“流空间”视角下成渝地区双城经济圈城市网络结构研究

doi:10.3969/j.issn.1004-9479.2024.09.20222424

摘要/Abstract

摘要：

引领成渝地区双城经济圈向世界级城市群迈进，促进区域经济一体化发展，以区域内循环助推国内大循环，对加快形成以国内大循环为主体、国内国际双循环相互促进的新发展格局具有重要意义。基于城市网络结构视角，采用铁路公路客运班次、区域外向功能影响量、人口迁徙量和百度指数数据，在构建交通、经济、人口和信息城市空间联系网络的基础上，运用社会网络分析方法，借助ArcGIS空间分析工具的可视化功能，对成渝地区双城经济圈城市网络结构特征及其差异进行刻画，进而针对各网络从不同视角提出网络结构优化策略和建议。结果表明：（1）城市网络表现出以“成都和重庆”为主的双核心圈层放射状空间结构，总体网络联系空间呈“非均衡”格局。（2）城市体系雏形初显，网络结构不具备稳定性，韧性能力有待进一步提升。整体指标测算显示各城市网络紧密性总体表现为人口>信息>经济>交通。（3）“核心-边缘”效应均显著，“塌陷”现象明显，缺乏强有力的次级中心城市。（4）凝聚子群分布形态差异性强，子群内城市的地域空间分布基本符合地理邻近性。

关键词: 网络结构, 流空间, 中心度, 凝聚子群, 成渝地区

Abstract:

It is of great significance to lead Chengdu-Chongqing economic circle to stride forward to world-class urban agglomeration, promote regional economic integrated development, and boost domestic circulation with regional circulation for accelerating the formation of a new development pattern with domestic circulation as the main body and the domestic and international dual circulation promoting each other. Based on the perspective of urban network structure, the urban network structure characteristics and differences of Chengdu-Chongqing Economic Circle are described by using the social network analysis method and the visualization function of ArcGIS spatial analysis tool on the basis of constructing the urban spatial connection network of transportation, economy, population and information by using the data of railway and highway passenger transport frequency, regional outward function influence quantity, population migration quantity and Baidu index. Finally, the optimization strategies and suggestions of the network structure of Chengdu-Chongqing economic circle are put forward from different perspectives. The results show that: (1) The urban network shows a dual-core circle radial spatial structure dominated by "Chengdu and Chongqing", and the overall network connection presents an "unbalanced" pattern. (2) The embryonic form of urban system is emerging, the network structure is not stable, and the resilience needs to be further improved. The overall index calculation shows that the tightness of the urban network is population> information> economy> transportation. (3) The "core-periphery" effect is significant, the "collapse" phenomenon is obvious, and there is no strong secondary central city. (4) The distribution of cohesive subgroups is highly different, and the spatial distribution of the cities in the agglomerated subgroups is basically in line with the geographical proximity.

Key words: network structure, flow space, centrality, agglomerative subgroup, Chengdu-Chongqing region

孙芳城, 张娜, 胡钰苓, 唐菁. “流空间”视角下成渝地区双城经济圈城市网络结构研究[J]. 世界地理研究, 2024, 33(9): 147-162.

Fangcheng SUN, Na ZHANG, Yuling HU, Jing TANG. Research on urban network structure in Chengdu-Chongqing Economic Circle based from the perspective of "flow space"[J]. World Regional Studies, 2024, 33(9): 147-162.

