侯静轩 张恩嘉 龙瀛

Hou Jingxuan, Zhang Enjia, Long Ying

关键词：网络科学；尺度；空间分析；空间网络；流网络；二分网络；流类型

Keywords：Network Science; Scale; Spatial Analysis; Spatial Network; Flow Network; Bipartite Networks; Flow Type

摘要：

目前越来越多的城市研究者开始以网络科学的视角研究城市空间。本研究通过梳理已有城市空间网络研究，将相关研究分为区域、城市与人本三个研究尺度，并分析了“尺度”这一网络研究中的重要元素在研究方法与研究内容方面产生的作用与影响。研究方法方面，所研究空间尺度越大，网络化过程中对空间的抽象程度越高，越侧重于测度网络整体特征；所研究空间尺度越小，使用的空间模型则越精细，常聚焦于分析节点在网络中的地位。研究内容方面，较大尺度研究中针对的流类型更多且涉及动态网络研究，但主要倾向于刻画网络现象；而较小尺度研究中已较多开展流网络与空间网络作用方式的研究。此外，本文展望了未来多尺度城市空间网络研究可能的研究方法与研究内容，试图挖掘网络科学视角下多尺度城市研究的机遇，从而为城市研究提供新的视角和参考。

Abstract：

Recently, there are a growing number of scholars studying cities from the perspective of networks. This research reviews exiting studies by dividing them into three categories to reveal the spatial scale effects on study methods and contents of urban spatial networks. From the perspective of the study method, researchers prefer the highly abstract spatial network and measuring the fundamental characteristics of the network for large-scale studies. In contrast, the fine spatial model is usually applied at fine-scale explorations to reveal some nodes’ roles in the whole network. As for the study focus, various types of flows and their dynamics are depicted to interpret some spatial phenomena at larger scales, and the interaction between flow and spatial network is the main theme in fine-scale studies. Moreover, this paper tries to show the opportunities of the future multiscale urban research by prospecting its possible analytic methods and contents, and to provide a new perspective and reference for urban studies.

侯静轩，清华大学建筑学院，博士研究生。houjx19@mails.tsinghua.edu.cn

张恩嘉，清华大学建筑学院，博士研究生。zej18@mails.tsinghua.edu.cn

龙瀛（通信作者），清华大学建筑学院、清华大学恒隆房地产研究中心，研究员、博士生导师；中国城市规划学会城市规划新技术应用学术委员会，副主任委员。ylong@tsinghua.edu.cn

• [1] CASTELLS M. The rise of the network society (the information age): economy, society and culture[M]. New Jersey: Wiley-Blackwell, 1996.

  [2] BATTY M. The new science of cities[M]. Cambridge, MA: The MIT Press, 2013.

  [3] BETTENCOURT L M A, LOBO J, HELBING D, et al. Growth, innovation, scaling, and the pace of life in cities[J]. Proceedings of the National Academy of Sciences of the United States of America, 2007, 104(17): 7301-7306.

  [4] DERUDDER B, WITLOX F. An appraisal of the use of airline data in assessing the world city network: a research note on data[J]. Urban studies, 2005, 42(13): 2371-2388.

  [5] SCHLAEPFER M, BETTENCOURT L M A, GRAUWIN S, et al. The scaling of human interactions with city size[J]. Journal of the Royal Society interface, 2014, 11(98): 20130789.

  [6] LOBO J, ALBERTI M, ALLEN-DUMASA M, et al. Urban science: integrated theory from the first cities to sustainable metropolises[R/OL]. (2020-01-28)[2021-05-01]. http://dx.doi.org/10.2139/ssrn.3526940.

  [7] RYBSKI D, ARCAUTE E, BATTY M. Urban scaling laws[J]. Environment and planning b: urban analytics and city science, 2019, 46(9): 1605-1610.

  [8] BATTY M. The size, scale, and shape of cities[J]. Science, 2008, 319(5864): 769-771.

