北京市公共服务设施集聚中心识别分析

doi:10.11821/dlyj020190117

地理研究 ›› 2020, Vol. 39 ›› Issue (3): 554-569.doi: 10.11821/dlyj020190117

北京市公共服务设施集聚中心识别分析

湛东升¹, 张文忠²(), 张娟锋¹, 李佳洺², 谌丽³, 党云晓⁴

^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

收稿日期:2019-02-18 修回日期:2019-07-12 出版日期:2020-03-20 发布日期:2020-05-20
通讯作者: 张文忠
作者简介:湛东升（1987-）,男,安徽寿县人,博士,副教授,硕士生导师,研究方向为人居环境和城市空间结构。E-mail: zhands@126.com
基金资助:
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)

Identifying urban public service facilities centers in Beijing

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

^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

摘要/Abstract

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。

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

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

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.

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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参考文献 48

[1]	孙铁山, 王兰兰, 李国平 . 北京都市区多中心空间结构特征与形成机制. 城市规划, 2013,37(7):28-32.
	[ Sun Tieshan, Wang Lanlan, Li Guoping . Characteristics and formation mechanisms of polycentric spatial structure in Beijing metropolitan area. City Planning Review, 2013,37(7):28-32.]
[2]	张纯, 易成栋, 宋彦 . 北京市职住空间关系特征及变化研究: 基于第五、六次人口普查和2001、2008年经济普查数据的实证分析. 城市规划, 2016,40(10):59-64.
	[ Zhang Chun, Yi Chengdong, Song Yan . Characteristics of job-housing spatial relationship and changes in Beijing: An empirical study based on data from the 5th, 6th population census and economy census in 2001 and 2008. City Planning Review, 2016,40(10):59-64.]
[3]	王松涛, 郑思齐, 冯杰 . 公共服务设施可达性及其对新建住房价格的影响: 以北京中心城为例. 地理科学进展, 2007,26(6):87-94.
	[ Wang Songtao, Zheng Siqi, Feng Jie . Spatial accessibility of housing to public services and its impact on housing price: A case study of Beijing's inner city. Progress in Geography, 2007,26(6):87-94.]
[4]	张文忠 . 宜居城市建设的核心框架. 地理研究, 2016,35(2):205-213.
	[ Zhang Wenzhong . The core framework of the livable city construction. Geographical Research, 2016,35(2):205-213.]
[5]	张文忠, 湛东升 . “国际一流的和谐宜居之都”的内涵及评价指标. 城市发展研究, 2017,24(6):116-124.
	[ Zhang Wenzhong, Zhan Dongsheng . Study on connotation and evaluation index of world-class metropolis of harmony and livability. Urban Studies, 2017,24(6):116-124.]
[6]	魏义方, 张本波 . 特大城市公共服务均衡发展的重点、难点与对策: 以北京市为例. 宏观经济管理, 2018, (5):73-78.
	[ Wei Yifang, Zhang Benbo . Research on balanced development of public services in mega cities: Take Beijing for example. Macroeconomic Management, 2018, (5):73-78.]
[7]	樊立惠, 蔺雪芹, 王岱 . 北京市公共服务设施供需协调发展的时空演化特征: 以教育医疗设施为例. 人文地理, 2015,30(1):90-97.
	[ Fan Lihui, Lin Xueqin, Wang Dai . Spatial-temporal succession characteristics of public service facilities supply and demand coordinated development in Beijing: A case study of educational and medical facilities. Human Geography, 2015,30(1):90-97.]
[8]	黎婕, 冯长春 . 北京城市公共服务设施空间分布均衡性研究. 地域研究与开发, 2017,36(3):71-77.
	[ Li Jie, Feng Changchun . Spatial balance analysis on urban public service in Beijing city. Areal Research and Development, 2017,36(3):71-77.]
[9]	纪叶, 周家祥 . 多样化需求下基本公共服务的规划方法探索: 以北京市小学生住—学时空结构为例. 城市发展研究, 2017,24(6):53-61.
	[ Ji Ye, Zhou Jiaxiang . Planning methods of basic public services under diversified demands: A case study of home-school isochronal spatial structures of Beijing pupils. Urban Development Studies, 2017,24(6):53-61.]
[10]	谌丽, 张文忠, 杨翌朝 . 北京城市居民服务设施可达性偏好与现实错位. 地理学报, 2013,68(8):1071-1081.
	[ Chen Li, Zhang Wenzhong, Yang Yizhao . Residents' incongruence between reality and preference of accessibility to urban facilities in Beijing. Acta Geographica Sinica, 2013,68(8):1071-1081.]
[11]	吴一洲, 赖世刚, 吴次芳 . 多中心城市的概念内涵与空间特征解析. 城市规划, 2016,40(6):23-31.
	[ Wu Yizhou, Lai Shigang, Wu Cifang . Research on polycentricity: Concept, connotation, and spatial features. City Planning Review, 2016,40(6):23-31.]
[12]	孙斌栋, 魏旭红 . 上海都市区就业—人口空间结构演化特征. 地理学报, 2014,69(6):747-758.
