武汉市道路结构与商业集聚空间关联分析

doi:10.18306/dlkxjz.2017.11.004

Abstract

Abstract:

Urban road structure is one of the most important factors influencing commercial agglomeration. Research on the relationship between urban road structure and commercial agglomeration plays a supporting role for the layout of services and traffic planning. Based on theories of space syntax combined with GIS and bivariate correlation analysis, we explored the correlation between road structure and commercial agglomeration in the Wuhan metropolitan area. The space syntax model was used to compute road structure indicators. The kernel density estimation method was used to calculate the density of commercial points of interests (C-POI) in 2014 to analyze the spatial structure of commercial agglomeration. We used the Pearson correlation coefficient to analyze the correlation between road structure and commercial agglomeration. The results show that: (1) Global integration showed the highest correlation with the commercial agglomeration among the four spatial syntactic variables. Finance and insurance services had the highest correlation with road structure. (2) Connectivity value and global integration value were significantly and positively correlated with C-POI density, with a spatial correlation pattern of "high-high" agglomeration. Total depth value showed a significant and negative correlation with C-POI density, with a spatial correlation pattern of "high-low" agglomeration. C-POI density increased first and then decreased with increasing control values. (3) The spatial distribution of commercial agglomeration presented a "multicore-transitional area-periphery" multiple level structure. "High-high" agglomeration and "high-low" agglomeration were concentrated in the "core area" and the "transitional area" in the vicinity of the cores.

Key words: space syntax, kernel density estimation, road structure, commercial agglomeration, spatial correlation, Wuhan City

Yuyao HAN, Limin JIAO, Gang XU. Correlation analysis of road structure and commercial agglomeration in Wuhan City[J].PROGRESS IN GEOGRAPHY, 2017, 36(11): 1349-1358.

