Exploring relations between city regions based on mobile phone data

被引:1
作者
Wang Shuo-feng [1 ]
Li Zhi-heng [1 ,2 ]
Jiang Shan [1 ,2 ]
Xie Na [3 ]
机构
[1] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Grad Sch Shenzhen, Shenzhen, Peoples R China
[3] Cent Univ Finance & Econ, Sch Management Sci & Engn, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
mobile phone data; city relations; community; degree; COMMUNITY STRUCTURE; PATTERNS;
D O I
10.1007/s11771-016-3233-7
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
City regions often have great diversity in form and function. To better understand the role of each region, the relations between city regions need to be carefully studied. In this work, the human mobility relations between regions of Shanghai based on mobile phone data is explored. By formulating the regions as nodes in a network and the commuting between each pair of regions as link weights, the distribution of nodes degree, and spatial structures of communities in this relation network are studied. Statistics show that regions locate in urban centers and traffic hubs have significantly larger degrees. Moreover, two kinds of spatial structures of communities are found. In most communities, nodes are spatially neighboring. However, in the communities that cover traffic hubs, nodes often locate along corridors.
引用
收藏
页码:1799 / 1806
页数:8
相关论文
共 50 条
[21]   Application of the local colocation quotient method in jobs-housing balance measurement based on mobile phone data: A case study of Nanjing City [J].
Liu, Hao ;
Kwan, Mei-Po ;
Hu, Mingxing ;
Wang, Hui ;
Zheng, Jiemin .
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2024, 109
[22]   Bus Trip OD Identification Based on Mobile Phone Data [J].
Yu Y.-B. ;
Hou J. .
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2021, 21 (02) :65-72
[23]   Population dynamics based on mobile phone data to improve air pollution exposure assessments [J].
Picornell, Miguel ;
Ruiz, Tomas ;
Borge, Rafael ;
Garcia-Albertos, Pedro ;
de la Paz, David ;
Lumbreras, Julio .
JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY, 2019, 29 (02) :278-291
[24]   Mobile Phone Data: A Survey of Techniques, Features, and Applications [J].
Okmi, Mohammed ;
Por, Lip Yee ;
Ang, Tan Fong ;
Ku, Chin Soon .
SENSORS, 2023, 23 (02)
[25]   Exploring the changes of individuals' travel behavior in response to COVID-19 and their influencing factors based on mobile phone data [J].
Zhou, Shuli ;
Zhou, Suhong ;
Jing, Fengrui ;
Qi, Luhui ;
Li, Jianjun .
JOURNAL OF TRANSPORT & HEALTH, 2024, 36
[26]   Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method [J].
Liu, Lingbo ;
Peng, Zhenghong ;
Wu, Hao ;
Jiao, Hongzan ;
Yu, Yang .
SUSTAINABILITY, 2018, 10 (07)
[27]   How does socioeconomic status influence social relations? A perspective from mobile phone data [J].
Wang, Xi ;
Pei, Tao ;
Song, Ci ;
Chen, Jie ;
Shu, Hua ;
Liu, Yaxi ;
Guo, Sihui ;
Chen, Xiao .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2023, 615
[28]   Exploring the Effects of Sampling Locations for Calibrating the Huff Model Using Mobile Phone Location Data [J].
Lu, Shiwei ;
Shaw, Shih-Lung ;
Fang, Zhixiang ;
Zhang, Xirui ;
Yin, Ling .
SUSTAINABILITY, 2017, 9 (01)
[29]   Exploring the disparities in park access through mobile phone data: Evidence from Shanghai, China [J].
Xiao, Yang ;
Wang, De ;
Fang, Jia .
LANDSCAPE AND URBAN PLANNING, 2019, 181 :80-91
[30]   Population movements based on mobile phone location data: the Czech Republic [J].
Halas, Marian ;
Blazek, Vojtech ;
Klapka, Pavel ;
Kraft, Stanislav .
JOURNAL OF MAPS, 2021, 17 (01) :116-122