkxjz.2014.02.003
	[Yu H, Chen T, Lu L, et al.2014. Structure of tourist economy network and its spatial development pattern in Jianghuai urban agglomeration[J]. Progress in Geography, 33(2): 169-180.] doi: 10.11820/dlkxjz.2014.02.003
[35]	张莉. 2001. 我国区际经济联系探讨: 以铁路客运为例[J]. 中国软科学, (11): 99-103.
	[Zhang L.2001. Study on the inter-regional economic linkage in China[J]. China Soft Science, (11): 99-103.]
[36]	张萍, 张玉鑫. 2013. 上海大都市区空间范围研究[J]. 城市规划学刊, (4): 27-32.
	[Zhang P, Zhang Y X.2013. 上海大都市区空间范围研究[J]. Urban Planning Forum, (4): 27-32.]
[37]	张倩, 胡云锋, 刘纪远, 等. 2011. 基于交通、人口和经济的中国城市群识别[J]. 地理学报, 66(6): 761-770.
	[Zhang Q, Hu Y F, Liu J Y, et al.2011. Identification of urban clusters in China based on assessment of transportation accessibility and socio-economic indicators[J]. Acta Geographica Sinica, 66(6): 761-770.]
[38]	张荣天. 2017. 长三角城市群网络结构时空演变分析[J]. 经济地理, 37(2): 46-52.
	[Zhang R T.2017. Urban agglomeration spatial network structure spatial-temporal evolution in the Yangtze River Delta[J]. Economic Geography, 37(2): 46-52.]
[39]	张毅, 张恒奇, 欧阳斌, 等. 2014. 绿色低碳交通与产业结构的关联分析及能源强度的趋势预测[J]. 中国人口·资源与环境, 24(S3): 5-9.
	[Zhang Y, Zhang H Q, Ouyang B, et al.2014. Analysis and forecast of energy consumption in transportation industry: Based on the grey model[J]. China Population, Resources and Environment, 24(S3): 5-9.]
[40]	赵璟, 刘佳. 2015. 基于动态因子分析的区域城市化质量时空分析: 以陕西省关中城市群为例[J]. 地理与地理信息科学, 31(2): 81-86.
	[Zhao J, Liu J.2015. Space-time analysis of regional urbanization quality based on dynamic factor analysis: A case study of Guanzhong urban agglomeration in Shaanxi Province[J]. Geography and Geo-Information Science, 31(2): 81-86.]
[41]	甄峰, 王波, 陈映雪. 2012. 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, 67(8): 1031-1043.
	[Zhen F, Wang B, Chen Y X.2012. China's city network characteristics based on social network space: An empirical analysis of Sina micro-blog[J]. Acta Geographica Sinica, 67(8): 1031-1043.]
[42]	朱查松, 王德, 罗震东. 2014. 中心性与控制力: 长三角城市网络结构的组织特征及演化: 企业联系的视角[J]. 城市规划学刊, (4): 24-30.
	[Zhu C S, Wang D, Luo Z D.2014. Centrality and power: A method of analyzing city network spatial structure[J]. Urban Planning Forum, (4): 24-30.]
[43]	朱英明. 2004.城市群经济空间分析[M]. 北京: 科学出版社.
	[Zhu Y M.2004.Economic space analysis of urban agglomeration[M]. Beijing, China: Science Press.]
[44]	Fujita M, Mori T.2004. Structural stability and evolution of urban systems[J]. Regional Science & Urban Economics, 27(4-5): 399-442.
[45]	Goddard J B, Berry B J L, Horton F E.2016. Geographic perspectives on urban systems[J]. Geographical Journal, 137(1):103.
[46]	Golledge R G, Stimson R J.1997. Spatial behavior: A geographic perspective[J]. Economic Geography, 74(1): 83-85.
[47]	Howard E.2010.Tomorrow: A peaceful path to real reform[M]. Cambridge, UK: Cambridge University Press.
[48]	Lan M U, Wang X.2006. Population landscape: A geometric approach to studying spatial patterns of the US urban hierarchy[J]. International Journal of Geographical Information Science, 20(6): 649-667. doi: 10.1080/13658810600661342
[49]	Marchetti C.1994. Anthropological invariants in travel behavior[J]. Technological Forecasting & Social Change, 47(1): 75-88.
[50]	Meller H E.1973. Patrick Geddes: An analysis of his theory of civics, 1880-1904[J]. Victorian Studies, 16(3): 291-315.
[51]	Smith R.1974. New towns: Regional planning and development[J]. Urban Studies, 11(1): 114-115. doi: 10.1080/00420987420080241

序号	指标	权重	主成分
1	地区生产总值/万元	0.909	主成分1：经济实力
2	第三产业产值比重/%	0.958
3	地方一般财政收入/万元	0.769
4	规模以上工业企业主营业务收入/万元	0.858
5	年末总人口/万人	0.617	主成分2：人口流动潜力
6	城镇在岗职工人数/万人	0.745	主成分2：人口流动潜力
7	全社会固定资产投资额/万元	0.814	主成分3：投融资能力
8	实际使用外资/万美元	0.827
9	城乡居民存款年末余额/万元	0.893
10	社会消费品零售总额/万元	0.858	主成分4：商业中心特点

Spatial development of the Beijing-Tianjin-Hebei urban agglomeration from the perspective of traffic-industry coupling relation

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核心城市	区县名称	所属地级市
北京	定兴县	保定市
	大厂县	廊坊市
	津南区	天津市
	宁河区	天津市
天津	大城县	廊坊市
	沧县	沧州市
	宁河区	天津市
	津南区	天津市

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