Figures/Tables 9

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References 37

[1]	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. doi: 10.3969/j.issn.1673-0410.2014.11.280
	[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.] doi: 10.3969/j.issn.1673-0410.2014.11.280
[2]	池娇, 焦利民, 董婷, 等. 2016. 基于POI数据的城市功能区定量识别及其可视化[J]. 测绘地理信息, 41(2): 68-73.
	[Chi J, Jiao L M, Dong T, et al.2016. Quantitative identification and visualization of urban functional area based on POI data[J]. Journal of Geomatics, 41(2): 68-73.]
[3]	邓毅, 胡彬. 2016. 基于空间句法的城市公共空间适老性规划设计框架[J]. 城市问题, (6): 53-60.
	[Deng Y, Hu B.2016. Planning framework of urban public space for the aged based on space syntax[J]. Urban Problems, (6): 53-60.]
[4]	黄经南, 高浩武, 但梦薇. 2014. 基于空间句法的商场室内空间可识别性研究: 以武汉光谷步行街为例[J]. 城市问题, (6): 46-52.
	[Huang J N, Gao H W, Dan M W.2014. Urban commercial interior space identification based on space syntax: A case study of Wuhan Optical Valley Walking Streett[J]. Urban Problems, (6): 46-52.]
[5]	江斌, 黄波, 陆锋. 2002. GIS环境下的空间分析和地学视觉化[M]. 北京: 高等教育出版社.
	[Jiang B, Huang B, Lu F.2002. Spatial analysis and geovisualization in GIS[M]. Beijing, China: Higher Education Press.]
[6]	蒋三庚. 2005. 论商业集聚[J]. 北京工商大学学报: 社会科学版, 20(3): 1-4.
	[Jiang S G.2005. Research on commercial enterprise concentration[J]. Journal of Beijing Technology and Business University: Social Sciences, 20(3): 1-4.]
[7]	焦利民, 张博恩, 许刚, 等. 2016. 气溶胶光学厚度与PM2.5浓度相关关系的时空变异[J]. 干旱区资源与环境, 30(12): 34-39. doi: 10.13448/j.cnki.jalre.2016.380
	[Jiao L M, Zhang B E, Xu G, et al.2016. Spatio-temporal variability of correlation between aerosol optical depth and PM2.5 concentration[J]. Journal of Arid Land Resources and Environment, 30(12): 34-39.] doi: 10.13448/j.cnki.jalre.2016.380
[8]	刘承良, 余瑞林, 段德忠. 2015. 基于空间句法的武汉城市圈城乡道路网通达性演化分析[J]. 地理科学, 35(6): 698-707. doi: 10.1016/j.dendro.2011.01.009
	[Liu C L, Yu R L, Duan D Z.2015. The evolution of spatial accessibility of urban-rural road network based on the space syntax in Wuhan metropolitan area[J]. Scientia Geographica Sinica, 35(6): 698-707.] doi: 10.1016/j.dendro.2011.01.009
[9]	卢燕, 余斌, 韩勇. 2016. 基于客流结构的高铁经济辐射效应研究: 以武汉市为例[J]. 长江流域资源与环境, 25(1): 39-47. doi: 10.11870/cjlyzyyhj201601005
	[Lu Y, Yu B, Han Y.2016. Economic radiation effect of high-speed rail based on structure of passenger flow: A case study of Wuhan City[J]. Resources and Environment in the Yangtze Basin, 25(1): 39-47.] doi: 10.11870/cjlyzyyhj201601005
[10]	毛政元, 李霖. 2004. 空间模式的测度及其应用[M]. 北京: 科学出版社.
	[Mao Z Y, Li L.2004. Kongjian moshi de cedu jiqi yingyong[M]. Beijing, China: Science Press.]
[11]	王浩锋, 施苏, 饶小军. 2013. 街道形态与城市密度[C]//城市时代, 协同规划: 2013中国城市规划年会论文集. 青岛: 中国城市规划学会.
	[Wang H F, Shi S, Rao X J.2013. Jiedao xingtai yu chengshi midu[C]//Chengshi shidai, xietong guihua: Annual national planning conference 2013. Qingdao: Urban Planning Society of China.]
[12]	王益, 吴永发. 2016. 基于句法变量分析的徽州古村落空间安全机制研究[J]. 规划师, 32(3): 101-107.
	[Wang Y, Wu Y F.2016. Syntax parameter analysis based Huizhou ancient village space crime prevention mechanism[J]. Planners, 32(3): 101-107.]
[13]	吴志军, 田逢军. 2012. 基于空间句法的城市游憩空间形态特征分析: 以南昌市主城区为例[J]. 经济地理, 32(6): 156-161.
	[Wu Z J, Tian F J.2012. The analysis of urban recreational space shape characteristic and influencing factors based on space syntax: Taking Nanchang as an example[J]. Economic Geography, 32(6): 156-161.]
[14]	薛东前, 王传胜. 2002. 城市群演化的空间过程及土地利用优化配置[J]. 地理科学进展, 21(2): 95-102. doi: 10.11820/dlkxjz.2002.02.001
	[Xue D Q, Wang C S.2002. A study on the spatial process for the evolution of urban agglomerations and optimal land use[J]. Progress in Geography, 21(2): 95-102.] doi: 10.11820/dlkxjz.2002.02.001
[15]	詹璇, 林爱文, 孙铖, 等. 2016. 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[J]. 地理科学进展, 35(9): 1155-1166.
	[Zhan X, Lin A W, Sun C, et al.2016. Centrality of public transportation network and its coupling with bank branches distribution in Wuhan City[J]. Progress in Geography, 35(9): 1155-1166.]
[16]	张晓瑞, 程志刚, 白艳. 2014. 空间句法研究进展与展望[J]. 地理与地理信息科学, 30(3): 82-87. doi: 10.3969/j.issn.1672-0504.2014.03.018
	[Zhang X R, Cheng Z G, Bai Y.2014. Review and prospect of space syntax[J]. Geography and Geo-Information Science, 30(3): 82-87.] doi: 10.3969/j.issn.1672-0504.2014.03.018
[17]	郑星. 2005. 武汉市大型零售商业设施空间布局研究[D]. 武汉: 华中科技大学.
	[Zheng X.2005. Spatial location analysis of large retail stores in Wuhan[D]. Wuhan, China: Huazhong University of Science and Technology.]
[18]	周瑄, 鲁政. 2014. 环境意象的空间句法解读[J]. 建筑学报, (3): 1-6.
	[Zhou X, Lu Z.2014. Rereading environmental image in terms of spatial syntax[J]. Architectural Journal, (3): 1-6.]
[19]	朱东风. 2006. 基于空间句法(Spacesyntax)分析的城市内部中心性研究: 以苏州为例[J]. 现代城市研究, 21(12): 60-67.
	[Zhu D F.2006. A case study of city Suzhou on urban inner centralities basing on spacesyntax methods[J]. Modern Urban Research, 21(12): 60-67.]
[20]	Bafna S.2003. Space syntax a brief introduction to its logic and analytical techniques[J]. Environment and Behavior, 35(1): 17-29. doi: 10.1177/0013916502238863
[21]	Barabási A L, Albert R.1999. Emergence of scaling in random networks[J]. Science, 286: 509-512. doi: 10.1126/science.286.5439.509 pmid: 10521342
[22]	Cerin E, Saelens B E, Sallis J F, et al.2006. Neighborhood environment walkability scale: Validity and development of a short form[J]. Medicine and Science in Sports and Exercise, 38(9): 1682-1691. doi: 10.1249/01.mss.0000227639.83607.4d
[23]	Dzhambov A M, Dimitrova D D, Turnovska T H.2014. Improving traffic noise simulations using space syntax: Preliminary results from two roadway systems[J]. Archives of Industrial Hygiene and Toxicology, 65(3): 259-272. doi: 10.2478/10004-1254-65-2014-2469 pmid: 25222575
[24]	Hiller B.1996. Space is the machine: A configurational theory of architecture[M]. New York, NY: Cambridge University Press.
[25]	Jeong S K, Lee T H, Ban Y U.2015. Characteristics of spatial configurations in Pyongyang, North Korea[J]. Habitat International, 47: 148-157. doi: 10.1016/j.habitatint.2015.01.010
[26]	Jiang B.2009. Ranking spaces for predicting human movement in an urban environment[J]. International Journal of Geographical Information Science, 23(7): 823-837. doi: 10.1080/13658810802022822
[27]	Jiang B, Claramunt C, Klarqvist B.2000. Integration of space syntax into GIS for modelling urban spaces[J]. International Journal of Applied Earth Observation and Geoinformation, 2(3-4): 161-171. doi: 10.1016/S0303-2434(00)85010-2
[28]	Jiao L M, Mao L F, Liu Y L.2015. Multi-order landscape expansion index: Characterizing urban expansion dynamics[J]. Landscape and Urban Planning, 137: 30-39. doi: 10.1016/j.landurbplan.2014.10.023
[29]	Koohsari M J, Sugiyama T, Mavoa S, et al.2016. Street network measures and adults' walking for transport: Application of space syntax[J]. Health & Place, 38: 89-95. doi: 10.1016/j.healthplace.2015.12.009 pmid: 26808485
[30]	Lima J J.2001. Soeio-spatial segregation and urban form: Belém at the end of the 1990s[J]. Geoforum, 32(4): 493-507. doi: 10.1016/S0016-7185(01)00019-7
[31]	Liu X T, Jiang B.2012. Defining and generating axial lines from street center lines for better understanding of urban morphologies[J]. International Journal of Geographical Information Science, 26(8): 1521-1532. doi: 10.1080/13658816.2011.643800
[32]	Moudon A V, Lee C, Cheadle A D, et al.2006. Operational definitions of walkable neighborhood: Theoretical and empirical insights[J]. Journal of Physical Activity and Health, 3(S1): S99-S117. doi: 10.1123/jpah.3.s1.s99
[33]	Omer I, Jiang B.2015. Can cognitive inferences be made from aggregate traffic flow data[J]. Computers Environment and Urban Systems, 54: 219-229. doi: 10.1016/j.compenvurbsys.2015.08.005
[34]	Önder D E, Gigi Y.2010. Reading urban spaces by the space-syntax method: A proposal for the South Haliç Region[J]. Cities, 27(4): 260-271. doi: 10.1016/j.cities.2009.12.006
[35]	Xu G, Jiao L M, Zhao S L, et al.2016. Examining the impacts of land use on air quality from a spatio-temporal perspective in Wuhan, China[J]. Atmosphere, 7(5): 62. doi: 10.3390/atmos7050062
[36]	Wang F H, Antipova A, Porta S.2011. Street centrality and land use intensity in Baton Rouge, Louisiana[J]. Journal of Transport Geography, 19(2): 285-293. doi: 10.1016/j.jtrangeo.2010.01.004
[37]	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. doi: 10.1016/j.cities.2014.05.005

