GEOGRAPHICAL RESEARCH ›› 2020, Vol. 39 ›› Issue (3): 554-569.doi: 10.11821/dlyj020190117

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Identifying urban public service facilities centers in Beijing

ZHAN Dongsheng1, ZHANG Wenzhong2(), ZHANG Juanfeng1, LI Jiaming2, CHEN Li3, DANG Yunxiao4   

  1. 1. School of Management, Zhejiang University of Technology, Hangzhou 310023, China
    2. Institute of Geographic Science and Natural Resources Research, CAS, Beijing 100101, China
    3. College of Applied Arts and Science, Beijing Union University, Beijing 100191, China
    4. Land and Urban-Rural Development Institute, Zhejiang University of Finance and Economics, Hangzhou 310018, China
  • Received:2019-02-18 Revised:2019-07-12 Online:2020-03-20 Published:2020-05-20
  • Contact: ZHANG Wenzhong E-mail:zhangwz@igsnrr.ac.cn

Abstract:

Urban public service facilities centers are not only the concentrated areas for the diverse public service facilities, but also the hot spots areas of public service facilities’ consumption and demonstration areas of urban vitality. While previous polycentric city literature have focused on job and population subcenters, very little is known about multi-centers of urban public service facilities. Using spatial points data of urban public service facilities in Beijing, this paper utilizes the weighted kernel density analysis and contour analysis methods to identify the urban public service facilities centers in Beijing with consideration of their service radius and quality among different types and grades facilities. The results show that although the spatial patterns of different types of urban public service facilities’ hotspots are varied, all of them have presented a similar center-edge spatial pattern. The spatial patterns of cluster intensity and mixing degree of urban public service facilities display “one center with five sub-regions” and “one core with multiple points”, respectively. There are 136 urban public service facilities centers totally identified within the study area, whose cluster intensity presents a U-shaped change by distance to the city center and an exponential distribution by population density. Multiple regression modelling results further indicate that distance to the closest urban public service facilities center has a significant negative impact on urban residents’ satisfaction with public service facilities in Beijing, and its impact intensity is much stronger than that of distance to the city center. The formation mechanism of urban public service facilities centers in Beijing include the basic role of natural and historical factors, the leading role of economic development factors, the regulating role of social demand factors in addition with the guiding role of planning and policy factors. Our findings suggest that the spatial equalization of urban public service facilities centers in Beijing should be strengthened, and the number of urban public service facilities centers in urban fringe areas should be moderately increased, especially for the urban public service facilities centers with higher concentration intensity, which could promote to dismantling non-capital functional industries and population from the central city zone to the suburbs.

Key words: urban public service facilities centers, satisfaction with urban public service facilities, weighted kernel density analysis, contour lines analysis, Beijing