图/表 8

参考文献 42

1	孟德友,冯兴华,文玉钊.铁路客运视角下东北地区城市网络结构演变及组织模式探讨.地理研究,2017,36(7):1339-1352.
	MENG D, FENG X, WEN Y. Urban network structure evolution and organizational pattern in Northeast China from the perspective of railway passenger transport. Geographical Research,2017,36(7):1339-1352.
2	CASTELLS M.The Rise of Network Society.Oxford:Blackwell,1996.
3	ALDERSON A S, BECKFIELD J. Power and position in the world city system. American Journal of Sociology,2004,109(4):811-851.
4	DERUDDER B. An appraisal of the use of airline data in assessing the world city network: A research note on data. Urban Studies,2005,42(13):2371-2388.
5	AELST S V. Assessing the functional polycentricity of the mega-city- region of central Belgium based on advanced producer service transaction links. Regional Studies, 2014, 48(12): 1939-1953.
6	ZHONG C, ARISONA S M, HUANG X. Detecting the dynamics of urban structure through spatial network analysis. International Journal of Geographical Information Science,2014, 28(11): 2178-2199.
7	董琦,甄峰.基于物流企业网络的中国城市网络空间结构特征研究.人文地理,2013,28(4):71-76.
	DONG Q, ZHEN F. The study on spatial structure characteristic of China's city network based on the logistics enterprise network. Human Geography,2013,28(4):71-76.
8	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.城市规划,2017,41(6):18-26.
	JIANG X, YANG Y, WANG S, et al. Spatial structure of Chinese intercity network based on the data of listed companies. City Planning Review,2017,41(6):18-26.
9	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.地域研究与开发,2018,37(2):9-13.
	ZHAO J, ZHANG L, SONG J. Spatial structure of urban system and its evolution in Jing-Jin-Ji Urban Agglomeration. Areal Research and Development,2018,37(2):9-13.
10	冯长春,谢旦杏,马学广,等.基于城际轨道交通流的珠三角城市区域功能多中心研究.地理科学,2014,34(6):648-655.
	FENG C, XIE D, MA X, et al. Functional polycentricity of the urban region in the Zhujiang River Delta based on intercity rail traffic flow. Scientia Geographical Sinica,2014,34(6):648-655.
11	王姣娥,景悦.中国城市网络等级结构特征及组织模式——基于铁路和航空流的比较.地理学报,2017,72(8):1508-1519.
	WANG J, JING Y. Comparison of spatial structure and organization mode of inter-city networks from the perspective of railway and air passenger flow. Acta Geographica Sinica,2017,72(8):1508-1519.
12	曹子威,罗震东,耿磊.基于信息流的城市-区域关系比较研究——以马鞍山和芜湖为例.经济地理,2013,33(5):47-53.
	CAO Z, LUO Z, GENG L. Information-flow based comparative research of urban-region relations--A case study of Ma'anshan and Wuhu. Economic Geography,2013,33(5):47-53.
13	王宁宁,陈锐,赵宇.基于信息流的互联网信息空间网络分析.地理研究,2016,35(1):137-147.
	WANG N, CHEN R, ZHAO Y. Analysis of the provincial information space network basted on the internet information flow. Geographical Research,2016,35(1):137-147.
14	熊丽芳,甄峰,席广亮,等.我国三大经济区城市网络变化特征——基于百度信息流的实证研究.热带地理,2014,34(1):34-43.
	XIONG L, ZHEN F, XI G, et al. Characteristics of the city network in the three major economic zones of China: A study based on Baidu information flow. Tropical Geography,2014,34(1):34-43.
15	TAYLOR P J. Specification of the world city network. Geographical Analysis, 2001, 33(2): 181-194.
16	GOETZ A R. Air passenger transportation and growth in the US urban system, 1950-1987. Growth and Change, 1992, 23(2): 217-238.