  [9] 魏冶, 修春亮. 城市网络韧性的概念与分析框架探析[J]. 地理科学进展, 2020, 39(3): 488-502.

  [10] 彭翀, 林樱子, 顾朝林. 长江中游城市网络结构韧性评估及其优化策略[J]. 地理研究, 2018, 37(6): 1193-1207.

  [11] WEST G. Scale: the universal laws of growth, innovation, sustainability, and the pace of life in organisms, cities, economies, and companies[M]. New York: Penguin Press, 2017.

  [12] MANDELBROT B. The fractal geometry of nature[M]. San Francisco, CA: W. H. Freeman, 1982.

  [13] BATTY M. Inventing future cities[M]. Cambridge, MA: The MIT Press, 2018.

  [14] BATTY M. On scale and size[J]. Environment and planning b: urban analytics and city science, 2020, 47(3): 359-362.

  [15] 杨滔. 空间句法：基于空间形态的城市规划管理[J]. 城市规划, 2017, 41(2): 27-32.

  [16] BATTY M, LONGLEY P A. Fractal cities: a geometry of form and function[M]. San Diego, CA: Academic Press, 1994.

  [17] 李涛, 程遥, 张伊娜, 等. 城市网络研究的理论、方法与实践[J]. 城市规划学刊, 2017 (6): 43-49.

  [18] 潘峰华, 方成, 李仙德. 中国城市网络研究评述与展望[J]. 地理科学, 2019, 39(7): 1093-1101.

  [19] 杨延杰, 尹丹, 刘紫玟, 等. 基于大数据的流空间研究进展[J]. 地理科学进展, 2020, 39(8): 1397-1411.

  [20] BARABASI A L. Network science[M]. Cambridge: Cambridge University Press, 2016.

  [21] MAHUTAGA M C, MA X, SMITH D A, et al. Economic globalisation and the structure of the world city system: the case of airline passenger data[J]. Urban studies, 2010, 47(9): 1925-1947.

  [22] SALAT S. Cities and forms[M]. Paris, France: Editions Hermann, 2011.

  [23] 黄蔚欣, 张宇, 吴明柏, 等. 基于WiFi 定位的智慧景区游客行为研究——以黄山风景名胜区为例[J]. 中国园林, 2018, 34(3): 25-31.

  [24] BIANCONI G. Multilayer networks: structure and function[M]. Oxford: Oxford University Press, 2018.

  [25] BOCCALETTI S, BIANCONI G, CRIADO R, et al. The structure and dynamics of multilayer networks[J]. Physics reports, 2014, 544(1): 1-122.

  [26] KIVEL? M, ARENAS A, BARTHELEMY M, et al. Multilayer networks[J]. Journal of complex networks, 2014, 2(3): 203-271.

  [27] 盛强, 杨滔, 侯静轩. 连续运动与超链接机制——基于重庆地面及地铁交通流量数据的大尺度范围空间句法实证分析[J]. 西部人居环境学刊, 2015, 30(5): 16-21.

  [28] HAGGETT P, CLIFF A D, FREY A. Locational analysis in human geography[M]. New York: Wiley, 1977.

  [29] NEAL Z. The connected city: how networks are shaping the modern metropolis[M]. New York: Routledge, 2013.

  [30] BARTHELEMY M. The structure and dynamics of cities: urban data analysis and theoretical modeling[M]. Cambridge: Cambridge University Press, 2017.

  [31] 马学广, 赵彩霞. 中国城市网络格局阶层与布局: 航空客运流的实证[J]. 城市发展研究, 2020, 27(9): 66-71, 81.

  [32] 王启轩, 张艺帅. 广东省域城市网络的“核心—边缘”结构再解读——基于“流动空间”视角的实证研究[J]. 上海城市规划, 2020(4): 84-90.

  [33] 王均瑶, 宋崴, 刘彤起. 基于多元“流”数据的吉林省城市研究[J]. 规划师, 2020, 36( 增刊2): 64-68.

