服务业区位选择的交通网络指向研究——以北京城市中心区为例

doi:10.18306/dlkxjz.2015.08.002

摘要/Abstract

摘要：

基于空间句法、核密度估计和皮尔森相关分析等方法,以北京城市中心区为例,结合空间句法轴线模型与百度POI（Points of Interest）数据,探讨服务业区位选择的交通网络指向规律。结果表明：①北京城市中心区的交通网络总体呈现“东优西劣、北优南劣、西南最劣”的空间格局,高层级网络则呈现“中心环状集聚—外围多极分布”的分布模式。②与高穿行度交通网络相比,高整合度交通网络的区位指向性更强,在不同尺度均更易诱发服务业的集聚。③总体而言,服务业区位选择的交通网络指向性明显,但不同类型服务业的区位指向程度依据研究尺度的不同具有显著差异,并据此将25类主要服务业划分为街区指向型、街道指向型、双重指向型和无指向型四类。本文对探索服务业集聚发展规律、提高服务业和交通网络规划的科学性具有参考意义,并可为北京城市中心区服务业存量优化提供决策依据。

关键词: 服务业区位选择, 交通网络指向, 空间句法, 北京, 城市中心区

Abstract:

Using space syntax, kernel density estimation, and Pearson correlation analysis methods, this research combines the segment lines model of space syntax and Baidu POI data to explore the traffic network point of services location choice in the central city area of Beijing. The results indicate that (1) the traffic network is well connected, accessible, and dense in east and north, relatively poorly connected and sparse in west and south, and most poorly connected in southwest. The overall network shows the spatial pattern of annular agglomeration in the inner city and polycentric distribution in the periphery. (2) Compared to traffic network with high connectivity NACH(Normalised Angular Choice), traffic network with high level of integration NAIN (Normalised Angular Integration) has stronger level of point of services location choice and is more likely to induce agglomeration of services.(3) Traffic network point of services location choice is clear but the point levels of different services are remarkably different at different scales. Therefore, the services are divided into four types, including point at the neighborhood scale; point at the street scale; point at both scales, and nonpoint. This research provides some reference that facilities the understanding of services agglomeration and helps to improve services and traffic network planning and decision-making for optimizing urban structure of the central city area of Beijing.

Key words: services location choice, traffic network point, space syntax, Beijing, central city area

沈体雁, 周麟, 王利伟, 吕永强. 服务业区位选择的交通网络指向研究——以北京城市中心区为例[J]. 地理科学进展, 2015, 34(8): 947-956.

SHEN Tiyan, ZHOU Lin, WANG Liwei, LV Yongqiang. Traffic network point of services location choice:a case study of the central city area of Beijing[J]. PROGRESS IN GEOGRAPHY, 2015, 34(8): 947-956.

图/表 8

图1

图2

图3

表1

服务业区位选择与交通网络的关系"