17	MATSUMOTO H. International urban systems and air passenger and cargo flows: Some calculations. Journal of Air Transport Management, 2004, 10(4): 239-247.
18	MAGGIONI M A, NOSVELLI M, UBERTI T E. Space versus networks in the geography of innovation: A European analysis. Papers in Regional Science, 2007, 86(3): 471-493.
19	夏天慈.基于空间流分析的成渝城市群空间结构特征研究//中国城市规划年会.共享与品质——2018中国城市规划年会论文集(16区域规划与城市经济).北京:中国建筑工业出版社,2018:1516-1528.
	XIA T. Research on spatial structure characteristics of Chengdu-Chongqing Urban Agglomeration based on spatial flow analysis//China Urban Planning Annual Conference.Sharing and Quality--Proceedings of the 2018 China Urban Planning Annual Conference (16 Regional Planning and Urban Economy),Beijing:China Architecture & Building Press,2018:1516-1528.
20	冷炳荣,杨永春,李英杰,等.中国城市经济网络结构空间特征及其复杂性分析.地理学报,2011,66(2):199-211.
	LENG B, YANG Y, LI Y, et al. Spatial characteristics and complex analysis:A perspective from basic activities of urban networks in China. Acta Geographica Sinica,2011,66(2):199-211.
21	潘竟虎,赖建波.中国城市间人口流动空间格局的网络分析:以国庆-中秋长假和腾讯迁徙数据为例.地理研究,2019,38(7):1678-1693.
	PAN J, LAI J.Research on spatial pattern of population mobility among cities:A case study of "Tencent Migration"big data in"National Day-Mid-Autumn Festival" vacation.Geographical Research,2019,38(7):1678-1693.
22	夏源,牛强,王兵.基于腾讯迁徙数据的城市群网络结构分析——以京津冀城市群为例//中国城市规划年会.持续发展理性规划——2017中国城市规划年会论文集(16区域规划与城市经济),北京:中国建筑工业出版社,2017:1199-1207.
	XIA Y, NIU Q, WANG B. Analysis of urban agglomeration network structure based on Tencent migration data--Taking the Beijing-Tianjin-Hebei urban agglomeration as an example//China Urban Planning Annual Conference.Sustainable development and Rational planning--Proceedings of the 2017 China Urban Planning Annual Conference (16 Regional Planning and Urban Economy),Beijing:China Architecture & Building Press,2017:1199-1207.
23	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.经济地理,2013,33(7):67-73.
	XIONG L, ZHEN F, WANG B, et al. The research of the Yangtze River Delta core area's city network characteristics based on Baidu index. Economic Geography,2013,33(7):67-73.
24	谭一洺,杨永春,冷炳荣,等.基于高级生产者服务业视角的成渝地区城市网络体系.地理科学进展,2011,30(6):724-732.
	TAN Y, YANG Y, LENG B, et al. Urban network system in Chengdu-Chongqing Region in the perspective of advanced producer service. Progress in Geography,2011,30(6):724-732.
25	黄言,宗会明,杜瑜,等.交通网络建设与成渝城市群一体化发展——基于交通设施网络和需求网络的分析.长江流域资源与环境,2020,29(10):2156-2166.
	HUANG Y, ZONG H, DU Y, et al. Transport network construction and integrated development of Chengdu-Chongqing Urban Agglomeration: A study based on transport infrastructure network and transport demand network. Resources and Environment in the Yangtze Basin,2020,29(10):2156-2166.
26	宗会明,黄言.高速铁路对成渝城市群区域可达性和城市相互作用格局的影响.人文地理,2019,34(3):99-107.
	ZONG H, HUANG Y. The impact of high-speed rail on regional accessibility and regional spatial interaction:A case study of Chengdu-Chongqing Urban Agglomeration. Human Geography,2019,34(3):99-107.
27	黎耕,宗会明.基于铁路交通的成渝城市群功能多中心度研究.西南大学学报(自然科学版),2019,41(2):109-116.
	LI G, ZONG H. Study on multi-centered degree of Chengdu-Chongqing Urban Agglomerations based on railway transportation. Journal of Southwest University(Natural Science Edition),2019,41(2):109-116.
28	宗会明,黄言,胡佯佯.基于多元城际客流的成渝城市群城市网络特征研究.地域研究与开发,2018,37(5):60-65.