  [34] 闫闪闪, 靳诚. 洛阳城区旅游流空间网络结构特征[J]. 地理科学, 2019, 39(10): 1602-1611.

  [35] 田深圳, 李守伟, 李雪铭. 我国滨海城市网络时空格局研究——基于2012—2019 年百度指数数据[J]. 城市问题, 2020(8): 14-21.

  [36] 李帅, 彭震伟. 信息流视角下的成渝城市群空间组织特征及其规划探讨——基于百度指数的城市网络研究[J]. 西部人居环境学刊, 2020,35(6): 49-57.

  [37] 周慧玲, 许春晓. 中国城市旅游信息流空间网络结构特征分析[J]. 统计与决策, 2019, 35(20): 91-94.

  [38] HU X, SHEN P, SHI Y, et al. Using Wi-Fi probe and location data to analyze the human distribution characteristics of green spaces: a case study of the Yanfu Greenland Park, China[J]. Urban forestry & urban greening, 2020, 54: 126733.

  [39] 黄洁, 杜德林, 王姣娥, 等. 基于城市群尺度的高铁列车与长途汽车网络结构比较[J]. 地理科学, 2020, 40(12): 1958-1966.

  [40] 孙继平, 侯兰功. 基于腾讯人口迁徙数据的成渝城市群网络结构特征研究[J]. 现代城市研究, 2020(9): 78-85.

  [41] 钱肖颖, 孙斌栋. 基于城际创业投资联系的中国城市和组织模式[J]. 地理研究, 2021, 40(2): 419-430.

  [42] HILLIER B, LEAMAN P, STANSALL P, et al. Space syntax[J]. Environment and planning b: urban analytics and city science, 1976, 3(2): 147-185.

  [43] BAFNA S. Space syntax: a brief introduction to its logic and analytical techniques[J]. Environment and behavior, 2003, 35(1): 17-29.

  [44] HILLIER B, MAJOR M, DESYLLAS J, et al. A study of the existing layout and new masterplan proposal[M]. London: Tate Gallery, Millbank, 1996.

  [45] 杨滔. 城市几何设计：空间句法的阐释[J]. 城市设计, 2019(4): 42-51.

  [46] DESYLLAS J, DUXBURY E. Axial maps and visibility analysis: a comparison of their methodology and use in models of urban pedestrian movement[C] // Proceedings, Third International Symposium on Space Syntax. Atlanta, 2001, 27: 1-13.

  [47] ERICSON J, CHRASTIL E, WARREN W. Space syntax visibility graph analysis is not robust to changes in spatial and temporal resolution[J/OL]. Environment & planning b. (2020-01-20)[2021-05-01]. DOI: 10.1177/2399808319897624.

  [48] ZHEN F, CAO Y, QIN X, et al. Delineation of an urban agglomeration boundary based on Sina Weibo microblog ‘check-in’ data: a case study of the Yangtze River Delta[J]. Cities, 2017, 60: 180-191.

  [49] PAN J, LAI J. Spatial pattern of population mobility among cities in China: case study of the National Day plus Mid-Autumn Festival based on Tencent migration data[J]. Cities, 2019, 94: 55-69.

  [50] ROTH C, KANG S M, BATTY M, et al. Structure of urban movements: polycentric activity and entangled hierarchical flows[J]. PLoS one, 2011, 6(1): e15923.

  [51] SHEN Y, BATTY M. Delineating the perceived functional regions of London from commuting flows[J]. Environment and planning a: economy and space, 2019, 51(3): 547-550.

  [52] LIN Y. E-urbanism: e-commerce, migration, and the transformation of Taobao villages in urban China[J]. Cities, 2019, 91: 202-212.

  [53] 武善梅, 王艳东, 乔梦玲, 等. 利用社交媒体数据探测细粒度城市子区域[J]. 地理空间信息, 2020, 18(9): 122-125.