服务业类型	数量	R_NACH	R_NACH₁₆₀₀	R_NAIN	R_NAIN₁₆₀₀	S_NACH/%	S_NACH₁₆₀₀/%	S_NAIN/%	S_NAIN₁₆₀₀/%
零售业	23327	0.56^**	0.56^**	0.60^**	0.62^**	56.33	57.01	60.90	64.35
餐饮业	12290	0.55^**	0.55^**	0.61^**	0.58^**	52.02	51.42	54.09	54.58
居民服务业	8091	0.65^**	0.66^**	0.72^**	0.70^**	48.64	48.68	47.95	50.57
商务服务业	4091	0.32^**	0.31^**	0.40^**	0.36^**	41.36	37.50	53.75	45.45
货币金融服务	4039	0.34^**	0.33^**	0.42^**	0.41^**	57.20	54.97	62.22	60.14
住宿业	3997	0.61^**	0.61^**	0.63^**	0.68^**	42.69	42.24	44.58	45.00
教育	3221	0.48^**	0.48^**	0.47^**	0.40^**	38.54	38.12	36.54	38.79
娱乐业	2738	0.57^**	0.58^**	0.62^**	0.64^**	48.58	50.10	50.62	50.66
房地产业	1796	0.47^**	0.47^**	0.54^**	0.51^**	52.93	53.25	53.95	54.70
基层群众自治组织	1720	0.63^**	0.63^**	0.66^**	0.70^**	27.38	25.71	32.10	31.93
国家机构	1675	0.42^**	0.41^**	0.45^**	0.51^**	40.77	40.53	42.54	47.49
卫生	1441	0.57^**	0.57^**	0.62^**	0.64^**	42.78	41.28	44.21	47.40
文化艺术业	1213	0.59^**	0.58^**	0.58^**	0.61^**	38.25	36.37	40.29	38.64
电信、广播电视和卫星传输服务	1144	0.31^**	0.29^**	0.36^**	0.32^**	55.16	50.74	62.37	55.25
群众团体、社会团体和其他成员组织	1137	0.48^**	0.47^**	0.50^**	0.52^**	37.87	36.30	40.48	40.21
机动车、电子产品和日用产品修理业	885	0.17^*	0.16^*	0.22^*	0.22^*	49.58	49.24	45.21	46.96
研究和试验发展	800	0.21^*	0.20^*	0.17^*	0.09^*	41.65	41.78	41.40	37.84
新闻和出版业	571	0.45^**	0.44^**	0.45^**	0.44^**	41.97	41.70	43.12	44.31
体育	551	0.57^**	0.58^**	0.62^**	0.65^**	43.27	40.98	43.80	45.56
邮政业	516	0.18^*	0.19^*	0.22^*	0.22^*	43.65	40.65	44.02	45.33
广播、电视、电影和影视录音制作业	475	0.37^**	0.30^**	0.37^*	0.35^*	41.89	39.88	50.37	45.72
社会工作	306	0.38^**	0.38^**	0.40^**	0.45^**	24.28	24.28	25.59	30.16
保险业	243	0.29^**	0.28^**	0.35^**	0.36^**	40.51	38.69	50.53	49.08
国际组织	238	0.01^*	0.06^*	0.08^*	0.06^*	32.20	23.41	39.61	41.93
资本市场服务	238	0.21^*	0.19^*	0.25^*	0.26^*	46.47	45.84	58.66	57.30