	ZONG H, HUANG Y, HU Y. Characteristics of urban networks of Chengdu-Chongqing Urban Agglomeration based on the passengers flow. Areal Research and Development,2018,37(5):60-65.
29	钟海燕,冷玉婷.基于知识图谱的成渝地区双城经济圈研究综述.重庆大学学报(社会科学版),2020,26(4):13-26.
	ZHONG H, LENG Y. Knowledge graph analysis on Chengdu-Chongqing Economic Circle. Journal of Chingqing University(Social Science Edition),2020,26(4):13-26.
30	姚作林,涂建军,牛慧敏,等.成渝经济区城市群空间结构要素特征分析.经济地理,2017,37(1):82-89.
	YAO Z, TU J, NIU H, et al. The research on urban agglomeration spatial structure of Cheng-Yu Economic Zone. Economic Geography,2017,37(1):82-89.
31	朱惠斌.基于航空客流的中国城市功能网络研究.经济地理,2014,34(4):59-63.
	ZHU H. The Chinese city function network based on aviation passenger flow. Economic Geography,2014,34(4):59-63.
32	武前波,宁越敏.中国城市空间网络分析——基于电子信息企业生产网络视角.地理研究,2012,31(2):207-219.
	WU Q, NING Y. China's urban network based on spatial organization of electronic information enterprises. Geographical Research,2012,31(2):207-219.
33	彭翀,林樱子.长株潭网络城市内部关联的时空机制研究.经济地理,2015,35(9):72-78.
	PENG C, LIN Y. Spatial-temporal mechanism of internal correlation in Changsha-Zhuzhou-Xiangtan network cities. Economic Geography,2015,35(9):72-78.
34	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.地理学报,2012,67(8):1031-1043.
	ZHENG F, WANG B, CHEN Y. China's city network characteristics based on social network space: An empirical analysis of sina micro-blog. Acta Geographica Sinica, 2012, 67(8): 1031-1043.
35	蒋大亮,孙烨,任航,等.基于百度指数的长江中游城市群城市网络特征研究.长江流域资源与环境,2015,24(10):1654-1664.
	JIANG D, SUN Y, REN H, et al. Analyses on the city network characteristics of Middle Yangtze Urban Agglomeration based on Baidu index. Resources and Environment in the Yangtze Basin,2015,24(10):1654-1664.
36	孙立新.社会网络分析法:理论与应用.管理学家(学术版),2012(9):66-73.
	SUN L. Social network analysis: Theory and application. Management Scientist(Academic Edition),2012(9):66-73.
37	陈映雪,甄峰,王波,等.基于微博平台的中国城市网络信息不对称关系研究.地球科学进展,2012,27(12):1353-1362.
	CHEN Y, ZHEN F, WANG B, et al. A study of internet information asymmetry relations among Chinese cities based on the micro-blog platform. Advances In Earth Science,2012,27(12):1353-1362.
38	汤放华,汤慧,孙倩,等.长江中游城市集群经济网络结构分析.地理学报,2013,68(10):1357-1366.
	TANG F, TANG H, SUN Q, et al. Analysis of the economic network structure of rban agglomerations in the Middle Yangtze River. Acta Geographica Sinica,2013,68(10):1357-1366.
39	刘军.整体网分析讲义:UCINET软件实用指南.上海:上海人民出版社,2009.
	LIU J. Holistic Net Analysis Lecture Notes: A Practical Guide to UCINET Software . Shanghai: Shanghai People's Publishing House,2009.
40	初楠臣,张平宇,姜博. 基于日高铁流量视角的中国高速铁路网络空间特征.地理研究,2018,37(11):2193-2205.
	CHU N, ZHANG P, JIANG B. Spatial characteristics of Chinese high-speed railway network from the perspective of daily flow. Geographical Research,2018,37(11):2193-2205.
41	黄洁,钟业喜.长江中游城市群铁路客运联系及其空间格局演变.世界地理研究,2016,25(2):72-81.
	HUANG J, ZHONG Y. Evolution of railway passenger traffic linkage and spatial pattern in Yangtze River Middle Reaches Clusters. World Regional Studies,2016,25(2):72-81.
42	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.经济地理,2017,37(8):53-59.
	YE Q, ZHANG L, PENG P,et al. The network characteristics of urban agglomerations in the Middle Reaches of the Yangtze River based on Baidu migration data. Economic Geography,2017,37(8):53-59.

