基于人口流的中国省域城镇化空间关联特征及形成机制
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摘要
空间关联是区域相互作用和影响的纽带,以人口流动为载体的城镇化空间关联影响并不断调整着中国区域经济社会发展格局。根据省际人口流动数据,构建城镇化空间关联模型,通过分析1990-2015年中国省域城镇化空间关联强度与关联网络结构变化,揭示城镇化空间关联特征及形成机制。结果发现:①中国省域城镇化空间关联强度演变过程可以解析出7种类型,其中主导类型与全国的吻合程度最高,并决定着全国城镇化空间关联强度演变过程;非主导类型的城镇化空间关联强度演变特征以2005年为界,之前增长缓慢甚至为负,之后与主导类型共同推动全国城镇化空间关联强度持续增长。②对城镇化空间关联进行不同尺度的结构分析,全国城镇化空间关联网络结构日趋复杂,关联路径由集中转向分散,不同属性的地域子群间关联密度差异开始缩小,高等级节点由东部向中西部扩散。③采用面板向量自回归和面板分位数回归检验城镇化空间关联强度与关联网络中心度的互动机制,并解释了居民收入水平和区域产业结构对城镇化空间关联特征的影响方式。城镇化空间关联不仅深化了城镇化的研究,也为中国人口城镇化发展和产业空间转移调控提供理论依据。
Spatial correlation is the link of regional interaction and influence; the urbanization spatial correlation is spatial relationship of urbanization based on population flow, which influences and continuously adjusts the regional economic and social development pattern in China. By analyzing the change of the spatial correlation intensity and the spatial correlation network of provincial urbanization in China during 1990-2015, this paper reveals the spatial correlation characteristics, formation process and influencing factors of China's provincial urbanization since China's reform and opening up. The results show that:(1) 7 types of spatial correlation intensity are identified in the evolution of provincial urbanization of China, among which the dominant type has the highest degree of coincidence with the whole country, and determines the evolution process of the spatial correlation intensity of urbanization in China.The non-dominant types of urbanization spatial correlation intensity evolution feature 2005 as the critical year, and their growth was slow or even negative before the year; then together with the dominant type, they have promoted a continuous increase in the urbanization spatial correlation intensity across the country.(2) Urbanization spatial correlation network structure characteristics are analyzed from national, regional and provincial scales. The structure of the spatial correlation network of urbanization is becoming more and more complicated, and the correlation paths have shifted from centralized to scattered. The differences in the correlation density between regional subgroups with different attributes have begun to shrink, and the highlevel nodes have spread from the eastern to the central and western regions.(3) Further, the panel-vector auto-regression and panel quantile regression are used to test the interaction mechanism between urbanization spatial correlation intensity and correlation network centrality, which explains the effect of residents' income level and regional industrial structure on urbanization spatial correlation characteristics. The specialization of urbanization spatial correlation not only deepens the research on urbanization theory and methodology, but also provides a theoretical basis for the development of population urbanization and the adjustment of industrial space in China.
Spatial correlation is the link of regional interaction and influence; the urbanization spatial correlation is spatial relationship of urbanization based on population flow, which influences and continuously adjusts the regional economic and social development pattern in China. By analyzing the change of the spatial correlation intensity and the spatial correlation network of provincial urbanization in China during 1990-2015, this paper reveals the spatial correlation characteristics, formation process and influencing factors of China's provincial urbanization since China's reform and opening up. The results show that:(1) 7 types of spatial correlation intensity are identified in the evolution of provincial urbanization of China, among which the dominant type has the highest degree of coincidence with the whole country, and determines the evolution process of the spatial correlation intensity of urbanization in China.The non-dominant types of urbanization spatial correlation intensity evolution feature 2005 as the critical year, and their growth was slow or even negative before the year; then together with the dominant type, they have promoted a continuous increase in the urbanization spatial correlation intensity across the country.(2) Urbanization spatial correlation network structure characteristics are analyzed from national, regional and provincial scales. The structure of the spatial correlation network of urbanization is becoming more and more complicated, and the correlation paths have shifted from centralized to scattered. The differences in the correlation density between regional subgroups with different attributes have begun to shrink, and the highlevel nodes have spread from the eastern to the central and western regions.(3) Further, the panel-vector auto-regression and panel quantile regression are used to test the interaction mechanism between urbanization spatial correlation intensity and correlation network centrality, which explains the effect of residents' income level and regional industrial structure on urbanization spatial correlation characteristics. The specialization of urbanization spatial correlation not only deepens the research on urbanization theory and methodology, but also provides a theoretical basis for the development of population urbanization and the adjustment of industrial space in China.