	[ Sun Bindong, Wei Xuhong . Spatial distribution and structure evolution of employment and population in Shanghai metropolitan area. Acta Geographica Sinica, 2014,69(6):747-758.]
[13]	魏冶, 修春亮, 王绮 . 空间联系视角的沈阳市多中心城市结构研究. 人文地理, 2014,29(3):83-88.
	[ Wei Ye, Xiu Chunliang, Wang Qi . An empirical study on polycentric urban spatial structure of Shenyang in the perspective of spatial association. Human Geography, 2014,29(3):83-88.]
[14]	Marmolejo-Duarte C, Cerda-Troncoso J . Metropolitan Barcelona 2001-06, or how people’s spatial-temporal behaviour shapes urban structures. Regional Studies, 2019, DOI: 10.1080/00343404.2019.1583326
[15]	Zhong C, Schläpfer M, Arisona S M , et al. Revealing centrality in the spatial structure of cities from human activity patterns. Urban Studies, 2017,54(2):437-455.
[16]	He Q, He W, Song Y , et al. The impact of urban growth patterns on urban vitality in newly built-up areas based on an association rules analysis using geographical‘big data’. Land Use Policy, 2018,78:726-738.
[17]	White A N . Accessibility and public facility location. Economic Geography, 1979,55(1):18-35.
[18]	Zolnik E, Minde J, Gupta D D , et al. Supporting planning to co-locate public facilities: A case study from Loudoun County, Virginia. Applied Geography, 2010,30(4):687-696.
[19]	甄峰, 秦萧, 王波 . 大数据时代的人文地理研究与应用实践. 人文地理, 2014,29(3):1-6.
	[ Zhen Feng, Qin Xiao, Wang Bo . Human geography research and practical application in big data era. Human Geography, 2014,29(3):1-6.]
[20]	杨喜平, 方志祥 . 移动定位大数据视角下的人群移动模式及城市空间结构研究进展. 地理科学进展, 2018,37(7):880-889.
	[ Yang Xiping, Fang Zhixiang . Recent progress in studying human mobility and urban spatial structure based on mobile location big data. Progress in Geography, 2018,37(7):880-889.]
[21]	龙瀛, 张宇, 崔承印 . 利用公交刷卡数据分析北京职住关系和通勤出行. 地理学报, 2012,67(10):1339-1352.
	[ Long Ying, Zhang Yu, Cui Chengyin . Identifying commuting pattern of Beijing using bus smart card data. Acta Geographica Sinica, 2012,67(10):1339-1352.]
[22]	Huang J, Levinson D, Wang Jiaoe , et al. Job-worker spatial dynamics in Beijing: Insights from smart card data. Cities, 2019,86:89-93.
[23]	Cai J, Huang B, Song Y . Using multi-source geospatial big data to identify the structure of polycentric cities. Remote Sensing of Environment, 2017,202(12):210-221.
[24]	Li J, Long Y, Dang A . Live-Work-Play centers of Chinese cities: Identification and temporal evolution with emerging data. Computers, Environment and Urban Systems, 2018,71(9):58-66.
[25]	Long Y, Han H, Tu Y , et al. Evaluating the effectiveness of urban growth boundaries using human mobility and activity records. Cities, 2015,46:76-84.
[26]	Zhai Wei, Bai Xueyin, Shi Yu , et al. Beyond Word2vec: An approach for urban functional region extraction and identification by combining Place2vec and POIs. Computers, Environment and Urban Systems, 2019,74(3):1-12.
[27]	陈世莉, 陶海燕, 李旭亮 , 等. 基于潜在语义信息的城市功能区识别: 广州市浮动车GPS时空数据挖掘. 地理学报, 2016,71(3):471-483.
	[ Chen Shili, Tao Haiyan, Li Xuliang , et al. Discovering urban functional regions using latent semantic information: Spatiotemporal data mining of floating cars GPS data of Guangzhou. Acta Geographica Sinica, 2016,71(3):471-483.]
[28]	段亚明, 刘勇, 刘秀华 , 等. 基于POI大数据的重庆主城区多中心识别. 自然资源学报, 2018,33(5):788-800.
	[ Duan Yaming, Liu Yong, Liu Xiuhua , et al. Identification of polycentric urban structure of central Chongqing using points of interest big data. Journal of Natural Resources, 2018,33(5):788-800.]
[29]	浩飞龙, 王士君, 冯章献 , 等. 基于POI数据的长春市商业空间格局及行业分布. 地理研究, 2018,37(2):366-378.
	[ Hao Feilong, Wang Shijun, Feng Zhangxian , et al. Spatial pattern and its industrial distribution of commercial space in Changchun based on POI data. Geographical Research, 2018,33(5):788-800.]
[30]	王芳, 高晓路, 许泽宁 . 基于街区尺度的城市商业区识别与分类及其空间分布格局: 以北京为例. 地理研究, 2015,34(6):1125-1134.
	[ Wang Fang, Gao Xiaolu, Xu Zening . Identification and classification of urban commercial districts at block scale. Geographical Research, 2015,34(6):1125-1134.]
