| 北京市公共服务设施集聚中心识别分析 |
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| 引用本文： | 湛东升,张文忠,张娟锋,李佳洺,谌丽,党云晓.北京市公共服务设施集聚中心识别分析[J].地理研究,2020,39(3):554-569. |
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| 作者姓名： | 湛东升 张文忠 张娟锋 李佳洺 谌丽 党云晓 |
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| 作者单位： | 1. 浙江工业大学管理学院,杭州310023;2. 中国科学院地理科学与资源研究所,北京100101;3. 北京联合大学应用文理学院,北京100191;4. 浙江财经大学土地与城乡发展研究院,杭州310018 |
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| 基金项目： | 浙江省社科规划课题成果(20NDQN261YB);国家自然科学基金项目(41871170);教育部哲学社会科学研究重大课题攻关项目资助(18JZD033) |
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| 摘 要： | 公共服务设施集聚中心不仅是多样化公共服务设施分布的集中区,也是公共服务设施消费的热点区和城市活力的窗口区。已有城市多中心研究主要关注就业和人口多中心,却较少关注公共服务设施多中心特征。基于北京市公共服务设施空间点要素数据,结合不同类型和等级公共服务设施的服务半径与质量特征,采用加权核密度与等值线分析等方法对北京市公共服务设施集聚中心进行了识别。研究发现：不同类型公共服务设施热点区分布的空间模式有所差异,但均存在一定程度的中心边缘结构;公共服务设施集聚强度和混合度分别呈现出“一心五片”与“一核多点”的空间特征;根据公共服务设施集聚强度和混合度的等值线分布综合判定,研究区范围共识别出136个公共服务设施集聚中心,其集聚强度与距市中心距离呈现出U型变化规律,与所在街道的人口密度存在指数分布规律;多元回归模型验证,最近公共服务设施集聚中心距离对北京城市居民公共服务设施满意度具有显著的负向影响,且其相对影响强度超过“市中心距离”区位变量;北京市公共服务设施集聚中心的形成机制包括自然历史因素的基础作用、经济发展因素的主导作用、社会需求因素的调节作用和规划政策因素的引导作用。研究认为应加强北京城市公共服务设施集聚中心的空间均衡化建设,适度增加城市边缘郊区公共服务设施集聚中心的数量和服务能级,有助于引导和疏解非首都功能产业和人口向城市郊区转移。
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| 关 键 词： | 公共服务设施集聚中心 公共服务设施满意度 加权核密度分析 等值线分析 北京 |
| 收稿时间： | 2019-02-18 |
| 修稿时间： | 2019-07-12 |
Identifying urban public service facilities centers in Beijing |
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| ZHAN Dongsheng,ZHANG Wenzhong,ZHANG Juanfeng,LI Jiaming,CHEN Li,DANG Yunxiao.Identifying urban public service facilities centers in Beijing[J].Geographical Research,2020,39(3):554-569. |
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| Authors: | ZHAN Dongsheng ZHANG Wenzhong ZHANG Juanfeng LI Jiaming CHEN Li DANG Yunxiao |
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| Institution: | 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 |
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| 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. |
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| Keywords: | urban public service facilities centers satisfaction with urban public service facilities weighted kernel density analysis contour lines analysis Beijing |
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