How do urban services facilities affect social segregation among people of different economic levels? A case study of Shenzhen city

被引:11
作者
Wu, Yuyang [1 ]
Yao, Yao [1 ,2 ]
Ren, Shuliang [1 ]
Zhang, Shiyi [1 ]
Guan, Qingfeng [1 ,3 ]
机构
[1] China Univ Geosci, Sch Geog & Informat Engn, Wuhan 430078, Peoples R China
[2] Univ Tokyo, Ctr Spatial Informat Sci, Kashiwa, Chiba 778568, Japan
[3] China Univ Geosci, Natl Engn Res Ctr GIS, Wuhan, Peoples R China
基金
中国国家自然科学基金;
关键词
Social segregation; urban environment; mobile phone data; urban planning; geographically weighted regression; MOBILE PHONE; ACTIVITY PATTERNS; VILLAGES; CHINA;
D O I
10.1177/23998083221140415
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Social segregation hinders the development of cities and has become a hot topic in urban research. Existing studies have focused on the difference in the distribution of crowd activities to measure segregation but have ignored the impact of the urban environment on crowd gathering and segregation. To study the impact and understand social segregation more comprehensively, we coupled mobile phone datasets and housing price data to divide city dwellers into three socioeconomic levels. Considering that spatial colocation is a necessary condition for interaction among various social groups, spatial colocation probability was proposed to quantitatively describe the degree of social segregation at the community scale. Point-of-interest (POI) data were introduced to represent the urban service facilities. The effect of urban service facilities on the segregation of different groups was analyzed by using geographically weighted regression (GWR). The results indicate three points, as follows. (1) Significant social segregation in Shenzhen mostly occurs in suburban and downtown areas, and the interaction segregation of people mainly occurs between people with high and low socioeconomic levels. (2) More economically inclusive and necessary service facilities (e.g., medical and insurance companies) can promote crowd interaction and ease the segregation of social activities. (3) The impact of service facilities on the interaction of various social groups is related to the development of the area where the activities occur, and the most significant impact is in high-tech industrial zones. This study quantitatively calculated the impacts of different service facilities on different groups of people in different communities and times. From the results, detailed and reasonable suggestions were made for city planners.
引用
收藏
页码:1502 / 1517
页数:16
相关论文
共 57 条
[1]  
Andersen H.S., 2019, Urban sores: On the interaction between segregation, urban decay and deprived neighbourhoods
[2]  
Blumenberg E., 2019, Built Environment, V45, P563, DOI DOI 10.2148/BENV.45.4.563
[3]  
Boo H.V., 2017, Journal of ASIAN Behavioural Studies, V2, P67, DOI DOI 10.1016/J.SBSPRO.2012.03.361
[4]   HOUSE PRICE IMPACTS OF RACIAL, INCOME, EDUCATION, AND AGE NEIGHBORHOOD SEGREGATION [J].
Brasington, David M. ;
Hite, Diane ;
Jauregui, Andres .
JOURNAL OF REGIONAL SCIENCE, 2015, 55 (03) :442-467
[5]   Geographically weighted regression - modelling spatial non-stationarity [J].
Brunsdon, C ;
Fotheringham, S ;
Charlton, M .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES D-THE STATISTICIAN, 1998, 47 :431-443
[6]  
Bureau, 2018, SHENZHEN STAT YB
[7]   Exploring the propensity to perform social activities: a social network approach [J].
Carrasco, Juan Antonio ;
Miller, Eric J. .
TRANSPORTATION, 2006, 33 (05) :463-480
[8]   Customer Restaurant Choice: An Empirical Analysis of Restaurant Types and Eating-Out Occasions [J].
Chua, Bee-Lia ;
Karim, Shahrim ;
Lee, Sanghyeop ;
Han, Heesup .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (17) :1-23
[9]   Inferring social ties from geographic coincidences [J].
Crandall, David J. ;
Backstrom, Lars ;
Cosley, Dan ;
Suri, Siddharth ;
Huttenlocher, Daniel ;
Kleinberg, Jon .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2010, 107 (52) :22436-22441
[10]   Effects of urban planning in guiding urban growth: Evidence from Shenzhen, China [J].
Deng, Yu ;
Fu, Bojie ;
Sun, Chuanzhun .
CITIES, 2018, 83 :118-128