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

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。

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

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.