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

doi:10.13249/j.cnki.sgs.2018.01.001

Abstract

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

CLC Number:

K901

Yanwei Chai, Bochu Liu, Yu Liu, Xiujun Ma, Tana, Yue Shen. Construction and Calculation of Diagnostic Index of Urban Signs Based on Multi-source Big Data: Case of Shanghai[J].SCIENTIA GEOGRAPHICA SINICA, 2018, 38(1): 1-10.

Figures/Tables 8

Fig.1

Table 1

Table 2

Diagnostic index for urban signs"

一层指数	二层指数	三层指数	四层指数	指标计算方式
城市体征诊断指数 S	底力指数(F/0.16)	建设指数(F₁/0.42)	土地开发潜力指数(F₁₁/0.08)	未开发土地面积比例
			土地建设强度指数(F₁₂/0.34)	建筑密度
			土地混合利用指数(F₁₃/0.58)	土地利用混合程度的熵值= $- ∑ i = 1 n p i lo g 10 p i$ ,式中, $∑ i = 1 n p i = 1$ ,n为土地利用类型数,p_i为第i类土地面积占总面积比例^[23]
		人口指数(F₂/0.58)	人口素质指数(F₂₁/0.33)	常住人口中本科及以上人口比例
		人口指数(F₂/0.58)	职住平衡度指数(F₂₂/0.67)	从业人口与常住人口比例
	动力指数(D/0.26)	经济指数(D₁/0.53)	经济发展水平指数(D₁₁/0.73)	0.5×(标准化企业数+标准化企业从业人员数)
		经济指数(D₁/0.53)	经济开放程度指数(D₁₂/0.27)	0.5×(标准化外资企业数+标准化外资企业从业人员数)
		绿色指数(D₂/0.47)	空气质量指数(D₂₁/0.53)	AQI^①
		绿色指数(D₂/0.47)	开敞空间指数(D₂₂/0.47)	绿地广场面积比例
	压力指数(P/0.28)	运行指数(P₁/0.45)	交通运行指数(P₁₁/0.67)	浮动车平均车速
		运行指数(P₁/0.45)	市政设施运行指数(P₁₂/0.33)	实际负荷与最大稳定负荷比值^②
		拥挤指数(P₂/0.55)	人流热度指数(P₂₁/0.60)	单位面积位置请求数
		拥挤指数(P₂/0.55)	人流变化率指数(P₂₂/0.40)	位置请求数变化率
	活力指数(V/0.30)	活动指数(V₁/0.52)	居住活动指数(V₁₁/0.23)	单位面积居住活动人次=（居住用地面积/总面积）×总活动人次/总面积
			商业活动指数(V₁₂/0.47)	单位面积商业活动人次=（商业用地面积/总面积）×总活动人次/总面积
			创新活动指数(V₁₃/0.30)	单位面积创新活动人次=（创新技术人员/总就业人员）×总活动人次/总面积^③
		联系流指数(V₂/0.48)	人流联系指数(V₂₁/0.33)	以空间单元i为起讫点的人流量 $= ∑ F ij + F ji$ ,式中,i,j为空间单元集合M中单元编号,F_ij为空间单元i到空间单元j的人流量,F_ji为空间单元j到空间单元i的人流量
			交通流联系指数(V₂₂/0.53)	以空间单元为起讫点的浮动车流量,方法同上
			信息流联系指数(V₂₃/0.14)	以空间单元为起讫点的手机通话时长,方法同上

Table 2

Fig.2

Fig.3

Fig.4

Table 3

Table 4

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二层指数	对应系统	意义	类比
底力指数	土地利用和房屋、人口等	反映空间单元的土地、人口基本属性,用以把握其类型特征	身高、体重、BMI
动力指数	经济运行、自然环境等	空间单元经济社会发展的基础禀赋和动力	肺活量、血氧饱和度
压力指数	运行系统、活动-移动系统等	反映城市系统运行压力,起到风险评判与预警作用	尿蛋白、心理压力
活力指数	活动-移动系统、联系网络等	动态展现空间上的人的活动及交通、信息等流的联系	消耗能量、摄入营养

区位	底力指数F			动力指数D		压力指数P			活力指数V
区位	建设指数		人口指数		经济指数	绿色指数	运行指数	拥挤指数	活动指数	联系流指数
内环以内	0.626	0.733		0.225	0.181	0.174	0.531		0.384	0.269
内环至外环	0.517	0.687		0.142	0.278	0.186	0.696		0.270	0.240

外环以外
街道名称	底力指数F			动力指数D		压力指数P			活力指数V
街道名称	建设指数		人口指数		经济指数	绿色指数	运行指数	拥挤指数	活动指数	联系流指数
陆家嘴街道	0.581（55）	0.656（150）		0.959（1）	0.188（111）	0.171（166）	0.754（150）		0.249（73）	0.615（7）
梅陇镇	0.425（184）	0.707（73）		0.363（12）	0.427（20）	0.167（169）	0.653（172）		0.316（56）	0.648（5）
宝山路街道	0.642（25）	0.678（114）		0.084（143）	0.127（145）	0.171（168）	0.111（229）		0.450（18）	0.151（118）

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

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