分频率关联视角下的上海—邻沪地区空间网络特征及机制研究

The Feature and Pattern of the Nested Spatial Structure of Shanghai and Neighboring Cities from the Perspective of High and Low Frequency City Network

许 劼
上海城建职业学院 副教授,博士

王 荻
上海电子信息职业技术学院 副教授,博士

摘要: 结合跨城手机信令和人口数据,区分高频与低频城际出行,运用社会网络分析法比较不同频率关联网络的空间分布特征及上海市的空间分布异质性,通过基于重力模型的泊松回归估算解析分布模式和形成机制,并分析不同频度、不同空间层面的关联网络嵌套对邻沪地区一体化发展的影响。研究发现,高、低频关联网络嵌套重叠部分的边界效应和低频关联的蔓延加飞地特征,城际与市域关联网络叠合形成多层嵌套式空间结构;城际关联符合泊松分布模式;高、低频重叠区块具备一体化发展物质空间条件,上海市新城具有衔接作用,以期为区域一体化发展政策提供依据。

Abstract: This study aims to contrast the spatial distribution of the high-frequency and low-frequency city networks using mobile signaling and census data. The mechanism is explored based on the Poisson regression. The impact of the city network on regional integration is revealed. The results show that both high and low frequency city networks are densely distributed around the administrative boundaries. Secondly, the trips conform to a Poisson distribution. The high-frequency trips are very sensitive to distance, restraining the spatial scope, whereas the low-frequency trips are supported by regional transportation facilities. Lastly, the overlaid high-frequency and low-frequency networks lay the foundation for integration development. The conclusions provide implications for the integration policies such as the Yangtze Delta Region Demonstration Area.

关键词:关联网络;高频率出行;低频率出行;上海—邻沪地区

Keyword: city network; high-frequency trip; low-frequency trip; Shanghai and neighboring cities