类型	交通流	经济流	人口流	信息流
交通流	—	0.817^***	0.395^***	0.519^***
经济流	0.817^***	—	0.451^***	0.502^***
人口流	0.395^***	0.451^***	—	0.519^***
信息流	0.519^***	0.502^***	0.519^***	—

类型	交通流	经济流	人口流	信息流
交通流	—	0.817^***	0.395^***	0.519^***
经济流	0.817^***	—	0.451^***	0.502^***
人口流	0.395^***	0.451^***	—	0.519^***
信息流	0.519^***	0.502^***	0.519^***	—

类型	网络密度	平均度数	平均路径长度	平均群集系数	网络效率
交通流	0.342	5.125	1.658	0.846	0.752
经济流	0.358	5.375	1.642	0.825	0.733
人口流	0.733	11.000	1.267	0.859	0.305
信息流	0.658	9.875	1.342	0.837	0.391
随机网络	—	—	1.504	0.507	—

类型	网络密度	平均度数	平均路径长度	平均群集系数	网络效率
交通流	0.342	5.125	1.658	0.846	0.752
经济流	0.358	5.375	1.642	0.825	0.733
人口流	0.733	11.000	1.267	0.859	0.305
信息流	0.658	9.875	1.342	0.837	0.391
随机网络	—	—	1.504	0.507	—

城市	度数中心度				接近中心度				中介中心度
城市	交通流	经济流	人口流	信息流	交通流	经济流	人口流	信息流	交通流	经济流	人口流	信息流
成都	1.000	1.000	1.000	1.000	100.000	100.000	100.000	100.000	37.583	43.667	6.416	8.070
重庆	1.000	0.933	0.933	1.000	100.000	93.750	93.750	100.000	37.583	29.667	3.749	8.070
自贡	0.267	0.400	0.667	0.600	57.692	62.500	75.000	71.429	0.000	0.500	0.250	0.435
泸州	0.267	0.333	0.533	0.667	57.692	60.000	68.182	75.000	0.000	0.000	0.000	1.095
德阳	0.200	0.267	0.800	0.600	55.556	57.692	83.333	71.429	0.000	0.333	2.710	0.619
绵阳	0.267	0.333	1.000	1.000	57.692	60.000	100.000	100.000	0.333	0.667	6.416	8.070
遂宁	0.200	0.267	0.667	0.467	55.556	57.692	75.000	65.217	0.000	0.000	0.952	0.000
内江	0.333	0.333	0.867	0.533	60.000	60.000	88.235	68.182	0.667	0.000	2.373	0.600
乐山	0.333	0.333	0.800	0.667	60.000	60.000	83.333	75.000	0.250	0.667	2.087	1.625
南充	0.267	0.333	0.933	0.867	57.692	60.000	93.75	88.235	0.333	0.667	3.749	3.720
眉山	0.267	0.267	0.800	0.400	57.692	57.692	83.333	62.500	0.000	0.333	2.004	0.000
宜宾	0.467	0.400	0.733	1.000	65.217	62.500	78.947	100.000	2.250	0.500	0.504	8.070
广安	0.133	0.200	0.467	0.467	53.571	55.556	65.217	65.217	0.000	0.000	0.143	0.000
达州	0.200	0.133	0.467	0.600	55.556	53.571	65.217	71.429	0.000	0.000	0.143	0.625
雅安	0.133	0.067	0.333	0.333	53.571	51.724	60.000	60.000	0.000	0.000	0.000	0.000
资阳	0.133	0.133	0.733	0.333	53.571	53.571	78.947	60.000	0.000	0.000	0.504	0.000