表1

图4

图5

图6

图7

参考文献 28

1	陈晨, 程林, 修春亮. 2013. 沈阳市中心城区交通网络中心性及其与第三产业经济密度空间分布的关系[J]. 地理科学进展, 33(11): 1612-1621.
	[Chen C, Cheng L, Xiu C L.2013. Distribution of centrality of traffic network and its relationship with economic density of tertiary industry in Shenyang[J]. Progress in Geography, 33(11): 1612-1621.]
2	陈晨, 王法辉, 修春亮. 2013. 长春市商业网点空间分布与交通网络中心性关系研究[J]. 经济地理, 33(10): 40-47.
	[Chen C, Wang F H, Xiu C L.2013. The relationship between the spatial distribution of commercial networks and street centrality in Changchun[J]. Economic Geography, 33(10): 40-47.]
3	陈晨, 修春亮. 2014. 基于交通网络中心性的长春市大型综合医院空间可达性研究[J]. 人文地理, 29(5): 81-87.
	[Chen C, Xiu C L.2014. Spatial accessibility of large general hospitals in Changchun City center based on street network centrality[J]. Human Geography, 29(5): 81-87.]
4	樊文平, 石忆邵, 车建仁, 等. 2011. 基于GIS与空间句法的道路网结构对城市商业中心布局的影响[J]. 中山大学学报: 自然科学版, 50(3): 112-117.
	[Fan W P, Shi Y S, Che J R, et al.2011. Influence of urban street configuration on the location of urban commercial center based on GIS and space syntax[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 50(3): 112-117.
5	赖德胜, 孟大虎, 李长安, 等. 2014. 2014中国劳动力市场发展报告[M]. 北京: 北京师范大学出版社.
	[Lai D S, Meng D H, Li C A, et al.2014. 2014 Zhongguo laodongli shichang fazhan baogao[M]. Beijing China: Beijing Normal University Press.]
6	邵晖. 2008. 北京市生产者服务业聚集特征[J]. 地理学报, 63(12): 1289-1298.
	[Shao H.2008. Agglomeration of producer services in Beijing[J]. Acta Geographica Sinica, 63(12): 1289-1298.]
7	盛强. 2012. 社区级活力中心分布的空间逻辑: 以北京三环内222个街区内小商业聚集为例[J]. 国际城市规划, 27(6): 61-68.
	[Sheng Q.2012. Distribution logic of local public space: a spatial configuration analysis on the local shops inside 222 urban blocks in the third ring of Beijing[J]. Urban Planning International, 27(6): 61-68.]
8	王法辉, 刘瑜, 王姣娥. 2014. 交通网络与城市结构研究: 理论框架与中美两国实证案例[J]. 地理科学进展, 33(10): 1289-1299.
	[Wang F H, Liu Y, Wang J E.2014. Transport networks, intraurban structure and system of cities: a Sino-US comparative perspective[J]. Progress in Geography, 33(10): 1289-1299.]
9	王瑶莉, 高松, 刘瑜. 2013. 青岛城市道路邻近中心性及其应用方法[J]. 地理研究, 32(3): 452-464.
	[Wang Y L, Gao S, Liu Y.2013. Exploration into urban street closeness centrality and its application methods: a case study of Qingdao[J]. Geographical Research, 32(3): 452-464.]
10	张景秋, 贾磊, 孟斌. 2010. 北京城市办公活动空间集聚区研究[J]. 地理研究, 29(4): 675-682.
	[Zhang J Q, Jia L, Meng B.2010. A study on off ice activities cluster in Beijing City[J]. Geographical Research, 29(4): 675-682.]
11	赵莹, 柴彦威, 关美宝. 2014. 中美城市居民出行行为的比较: 以北京市与芝加哥市为例[J]. 地理研究, 33(12): 2275-2285.
	[Zhao Y, Chai Y W, Kwan M P.2014. Comparison of urban residents' travel behavior in China and the U. S.: a case study between Beijing and Chicago[J]. Geographical Research, 33(12): 2275-2285.]
12	Alonso W.1964. Location and land use[M]. Cambridge, UK: Cambridge University Press.
13	Crucitti P, Latora V, Porta S.2006. Centrality measures in spatial networks of urban streets[J]. Physical Review E, 73(3): 036125.
14	Heikkila E, Gordon P, Kim J I, et al.1989. What happened to the CBD-distance gradient? land values in a polycentric city[J]. Environment and Planning A, 21(2): 221-232.
15	Hillier B.1996. Space is the machine: a configurational theory of architecture[M]. Cambridge, UK: Cambridge University Press.
16	Hillier B, Penn A, Hanson J, et al.1993. Natural movement: or, configuration and attraction in urban pedestrian movement[J]. Environment and Planning B: Planning and Design, 20(1): 29-66.
17	Hillier B, Yang T, Turner A.2012. Normalising least angle choice in Depthmap: and how it opens up new perspectives on the global and local analysis of city space[J]. The Journal of Space Syntax, 3(2): 155-193.
18	Long Y, Liu X J.2013a. Automated identification and characterization of parcels (AICP) with OpenStreetMap and Points of Interest[J]. arXiv preprint arXiv: 1311.6165.
19	Long Y, Liu X J.2013b. Featured graphic. How mixed is Beijing, China? A visual exploration of mixed land use[J]. Environment and Planning A, 45(12): 2797-2798.
20	Mills E S.1972. Studies in the structure of the urban economy[M]. Baltimore, MD: Johns Hopkins University Press.
21	Porta S, Latora V, Wang F H, et al.2009. Street centrality and densities of retail and services in Bologna, Italy[J]. Environment and Planning B: Planning and Design, 36(3): 450-465.
22	Porta S, Latora V, Wang F H, et al.2012. Street centrality and the location of economic activities in Barcelona[J]. Urban Studies, 49(7): 1471-1488.
23	Sevtsuk A.2010. Path and place: a study of urban geometry and retail activity in Cambridge and Somerville, MA[D]. Cambridge: Massachusetts Institute of Technology.
24	Sheng Q.2011. Changing centralities under urban configurational 'scale-structure': pondering the spatial conditions for market and retail areas in Beijing[D]. TU Delft, Netherlands: Delft University of Technology.
25	Tsou K W, Cheng H T.2013. The effect of multiple urban network structures on retail patterns: a case study in Taipei, Taiwan[J]. Cities, 32: 13-23.
26	Turner A.2007. From axial to road-centre lines: a new representation for space syntax and a new model of route choice for transport network analysis[J]. Environment and Planning B: Planning and Design, 34(3): 539-555.
27	Wang F H, Chen C, Xiu C L, et al.2014. Location analysis of retail stores in Changchun, China: a street centrality perspective[J]. Cities, 41: 54-63.
28	Wilson A G.2000. Complex spatial systems: the modelling foundations of urban and regional analysis[M]. New York: Pearson Education.