[31]	李佳洺, 张文忠, 李业锦 , 等. 基于微观企业数据的产业空间集聚特征分析: 以杭州市区为例. 地理研究, 2016,35(1):95-107.
	[ Li Jiaming, Zhang Wenzhong, Li Yejin , et al. The characteristics of industrial agglomeration based on micro-geographic data. Geographical Research, 2016,35(1):95-107.]
[32]	方忠权, 郭思茵, 王章郡 . 会展企业微观集聚研究: 以广州市流花地区为例. 经济地理, 2013,33(8):91-96.
	[ Fang Zhongquan, Guo Siyin, Wang Zhangjun . Analysis on the micro-agglomeration of exhibition enterprises: A case of Liuhua area in Guangzhou. Economic Geography, 2013,33(8):91-96.]
[33]	Talen E . The social equity of urban service distribution: An exploration of park access in Pueblo, Colorado, and Macon, Georgia. Urban Geography, 1997,18(6):521-541.
[34]	Talen E . School, community, and spatial equity: An empirical investigation of access to elementary schools in West Virginia. Annals of the Association of American Geographers, 2001,91(3):465-486.
[35]	Luo W, Wang F . Measures of spatial accessibility to health care in a GIS environment: Synthesis and a case study in the Chicago region. Environment and Planning B, 2003,30(6):865-884.
[36]	Giuliano G, Small K A . Subcenters in the Los Angeles region. Regional Science and Urban Economics, 1991,21(2):163-182.
[37]	Bogart W, Ferry W . Employment centres in Greater Cleveland: Evidence of evolution in a formerly monocentric city. Urban Studies, 1999,36(12):2099-2110.
[38]	Anderson N B, Bogart W T . The structure of sprawl: Identifying and characterizing employment centers in polycentric metropolitan areas. American Journal of Economics and Sociology, 2001,60(1):147-169.
[39]	胡瑞山, 王振波, 仇方道 . 基于普查单位的北京市就业中心识别与功能定位. 人文地理, 2016,31(4):58-65.
	[ Hu Ruishan, Wang Zhenbo, Qiu Fangdao . Identification and function orientation of employment centers in Beijing based on the census unit analyzing. Human Geography, 2016,31(4):58-65.]
[40]	郭洁, 吕永强, 沈体雁 . 基于点模式分析的城市空间结构研究: 以北京都市区为例. 经济地理, 2015,35(8):68-74.
	[ Guo Jie, Lv Yongqiang, Shen Tiyan . Urban spatial structure based on point pattern analysis: Taking Beijing metropolitan area as a case. Economic Geography, 2015,35(8):68-74.]
[41]	Mcmillen D P . Nonparametric employment subcenter identification. Journal of Urban Economics, 2001,50(3):448-473.
[42]	Dadashpoor H, Alidadi M . Towards decentralization: Spatial changes of employment and population in Tehran Metropolitan Region, Iran. Applied Geography, 2017,85:51-61.
[43]	Ouyang W, Wang B, Tian L , et al. Spatial deprivation of urban public services in migrant enclaves under the context of a rapidly urbanizing China: An evaluation based on suburban Shanghai. Cities, 2017,60:436-445.
[44]	詹璇, 林爱文, 孙铖 , 等. 武汉市公共交通网络中心性及其与银行网点的空间耦合性研究. 地理科学进展, 2016,35(9):1155-1166.
	[ Zhan Xuan, Lin Aiwen, Sun Cheng , et al. Centrality of public transportation network and its coupling with bank branches distribution in Wuhan city. Progress in Geography, 2016,35(9):1155-1166.]
[45]	Schuurman N, Bérubé M, Crooks V A . Measuring potential spatial access to primary health care physicians using a modified gravity model. Canadian Geographer, 2010,54(1):29-45.
[46]	张程远, 张淦, 周海瑶 . 基于多元大数据的城市活力空间分析与影响机制研究: 以杭州中心城区为例. 建筑与文化, 2017, (9):183-187.
	[ Zhang Chengyuan, Zhang Gan, Zhou Haiyao . The analysis and influence mechanism research of urban vigorous space based on multiple big data: A case study on the partial area of central Hangzhou. Architecture & Culture, 2017, (9):183-187.]
[47]	许泽宁, 高晓路 . 基于电子地图兴趣点的城市建成区边界识别方法. 地理学报, 2016,71(6):928-939.
	[ Xu Zening, Gao Xiaolu . A novel method for identifying the boundary of urban built-up areas with POI data. Acta Geographica Sinica, 2016,71(6):928-939.]
[48]	湛东升, 张文忠, 余建辉 , 等. 基于地理探测器的北京市居民宜居满意度影响机理. 地理科学进展, 2015,34(8):966-975.
	[ Zhan Dongsheng, Zhang Wenzhong, Yu Jianhui , et al. Analysis of influencing mechanism of residents' livability satisfaction in Beijing using geographical detector. Progress in Geography, 2015,34(8):966-975.]

