《Spatial Distribution of Enterprise Communities and Its Implications Based on POI Data: Case of Xi’an, China》

打印
作者
Wenheng Wu;Zhuhui Ding;Kun Huang;Yan Song;Haixia Dong
来源
JOURNAL OF URBAN PLANNING AND DEVELOPMENT,Vol.147,Issue3
语言
英文
关键字
作者单位
Professor, College of Urban and Environmental Sciences, Northwest Univ., Xi’an 710127, China; Key Laboratory of Earth Surface System and Environmental Carrying Capacity of Shaanxi Province, Northwest Univ., Xi’an 710127, China (corresponding author). Email: [email protected];Master Student, College of Urban and Environmental Sciences, Northwest Univ., Xi’an 710127, China. Email: [email protected];Master Student, College of Urban and Environmental Sciences, Northwest Univ., Xi’an 710127, China. Email: [email protected];Professor, Dept. of City and Regional Planning, Univ. of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3140. Email: [email protected];Associate Professor, School of Public Security, Northwest Univ. of Political Science and Law, Xi’an 710122, China. Email: [email protected]
摘要
China’s residential social space has changed significantly following economic reform in 1978. Enterprise communities (ECs) are walled-off residential spaces that were built and managed mostly by the state or collectively owned enterprises to house workers during the 1950s to 1970s. Many ECs are still used in urban China, but they are primary sites for urban poverty. This paper used point of interest (POI) data, field surveys, and spatial analysis to analyze the distribution of ECs in Xi’an, China, and assess the policy implications. Results indicated that the ECs were mainly located in the inner city and were characterized by small-scale agglomeration or cluster distribution along the former major transport routes. The ECs are sites of urban poverty because of industrial transition. Their large renewal potential as construction land should be fully recognized. This study will help to better understand and optimize urban internal space and may apply to countries or regions with similar housing types and urban space. Exploring the relevant issues of postsocialist ECs through POI data can enrich and strengthen scientific research in urban residential areas.