中图分类号:TU984

文献标识码: A

资金资助

教育部人文社科青年课题 城际高铁对上海都市圈空间和经济布局的影响和机制研究——基于公路的对比 22YJCZH207

崇明区博士后创新实践基地项目(上海林同炎李国豪土建工程咨询有限公司) 人流活动的空间分布规律和形成机制

国务院. 长江三角洲区域一体化发展规划纲要[Z]. 2019.
The State Council. The guidelines for integration development of the Yangtze River Delta[Z]. 2019.
国务院. 国务院关于上海市城市总体规划的批复(国函〔2017〕147号)[Z]. 2017.
The State Council. The approval of Shanghai Master Plan[Z]. 2017.
CASTELLS M. Grassrooting the space of flows[J]. Urban Geography, 1999, 20(4): 294-302.
TAYLOR P, HOYLER M, VERBRUGGEN R. External urban relational process: introducing central flow theory to complement central place theory[J]. Urban Studies, 2010, 47: 2803-2818.
TAYLOR P. Specification of the world city network[J]. Geographical Analysis, 2001, 33: 181-194.
王德,刘锴,耿慧志. 沪宁杭地区城市一日交流圈的划分与研究[J]. 城市规划汇刊,2001(5):38-44.
WANG De, LIU Kai, GENG Huizhi. The study of daily communication area in Hu-Ning-Hang Region[J]. Urban Planning Forum, 2001(5): 38-44.
王德,刘锴,郭洁. 沪宁杭三市一日交流圈的空间特征及其比较[J]. 城市规划汇刊,2004(3):33-38.
WANG De, LIU Kai, GUO Jie. The Comparison of Spatial Characteristics and Dynamic Changes of Daily-Communication-Areas of Hu-Ning-Hang[J]. Urban Planning Forum, 2004(3): 33-38.
刘美华,罗守贵. 基于潜力模型的上海都市圈城市等级划分[J]. 安徽农业科学,2008,36(9):3903-3904.
LIU Meihua, LUO Shougui. Classification of Shanghai metropolitan coordinating area hierarchy based on potential model[J]. Journal of Anhui Agriculture Science, 2008, 36(9): 3903-3904.
张萍,张玉鑫. 上海大都市区空间范围研究[J]. 城市规划学刊,2013(4):27-32.
ZHANG Ping, ZHANG Yuxin. A study on the spatial extent of Shanghai metropolitan area[J]. Urban Planning Forum, 2013(4): 27-32.
Office of Management and Budget. Standards for delineating metropolitan and micropolitan statistical areas[Z]. 2010.
Office for National Statistics. Travel to work area analysis in Great Britain[Z]. 2010.
KANASUGI H, USHIJIMA K. The impact of a high-speed railway on residential land prices[J]. Papers in Regional Science, 2018, 97(4): 1305-1335.
UREÑA J, MENERAULTB P, GARMENDIA M. The high-speed rail challenge for big intermediate cities: a national, regional and local perspective[J]. Cities, 2009, 26: 266-279.
武前波,陶娇娇,吴康,等. 长江三角洲高铁日常通勤行为特征研究——以沪杭、宁杭、杭甬线为例[J]. 城市规划,2018,42(8):90-97.
WU Qianbo, TAO Jiaojiao, WU Kang, et al. Daily commuting behavior characteristics of high speed rail passengers in the Yangtze River Delta Region: a case study of Shanghai-Hangzhou, Nanjing-Hangzhou, and Hangzhou-Ningbo Lines[J]. City Planning Review, 2018, 42(8): 90-97.
朱鹏程,曹卫东,张宇,等. 人口流动视角下长三角城市空间网络测度及腹地划分[J]. 经济地理,2019,39(11):41-48.
ZHU Pengcheng, CAO Weidong, ZHANG Yu, et al. Measurement of urban spatial network and its hinterworld division in the Yangtze River Delta from the perspective of population flow[J]. Economic Geography, 2019, 39(11): 41-48.
王启轩,张艺帅,程遥. 信息流视角下长三角城市群空间组织辨析及其规划启示[J]. 城市规划学刊,2018(3):105-112.
WANG Qixuan, ZHANG Yishuai, CHENG Yao. Spatial organization of the Yangtze River Delta urban agglomeration and its implications on planning from the perspective of information flow: analysis of city network based on Baidu Index[J]. Urban Planning Forum, 2018(3): 105-112.
郑德高,朱郁郁,陈阳,等. 上海大都市圈的圈层结构与功能网络研究[J]. 城市规划学刊,2017(s2):63-71.
ZHENG Degao, ZHU Yuyu, CHEN Yang, et al. Structure and functional network of Shanghai metropolitan[J]. Urban Planning Forum, 2017(s2): 63-71.
王垚,钮心毅,宋小冬. 基于城际出行的长三角城市群空间组织特征[J]. 城市规划,2021,45(11):43-53.
WANG Yao, NIU Xinyi, SONG Xiaodong. Spatial organizational characteristics of the Yangtze River Delta urban agglomeration based on intercity trips[J]. City Planning Review, 2021, 45(11): 43-53.
田琳. 基于迁徙数据的上海都市圈跨城联系特征研究[C]//2020年第十六届中国城市规划信息化年会暨中国城市规划学会城市规划新技术应用学术委员会年会,2020.
TIAN Lin. Characterization of cross-city linkages in the Shanghai metropolitan area based on migration data[C]//The 16th Annual China Urban Planning Informatization Conference, 2020.
钮心毅,李凯克. 跨城功能联系视角下的都市圈国土空间规划实施监测[J]. 资源科学,2021,43(2):380-389.
NIU Xinyi, LI Kaike. Implementation monitoring of territorial and spatial planning in metropolitan areas from the perspective of intercity functional linkages[J]. Resources Science, 2021, 43(2): 380-389.
蒋凯,昝骁毓,李政寰. 城镇体系识别及空间结构特征比较——以北京、上海、东京都市圈为例[J]. 城市发展研究,2020,27(4):55-61.
JIANG Kai, ZAN Xiaoyu, LI Zhenghuan. Identification of urban system and comparison of spatial structure characteristics: a case study of Beijing, Shanghai and Tokyo Metropolitan Areas[J]. Urban Development Studies, 2020, 27(4): 55-61.