  [54] 甘田, 刘鼎. 基于手机数据的职住空间关系研究——以重庆市主城区为例[J]. 城市交通, 2020, 18(5): 36-44, 119.

  [55] SHEN Y, KARIMI K, LAW S, et al. Physical co-presence intensity: measuring dynamic face-to-face interaction potential in public space using social media check-in records[J]. PLoS one, 2019, 14(2): e0212004.

  [56] 龙瀛, 叶宇. 人本尺度城市形态：测度、效应评估及规划设计响应[J]. 南方建筑, 2016(5): 41-47.

  [57] LONG Y, YE Y. Measuring human-scale urban form and its performance[J]. Landscape and urban planning, 2019, 191: 103612.

  [58] LAMBIOTTE R, SINATRA R, DELVENNE J C, et al. Flow graphs: interweaving dynamic and structure[J]. Physical review e: statistical, nonlinear, and soft matter physics, 2011, 84: 017102.

  [59] OMER I, KAPLAN N. Structural properties of the angular and metric street network’s centralities and their implications for movement flows[J]. Environment and planning b: urban analytics and city science, 2019, 46(6): 1182-1200.

  [60] XU J, ZHANG M, ZHANG X, et al. How does city-cluster high-speed rail facilitate regional integration? evidence from the Shanghai-Nanjing corridor[J]. Cities, 2019, 85: 83-97.

  [61] KHIALI-MIAB A, VAN STRIEN M J, AXHAUSEN K W, et al. Combining urban scaling and polycentricity to explain socio-economic status of urban regions[J]. PLoS one, 2019, 14(6): e0218022.

  [62] ZHEN F, QIN X, YE X, et al. Analyzing urban development patterns based on the flow analysis method[J]. Cities, 2019, 86(1): 78-97.

  [63] GEHL J, GEMZ?E L. Public spaces-public life[M]. Copenhagen: Danish Architectural Press, 1996.

  [64] 王垚, 钮心毅. 长江三角洲城市群核心区的功能多中心特征和规划响应——基于城际出行联系的研究[J/OL]. 国际城市规划. (2020-05-11)[2021-02-03]. http://kns.cnki.net/kcms/detail/11.5583.TU.20200722.1127.003.html.

  [65] SEROK N, LEVY O, HAVLIN S, et al. Unveiling the inter-relations between the urban streets network and its dynamic traffic flows: planning implication[J]. Environment and planning b: urban analytics and city science, 2019, 46(7): 1362-1376.

  [66] MATYUS T, SEER S, SCHROM-FEIERTAG H. Simulation-based forecasts of crowd flows at major events using real-time measurements[C] // Traffic and Granular Flow’ 15. Cham: Springer, 2016: 329-336.

  [67] SHI S, PAIN K. Investigating china’s Mid-Yangtze River economic growth region using a spatial network growth model[J]. Urban studies, 2020, 57(14): 2973-2993.

  [68] LAROTTA S, SILVA P. A gravity model analysis of determinants of international migration from Colombia 1990-2015[J]. Territorios, 2019, 41: 69-100.

  [69] SIERRA-PAYCHA C. The remigration of immigrants in Spain. beyond distance and pull factors: the migratory network effect (2007-2014)[J]. Territorios, 2019, 41: 45-68.

  [70] SALDARRIAGA J F, HUA Y. A gravity model analysis of forced displacement in Colombia[J]. Cities, 2019, 95: 102407.

  [71] RAIMBAULT J. Indirect evidence of network effects in a system of cities[J]. Environment and planning b: urban analytics and city science, 2020, 47(1): 138-155.

  [72] YANG H, DIJST M, WITTE P, et al. Comparing passenger flow and time schedule data to analyse high-speed railways and urban networks in China[J]. Urban studies, 2019, 56(6): 1267-1287.

  [73] WANG S, WANG J, LIU X. How do urban spatial structures evolution in the high-speed rail era? case study of Yangtze River Delta, China[J]. Habitat international, 2019, 93: 102051.