大类	小类	数据来源
购物设施	便利店;普通超市;大型连锁超市	高德POI数据
餐饮设施	餐馆	高德POI数据
金融设施	银行机构	高德POI数据
教育设施	幼儿园;小学;中学	北京市教育委员会
医疗设施	基层医疗设施;一二级医院;三级医院	北京市卫生和计划生育委员会
文体设施	社区文化服务中心;文体综合设施	北京市文化局、文物局和体育局
养老设施	养老服务机构	北京市民政局
休闲游憩设施	注册公园	首都园林绿化政务网
公共交通设施	公交站点;地铁站点	分别来自北京城市实验室和北京市交通委员会

变量	类型	偏回归系数	标准误	t值	P值	标准化回归系数
截距		3.453***	0.08	41.90	0.00
区位	最近公共服务设施集聚中心距离	-0.028***	0.00	-6.89	0.00	-0.098
	市中心距离	-0.005***	0.00	-3.59	0.00	-0.051
性别	女性	-0.027	0.02	-1.35	0.18	-0.019
年龄（岁）	20~29	-0.115	0.07	-1.62	0.11	-0.079
	30~39	-0.128**	0.07	-1.80	0.07	-0.083
	40~49	-0.093	0.07	-1.27	0.20	-0.048
	50~59	-0.121	0.08	-1.52	0.13	-0.042
	≥60	-0.029	0.12	-0.24	0.81	-0.004
学历	高中	0.041	0.04	1.04	0.30	0.025
	大专或大学	0.072*	0.04	1.83	0.07	0.049
	研究生以上	0.106**	0.05	2.03	0.04	0.041
户口	本地户口	0.040*	0.02	1.75	0.08	0.026
职业类型	技能型职业	-0.037	0.02	-1.60	0.11	-0.023
家庭月收入（元）	3000~4999	0.047	0.04	1.13	0.26	0.027
	5000~9999	0.159***	0.04	3.94	0.00	0.105
	10000~15000	0.170***	0.04	3.92	0.00	0.096
	15000~20000	0.164***	0.05	3.29	0.00	0.065
	20000~30000	0.215***	0.06	3.50	0.00	0.061
	>30000	0.249***	0.07	3.54	0.00	0.057

北京市公共服务设施集聚中心识别分析

Identifying urban public service facilities centers in Beijing

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