地理科学 ›› 2018, Vol. 38 ›› Issue (1): 1-10.doi: 10.13249/j.cnki.sgs.2018.01.001

所属专题: 地理大数据

• •    下一篇

基于多源大数据的城市体征诊断指数构建与计算——以上海市为例

柴彦威1(), 刘伯初1(), 刘瑜2, 马修军3, 塔娜4, 申悦5   

  1. 1.北京大学城市与环境学院,北京 100871
    2.北京大学遥感与地理信息系统研究所,北京 100871
    3.北京大学信息科学技术学院,北京 100871
    4.华东师范大学地理科学学院,上海 200241
    5.华东师范大学城市与区域科学学院,上海 200062
  • 收稿日期:2017-04-20 修回日期:2017-07-25 出版日期:2018-01-10 发布日期:2018-01-10
  • 作者简介:

    作者简介:柴彦威(1964-),男,甘肃会宁人,教授,博士生导师,主要从事城市社会与行为地理研究。E-mail:chyw@pku.edu.cn

  • 基金资助:
    国家自然科学基金项目(41571144,41529101,41601159);“十二五”国家科技支撑计划项目(2015BAJ08B06)资助

Construction and Calculation of Diagnostic Index of Urban Signs Based on Multi-source Big Data: Case of Shanghai

Yanwei Chai1(), Bochu Liu1(), Yu Liu2, Xiujun Ma3, Tana4, Yue Shen5   

  1. 1.College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
    2.Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing 100871, China
    3.School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China
    4.School of Geographic Sciences, East China Normal University, Shanghai 200241, China
    5.School of Urban and Regional Science, East China Normal University, Shanghai 200062, China
  • Received:2017-04-20 Revised:2017-07-25 Online:2018-01-10 Published:2018-01-10
  • Supported by:
    National Natural Science Foundation of China(41571144,41529101,41601159);The State Twelfth Five-year Scientific and Technological Support Project(2015BAJ08B06)

摘要:

基于多源大数据,构建了整合城市活动-移动系统、城市人口系统、城市运行系统、城市环境系统4个系统的城市体征诊断指数体系。该指数体系分解为底力、动力、压力、活力4个维度,具有4个层次和12个时空间尺度。底力指数表征土地、人口等空间单元基本属性,用以把握区域总体特征;动力指数通过企业发展状况、环境质量等反映了空间单元的发展状态;压力指数用以监测城市系统运行状况,起到风险评判与预警的作用;活力指数以活动和流的时空特征进行活动动态展现,反映空间单元的真实活力。最后以2016年4月6日为例,计算和展示了上海各街道的综合和各维度体征诊断指数,说明了体征诊断指数的可应用性和指数计算结果的稳健性。城市体征诊断指数可以辅助于城市网格化管理、压力预警等治理需求。

关键词: 城市体征, 城市体征诊断指数, 健康城市, 多源数据, 上海市

Abstract:

Urban signs characterize the state of development and operation of a city, including construction conditions of built environment,driving force of urban economic and social development, operational status of facilities and urban activities of individuals in the city, etc. The diagnosis of urban signs equals to the health examination of urban development and operation, by which sticking points are recognized. A set of reliable and practical urban diagnostic indices is required not only to comprehensively reflect correlative sub urban systems that are static or dynamic, but also illustrate the status of urban system through quantitative methods and geo-visualization. Using traditional data and big data from different sources, this paper constructs a system of diagnostic index of urban signs based upon the integration of urban activity-travel system, urban population system, urban operation system, and urban environment system. The diagnostic index system is decomposed into 4 dimensions including fundamental force, driving force, pressure and vitality. The fundamental force index is used to describe basic attributes of land use and population; the driving force index reflects the state of development of spatial units through development of enterprises and quality of the environment; the pressure index is used to monitor the running status of the urban system, and as such, it plays a role in risk-evaluation and risk-warning; the vitality index reflects the real vitality of the spatial units by demonstrating the dynamic characteristics of the activity system and flows in time and space. 12 spatio-temporal scales are acquired through intersection of 4 levels of the spatial units(municipal Shanghai , district, Jiedao, census tract)and 3 levels of temporal scales(annual,daily and real time levels). The index weight is determined by fuzzy hierarchy analysis. Taking April 6, 2016 as an example, we calculate both comprehensive and dimensional diagnostic index of urban signs of Jiedaos (subdistrict that is sub-divided into several residential communities or neighbourhoods) in Shanghai and elaborate on how the diagnostic index of urban signs corresponds to actual state and facilitates detection of urban problems. Results show that comprehensive diagnostic index varies slightly while considerable variations emerge in diagnostic index of each dimension. Fundamental force index, driving force index and vitality index decline gradually from inner city to suburbs. On the contrary, pressure index increases from inner city to suburbs. Through visual and real-time analysis and evaluation, the diagnostic index of urban signs has huge potential for implementation in urban grid management, pressure warning and other needs of urban governance.

Key words: urban signs, diagnostic index of urban signs, healthy city, multi-source data, Shanghai

中图分类号: 

  • K901