  [74] 周慧玲, 王甫园. 基于修正引力模型的中国省际旅游者流空间网络结构特征[J]. 地理研究, 2020, 39(3): 669-681.

  [75] GOREMYKO M V, MAKAROV V V, HRAMOV A E, et al. Betweenness centrality in urban networks: revealing the transportation backbone of the country from the demographic data[C] // IOP Conference Series: Earth and Environmental Science, 2018, 177: 012017.

  [76] ALKHEDER S, ABDULLAH W A A, AL-RUKAIBI F, et al. Mobility patterns for newly proposed metro system in Kuwait[J]. Journal of urban planning and development, 2020, 146(1): 04019020.

  [77] OSORIO-ARJONA J, GARCIA-PALOMARES J C. Social media and urban mobility: using Twitter to calculate home-work travel matrices[J]. Cities, 2019, 89: 268-280.

  [78] LIU Z, WANG S, WANG F. Isolated or integrated? planning and management of urban renewal for historic areas in old Beijing city, based on the association network system[J]. Habitat international, 2019, 93: 102049.

  [79] ZHANG P, ZHOU J, ZHANG T. Quantifying and visualizing jobs-housing balance with big data: a case study of Shanghai[J]. Cities, 2017, 66: 10-22.

  [80] KIELAR P, BIEDERMANN D, KNEIDL A, et al. A unified pedestrian routing model combining multiple graph-based navigation methods[C] // Traffic and Granular Flow ’15. Cham: Springer, 2016: 241-248.

  [81] ABEDI N, BHASKAR A, CHUNG E, et al. Assessment of antenna characteristic effects on pedestrian and cyclists travel-time estimation based on Bluetooth and WiFi MAC addresses[J]. Transportation research part c: emerging technologies, 2015, 60: 124-141.

  [82] ALOY J M, MAGRINYA F, DE MEDINA M C A. Centrality measures and intermediate scale: the potential structuring role of the road network in Valles Oriental[J]. Ace-architecture city and environment, 2019, 14(39): 11-36.

  [83] 闫闪闪, 靳诚. 基于多源数据的市域旅游流空间网络结构特征——以洛阳市为例[J]. 经济地理, 2019, 39(8): 231-240.

  [84] FENG X, LI K, DING C, et al. Bayesian network modeling explorations of strategies on reducing perceived transfer time for urban rail transit service improvement in different seasons[J]. Cities, 2019, 95: 102474.

  [85] QIN X, ZHEN F, GONG Y. Combination of big and small data: empirical study on the distribution and factors of catering space popularity in Nanjing, China[J]. Journal of urban planning and development, 2019, 145(1): 05018022.

  [86] 邱坚坚, 刘毅华, 陈浩然, 等. 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[J]. 经济地理, 2019, 39(6): 7-15.

  [87] SHI S, WALL R, PAIN K. Exploring the significance of domestic investment for foreign direct investment in china: a city-network approach[J]. Urban studies, 2019, 56(12): 2447-2464.

  [88] DANYLUK M. Fungible space: competition and volatility in the global logistics network[J]. International journal of urban and regional research, 2019, 43(1): 94-111.

  [89] TAYLOR P J. City generics: external urban relations in ancient-Mesopotamian and modern-global city networks[J]. Urban geography, 2019, 40(8): 1210-1230.

  [90] 龙瀛, 刘曦, 王晟. 中国电子商务空间格局研究——以某大型电商为例[J]. 上海城市规划, 2016(5): 86-93.

  [91] 席广亮, 甄峰, 张敏, 等. 网络消费时空演变及区域联系特征研究——以京东商城为例[J]. 地理科学, 2015, 35(11): 1372-1380.

  [92] 龙瀛, 吴康, 王江浩, 等. 大模型：城市和区域研究的新范式[J]. 城市规划学刊, 2014(6): 52-60.

  
  

• 收起