甄峰 秦萧

Zhen Feng, Qin Xiao

关键词：大数据；信息通信技术；城市研究；智慧城市规划；新型城镇化

Keywords：Big Data; Information and Communication Technology (ICT)

摘要：

在信息与通信技术快速发展和智慧城市建设上升为国家新型城镇化发展战略的背景下，大数据在城市研究中的地位日趋重要，并影响着智慧城市规划理念和方法的创新。本文通过对国内外应用大数据进行城市研究的文献梳理，认为大数据可以为智慧城市研究与规划提供新的数据思维和理念，并加强城市管理者分析和解决城市问题的能力。基于此，本文主要从多规协同体系、智慧空间规划体系、规划与建设重点以及体制与机制创新等四个层面构建了基于大数据应用的智慧城市规划框架，对于丰富和补充传统城市研究与规划理论，及指导智慧城市建设与管理实践具有重要意义。

Abstract：

With the background of the rapid development of Information and Communication Technology (ICT) and the construction of smart city being as one of the national urbanization development strategies, the status of the big data in the urban study is becoming more and more important. The appliance of the big data in the area of urban study has, as well, affected the innovation of the theory and methods of smart city planning. In this paper, authors review the application of big data in both domestic and foreign urban study and prove that big data can provide new ideas and concepts of data, enhance the ability of the urban managers to analyze and solve urban problems. Based on this, the authors build 4-level framework of the smart city planning based on big data application: the cooperative system of the multi-kind planning, space planning system of smart city, the key of planning and construction, and the innovation of system and mechanism. This study has the vital significance to enrich and supplement the traditional urban study and planning theory, to guide the smart city construction and management practice.

甄峰，南京大学建筑与城市规划学院，教授。
zhenfeng@nju.edu.cn
秦萧，南京大学地理与海洋科学学院，博士研究生。
qinxiao1070@126.com

• [1] Hey T, Tansley S, Tolle K M. The Fourth Paradigm: Data-intensive Scientific Discovery[R]. Microsoft Research.US, 2009.
  [2] 维克托·迈尔·舍恩伯格, 肯尼思, 著. 大数据时代：生活、工作与思维方式的大变革[M]. 盛杨艳, 周涛, 译. 杭州: 浙江人民出版社, 2012.
  [3] DeLyser D, Sui D. Crossing the Qualitative-Quantitative Chasm III[J]. Progress in Human Geography, 2014, 38(2): 294-307.
  [4] Krings G, Calabrese F, Ratti C, et al..Urban Gravity: A Model for Inter-city Telecommunication Flows[J]. Journal of Statistical Mechanics: Theory and Experiment, 2009(7): 1-8.
  [5] Naaman M, Zhang A X, Brody S, et al..On the Study of Diurnal Urban Routines on Twitter[C] // Sixth International AAAI Conference on Weblogs and Social Media, 2012.
  [6] 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[J]. 地理学报, 2012, 67(8): 1031-1043.

  [7] Kang C, Zhang Y, Ma X, et al..Inferring Properties and Revealing Geographical Impacts of Intercity Mobile Communication Network of China Using a Subnet Data Set[J]. International Journal of Geographical Information Science, (ahead-of-print), 2012: 1-18.
  [8] Becker R A, Caceres R, Hanson K, et al. A Tale of One City: Using Cellular Network Data for Urban Planning[J]. IEEE Pervasive Computing, 2011, 10(4): 18-26.
  [9] Mark B, Nick M. Microscopic Simulations of Complex Metropolitan Dynamics[R/OL]. 2011. http://eprints.ncrm.ac.uk/2051/1/complex_city_paper[1].pdf.
  [10] Sagl G, Resch B, Hawelka B, et al..From Social Sensor Data to Collective Human Behaviour Patterns: Analysing and Visualising Spatio-temporal Dynamics in Urban Environments[C] // Proceedings of the GI-Forum 2012: Geovisualization, Society and Learning. 2012: 54-63.
  [11] Chen H, Chiang R H L, Storey V C. Business Intelligence and Analytics: From Big Data to Big Impact[J]. MIS Quarterly, 2012, 36(4).
  [12] Liu Y, Kang C, Gao S, et al..Understanding Intra-urban Trip Patterns from Taxi Trajectory Data[J]. Journal of Geographical Systems, 2012, 14(4): 463-483.
  [13] Liu Y, Wang F, Xiao Y, et al. Urban Land Uses and Traffic ‘Source-sink Areas’: Evidence from GPS-enabled Taxi Data in Shanghai[J]. Landscape and Urban Planning, 2012, 106(1): 73-87.
  [14] 柴彦威, 申悦, 肖作鹏, 等. 时空间行为研究动态及其实践应用前景[J]. 地理科学进展, 2012, 31(6): 667-675.
  [15] Kwan M P, Lee J. Geovisualization of Human Activity Patterns Using 3D GIS: A Time-Geographic Approach[M] // Goodchild Michael F, Janelle Donald G, eds. Spatially Integrated Social Science: Examples in Best Practice. Oxford: Oxford University Press, 2004: 48-66.
  [16] Lüscher P, Weibel R. Exploiting Empirical Knowledge for Automatic Delineation of City Centres from Large-scale Topographic Databases[J]. Computers, Environment and Urban Systems, 2013, 37: 18-34.
  [17] Hollenstein L, Purves R. Exploring Place Through User-generated Content: Using Flickr Tags to Describe City Cores [J]. Journal of Spatial Information Science, 2013(1): 21-48.
  [18] Wakamiya S, Lee R, Sumiya K. Urban Area Characterization Based on Semantics of Crowd Activities in Twitter. GeoSpatial Semantics, Springer Berlin Heidelberg, 2011: 108-123.
  [19] Ming-Hsiang T, et al..Mapping Social Activities and Concepts with Social Media (Twitter) and Web Search Engines (Yahoo and Bing): A Case Study in 2012 U.S. Presidential Election[J]. AutoCarto International Symposium on Automated Cartography Proceedings, South Carolina, 2012: 1-13.
  [20] 秦萧, 甄峰, 等. 大数据时代城市时空间行为研究方法[J]. 地理科学进展, 2013, 32(9): 1352-1361.
  [21] 甄峰, 翟青, 等. 信息时代移动社会理论构建与城市地理研究[J]. 地理研究, 2012, 31(2): 197-206.
  [22] 魏广君, 董伟, 孙晖. “多规整合”研究进展与述评[J]. 城市规划学刊, 2012(1): 76-82.
  [23] Castells M. The Informational City: Information Technology, Economic Restructuring, and the Urban-Regional Process[M]. Oxford: Blackwell, 1989.
  [24] 秦萧, 甄峰, 朱寿佳，席广亮. 基于网络口碑度的南京主城区餐饮业空间分布格局研究——以大众点评网为例[J]. 地理科学，2014，34（7）： 810-816.
  [25] 冉斌, 邱志军, 裘炜毅, 等. 大数据环境下手机定位数据在城市规划中实践[C].中国城市规划年会（2013）, 2013.

  
  

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