[1]	朱冠宇, 陈鹏. 基于共同犯罪的犯罪人地域关系网络的空间演化及其影响因素——以北京市诈骗案件为例[J]. 地理科学进展, 2020, 39(5): 792-803.
[2]	郭雅琦, 陈鹏. 基于时空临近重复效应的犯罪热点特征及成因分析——以北京市抢劫案件为例[J]. 地理科学进展, 2020, 39(5): 804-814.
[3]	卢明华, 周悦颜, 刘汉初, 许欣. 北京企业对河北直接投资的时空动态特征及影响因素[J]. 地理科学进展, 2020, 39(3): 389-401.
[4]	李晓丽, 宋伟轩, 吴威, 马雨竹. 基于跟踪调查的北京城市空间感知研究——以中国科学院大学硕士研究生为例[J]. 地理科学进展, 2020, 39(2): 276-285.
[5]	王蓓, 王良, 刘艳华, 杨波, 黄晓春, 杨明. 基于手机信令数据的北京市职住空间分布格局及匹配特征[J]. 地理科学进展, 2020, 39(12): 2028-2042.
[6]	李春江, 马静, 柴彦威, 关美宝. 居住区环境与噪音污染对居民心理健康的影响——以北京为例[J]. 地理科学进展, 2019, 38(7): 1103-1110.
[7]	刘炳春, 齐鑫, 王庆山. 北京城市代谢预测研究——基于长短期记忆神经网络模型[J]. 地理科学进展, 2019, 38(6): 851-860.
[8]	申犁帆, 张纯, 李赫, 王烨, 王子甲. 城市轨道交通通勤与职住平衡状况的关系研究——基于大数据方法的北京实证分析[J]. 地理科学进展, 2019, 38(6): 791-806.
[9]	黄幸, 刘玉亭. 消费端视角的中国大城市新建绅士化现象——以北京宣武门ZS小区为例[J]. 地理科学进展, 2019, 38(4): 577-587.
[10]	杨振山, 吴笛, 杨定. 迁居意愿、地方依赖和社区认同——北京中关村地区居住选择调查分析[J]. 地理科学进展, 2019, 38(3): 417-427.
[11]	张延吉, 朱春武, 秦波. 犯罪数量与危害的空间分布及建成环境影响——基于北京市刑事案件的纵向研究[J]. 地理科学进展, 2019, 38(12): 1876-1889.
[12]	丁凯熙, 张利平, 宋晓猛, 佘敦先, 夏军. 北京地区汛期降雨时空演变特征及城市化影响研究[J]. 地理科学进展, 2019, 38(12): 1917-1932.
[13]	杜超, 王姣娥, 刘斌全, 黄鼎曦. 城市道路与公共交通网络中心性对住宅租赁价格的影响研究——以北京市为例[J]. 地理科学进展, 2019, 38(12): 1831-1842.
[14]	文嫮, 张强国, 杜恒, 罗芬. 北京电影产业空间集聚与网络权力分布特征研究[J]. 地理科学进展, 2019, 38(11): 1747-1758.
[15]	申犁帆, 张纯, 李赫, 王烨. 大城市通勤方式与职住失衡的相互关系[J]. 地理科学进展, 2018, 37(9): 1277-1290.