程遥,张艺帅,赵民. 长三角城市群的空间组织特征与规划取向探讨——基于企业联系的实证研究[J]. 城市规划学刊,2016(4):22-29.
CHENG Yao, ZHANG Yishuai, ZHAO Min. The spatial self-organization and planning agendas of the Yangtze River Delta's city cluster: spatial analysis based on enterprise connectivity[J]. Urban Planning Forum, 2016(4): 22-29.
刘雯婷,左桐祯,李冰夷,等. 全球功能流动视角下上海都市圈网络空间特征——基于国际手机漫游数据的实证[J]. 城市建筑,2021,18(10):14-16.
LIU Wenting, ZUO Tongzhen, LI Bingyi, et al. Spatial characteristics of Shanghai metropolitan area from the perspective of global function flow[J]. Urbanism and Architecture, 2021, 18(10): 14-16.
王德,顾家焕,晏龙旭. 上海都市区边界划分[J]. 地理学报,2018,73(10):1896-1909.
WANG De, GU Jiahuan, YAN Longxu. Delimiting the Shanghai metropolitan area using mobile phone data[J]. Acta Geographica Sinica, 2018, 73(10): 1896-1909.
钮心毅,李凯克. 紧密一日交流圈视角下上海都市圈的跨城功能联系[J]. 上海城市规划,2019(3):16-22.
NIU Xinyi, LI Kaike. Inter-city functional linkages in Shanghai metropolitan region from the perspective of close daily communication area[J]. Shanghai Urban Planning Review, 2019(3): 16-22.
李峰清. 基于高铁网络的我国城镇化空间模式再探[J]. 城市规划,2018,42(3):109-117.
LI Fengqing. Re-exploring the spatial model of urbanization in China based on high-speed rail network: inspection an analysis of Shanghai-Hinterland of Yangtze River Delta[J]. City Planning Review, 2018, 42(3): 109-117.
钮心毅,王垚,刘嘉伟,等. 基于跨城功能联系的上海都市圈空间结构研究[J]. 城市规划学刊,2018(5):80-87.
NIU Xinyi, WANG Yao, LIU Jiawei, et al. Spatial structure of Shanghai conurbation area from perspective of inter-city functional links[J]. Urban Planning Forum, 2018(5): 80-87.
焦利民,龚晨,许刚,等. 大都市区城市扩张过程及形态对比分析——以东京、纽约和上海为例[J]. 地理科学进展,2019,38(5):675-685.
JIAO Limin, GONG Chen, XU Gang, et al. Urban expansion dynamics and urban forms in three metropolitan areas: Tokyo, New York, and Shanghai[J]. Progress in Geography, 2019, 38(5): 675-685.
SCOTT A J. Social network analysis[M]. London: Sage Publication Inc, 2000.
TAYLOR P J. Urban hinterworlds: geographies of corporate service provision under conditions of contemporary globalization[J]. Geography, 2001, 86(1): 51-60.
DE GOEI B, BURGER M, VANOORT F, et al. Functional polycentrism and u rban network development in the Greater South East, United Kingdom: evidence from commuting patterns, 1981-2001[J]. Regional Studies, 2010, 44(9): 1149-1170.
FLOWERDEW R, AITKIN M. A method of fitting the gravity model based on the Poisson distribution[J]. Journal of Regional Science, 1982, 22: 191-202. 
LONG J. Regression models for categorical and limited dependent variables[M]. Thousand Oaks, CA: Sage, 1997.
ARVIS J, SHEPHERD B. The Poisson quasi-maximum likelihood estimator: a solution to the 'adding up' problem in gravity models[J]. Applied Economics Letters, 2013, 20(6): 515-519.
杨超,陈明垟,袁泉,等. 上海市新城通勤人群出行特征分析[J]. 城市交通,2022(2):99-110.
YANG Chao, CHEN Mingyang, YUAN Quan, et al. Travel characteristics of commuters living in Shanghai new towns[J]. Urban Transport of China, 2022(2): 99-110.
张天然,王波,訾海波,等. 上海五个新城职住空间特征对比研究[J]. 上海城市规划,2021(4):44-52.
ZHANG Tianran, WANG Bo, ZI Haibo, et al. A comparative study on the spatial characteristics of job-housing in five new towns in Shanghai[J]. Shanghai Urban Planning Review, 2021(4): 44-52.
张月朋,王德. 上海市早高峰出行问题源头区识别[J]. 城市规划,2021,45(7):83-90.
ZHANG Yuepeng, WANG De. Identification of the source of morning peak-hour traffic congestion in Shanghai[J]. City Planning Review, 2021, 45(7): 83-90. 
XIAO Y, WANG Y, MIAO S, et al. Assessing polycentric urban development in Shanghai, China, with detailed passive mobile phone data[J]. Environment and Planning B: Planning and Design, 2020, 48(9): 2656-2674.
王荻. 中心城市城际高铁人流分布与城市群发展研究——以长三角核心区为例[D]. 上海:复旦大学,2022.
WANG Di. The impact of city-cluster high-speed rail passenger flow from the central city on the development of mega-regions: evidence from the core area of the Yangtze River Delta[D]. Shanghai: Fudan University, 2022.
李志鹏. 基于居民活动的上海空间结构网络特征研究[C]//面向高质量发展的空间治理——2021中国城市规划年会论文集. 北京:中国建筑工业出版社,2021.
LI Zhipeng. The spatial network features of Shanghai based on residents' mobility[C]//High-quality spatial governance: proceedings of 2021 China Annual National Planning Conference. Beijing: China Architecture & Building Press, 2021.

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