一级分类	二级分类	占比/%
餐饮服务	外国餐厅,中餐厅,餐饮相关场所,咖啡厅,茶饮馆,糕饼店,快餐店,冷饮店,甜品店,休闲餐饮场所	30.81
购物服务	超级市场,商场,购物中心,商业街,家电电子卖场,家居建材市场,服装鞋帽皮具店,花鸟鱼虫市场,个人用品,体育用品店,专卖店,特殊买卖场所	37.89
住宿服务	宾馆酒店,旅馆招待所,住宿服务相关	3.76
金融保险服务	银行,银行相关,自动提款机,证券公司,保险公司	3.39
商务写字楼	商务写字楼,商住两用楼宇	0.87
科教文化服务	传媒机构,驾校,培训机构	3.18
生活服务	旅行社,美容美发店,摄影冲印店,事务所,洗浴场所	14.99
体育休闲服务	影剧院,休闲娱乐场所,度假疗养场所,高尔夫相关	3.73
医疗保健服务	诊所	1.38

相关性		连接值	全局集成度	总深度值	控制值
商业POI 密度	r	0.762^*	0.945^**	-0.789^*	-0.309
	Sig.	0.047	0.007	0.035	0.500
	N	7	7	7	7

相关性	连接值	控制值	全局集成度	总深度值
餐饮服务POI密度	0.761^*	-0.224	0.885^**	-0.783^*
购物服务POI密度	0.782^*	-0.240	0.926^**	-0.770^*
住宿服务POI密度	0.744	-0.229	0.948^**	-0.805^*
金融保险服务POI密度	0.785^*	-0.268	0.961^**	-0.815^*
商务写字楼POI密度	0.782^*	-0.277	0.955^**	-0.799^*
科教文化服务POI密度	0.785^*	-0.272	0.957^**	-0.804^*
生活服务POI密度	0.753	-0.270	0.944^**	-0.789^*
体育休闲服务POI密度	0.733	-0.249	0.945^**	-0.811^*
医疗保健服务POI密度	0.779^*	-0.306	0.954^**	-0.802^*

Correlation analysis of road structure and commercial agglomeration in Wuhan City

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