引文
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[14]Jacobs W,Koster H,Hall P.The location and global network structure of maritime advanced producer services.Urban Studies,2011,48(13):2749-2769.
[15]Xiulian M,Timberlake M F.Identifying China's leading world city:A network approach.GeoJournal,2008,71(1):19-35.
[16]Neal Z.Differentiating centrality and power in the World City Network.Urban Studies,2011,48(13):2733-2748.
[17]Boyd J P,Mahutga M C,Smith D A.Measuring centrality and power recursively in the World City Network:A reply to Neal.Urban Studies,2013,50(8):1641-1647.
[18]Meijers E J,Burger M J,Hoogerbrugge M M.Borrowing size in networks of cities:City size,network connectivity and metropolitan functions in Europe.Papers in Regional Science,2016,95(1):181-198.
[19]Ducruet C,Cuyala S,Hosni A E.Maritime networks as systems of cities:The long-term interdependencies between global shipping flows and urban development(1890-2010).Journal of Transport Geography,2018,66:340-355.
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[21]Wang Zhao,Yang Shan,Gong Fuhua et al.Identification of urban agglomerations deformation structure based on urbanflow space:A case study of the Yangtze River Delta urban agglomeration.Scientia Geographica Sinica,2017,37(9):1337-1344.[王钊,杨山,龚富华,等.基于城市流空间的城市群变形结构识别:以长江三角洲城市群为例.地理科学,2017,37(9):1337-1344.]
[22]Li Chen,Jin Xiangmu.Measurement of spatial interaction between central towns based on the gravity model.Scientia Geographica Sinica,2016,36(5):724-732.[李陈,靳相木.基于引力模型的中心镇空间联系测度研究:以浙江省金华市25个中心镇为例.地理科学,2016,36(5):724-732.]
[23]Chen Wei,Liu Weidong,Ke Wenqian,et al.The spatial structures and organization patterns of China's city networks based on the highway passenger flows.Acta Geographica Sinica,2017,72(2):224-241.[陈伟,刘卫东,柯文前,等.基于公路客流的中国城市网络结构与空间组织模式.地理学报,2017,72(2):224-241.]
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[25]Zhao Ziyu,Wei Ye,Pang Ruiqiu,et al.Alter-based centrality and power of Chinese city network using inter-provincial population flow.Acta Geographica Sinica,2017,72(6):1032-1048.[赵梓渝,魏冶,庞瑞秋,等.基于人口省际流动的中国城市网络转变中心性与控制力研究:兼论递归理论用于城市网络研究的条件性.地理学报,2017,72(6):1032-1048.]
[26]Zhao Ziyu,Wei Ye,Wang Shijun,et al.Measurement of directed alternative centricity and power of directed weighted urban network:A case of population flow network of China during"Chunyun"period.Geographical Research,2017,36(4):647-660.[赵梓渝,魏冶,王士君,等.有向加权城市网络的转变中心性与控制力测度:以中国春运人口流动网络为例.地理研究,2017,36(4):647-660.]
[27]Wang Cheng,Wang Maojun,Chai Qing.The relationship between centrality and power in the city network.Acta Geographica Sinica,2015,70(12):1953-1972.[王成,王茂军,柴箐.城市网络地位与网络权力的关系:以中国汽车零部件交易链接网络为例.地理学报,2015,70(12):1953-1972.]
[28]Cao Zhan,Peng Zhenwei.Correlation between"Attributes and Network"of global city and global city-region:A case of Shanghai and Yangtze River Delta.Economic Geography,2017,37(5):1-11.[曹湛,彭震伟.全球城市与全球城市-区域“属性与网络”的关联性:以上海和长三角为例.经济地理,2017,37(5):1-11.]
[29]Wu Kang,Fang Chuanglin,Zhao Miaoxi.The spatial organization and structure complexity of Chinese intercity networks.Geographical Research,2015,35(4):711-728.[吴康,方创琳,赵渺希.中国城市网络的空间组织及其复杂性结构特征.地理研究,2015,35(4):711-728.]
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