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Quantify city-level dynamic functions across China using social media and POIs data

文献类型：期刊论文

作者Qian, Jiale1,2; Liu, Zhang1,2; Du, Yunyan1,2; Liang, Fuyuan3; Yi, Jiawei1,2; Ma, Ting1,2; Pei, Tao1,2
刊名COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
出版日期2021
卷号85页码:14
关键词Urban function Human activity Social media Points-of-Interest Random forest
ISSN号0198-9715
DOI10.1016/j.compenvurbsys.2020.101552
通讯作者Du, Yunyan()
英文摘要Location-aware big data from social media have been widely used to study functions of different zones in a city but not across a city as a whole. In this study, a novel framework is proposed to quantify city-level dynamic functions of 200 cities in China from a perspective of collective human activities. The random forest model was used to determine the temporal variations in the proportions of different urban functions by examining the relationship between Points-of-Interest (POIs) and Tencent Location Request (TLR) data. We then hierarchically clustered and analyzed the structures and distribution patterns of the dynamic urban functions of 200 Chinese cities at different temporal scales. In the end, we calculated an urban functional equilibrium index based on the urban functional proportion and then mapped spatial distribution patterns of the indexes across mainland China. Results show that on a daily scale when the cities were grouped into two clusters, they are either dominated by the work/education and commerce or residence functions. The cities in the former cluster are mainly the provincial capitals and located within major urban agglomerations. When the cities were grouped into four clusters, the clusters are dominated their commerce, work, residence, and balanced multiple functions, respectively. For each of the 200 cities, its urban functions change dynamically from the daybreak to the evening in terms of human activities. Besides, the equilibrium indexes show a power-law relationship with their rankings. Our research shows that city-level dynamic function can be quantified from the perspective of variations in human activities by using social media big data that otherwise could not be achieved in the conventional urban functions' studies.
WOS关键词URBAN LAND-USE ; CLASSIFICATION ; PATTERNS ; REGIONS ; POINTS ; CITIES ; AREAS
资助项目National Key Research and Development Program of China[2017YFB0503605] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19040501] ; Strategic Priority Research Program of the Chinese Academy of Sciences[QYZDY-SSW-DQC007-2] ; National Science Foundation of China[41421001]
WOS研究方向Computer Science ; Engineering ; Environmental Sciences & Ecology ; Geography ; Operations Research & Management Science ; Public Administration
语种英语
WOS记录号WOS:000596814400006
出版者ELSEVIER SCI LTD
资助机构National Key Research and Development Program of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/137873]  
专题中国科学院地理科学与资源研究所
通讯作者Du, Yunyan
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, 11A,Datun Rd, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Western Illinois Univ, Dept Geog, Macomb, IL 61455 USA
推荐引用方式
GB/T 7714		 Qian, Jiale,Liu, Zhang,Du, Yunyan,et al. Quantify city-level dynamic functions across China using social media and POIs data[J]. COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,2021,85:14.
APA Qian, Jiale.,Liu, Zhang.,Du, Yunyan.,Liang, Fuyuan.,Yi, Jiawei.,...&Pei, Tao.(2021).Quantify city-level dynamic functions across China using social media and POIs data.COMPUTERS ENVIRONMENT AND URBAN SYSTEMS,85,14.
MLA Qian, Jiale,et al."Quantify city-level dynamic functions across China using social media and POIs data".COMPUTERS ENVIRONMENT AND URBAN SYSTEMS 85(2021):14.

入库方式： OAI收割

来源：地理科学与资源研究所

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