道路网络中心性对餐饮业空间布局的影响——以青岛市主城区为例

doi:10.13249/j.cnki.sgs.2022.09.010

地理科学 ›› 2022, Vol. 42 ›› Issue (9): 1609-1618.doi: 10.13249/j.cnki.sgs.2022.09.010

道路网络中心性对餐饮业空间布局的影响——以青岛市主城区为例

陈玥莹(), 陈延斌, 殷冠文(), 宋成镇, 侯毅鸣

山东师范大学地理与环境学院，山东济南 250358

收稿日期:2021-11-16 修回日期:2022-01-20 接受日期:2022-06-28 出版日期:2022-09-10 发布日期:2022-11-14
通讯作者: 殷冠文 E-mail:1181457880@qq.com;yingw@sdnu.edu.cn
作者简介:陈玥莹（1998-），女，山东青岛人，硕士研究生，主要从事城市地理与城乡发展研究。E-mail: 1181457880@qq.com
基金资助:
国家自然科学基金项目(41601156);国家自然科学基金项目(41701177);山东省高等学校青创科技支持计划(2019RWE-014)

The Influence of Road Network Centrality on the Spatial Distribution of Catering: A Case Study of Qingdao Main Urban Area

Chen Yueying(), Chen Yanbin, Yin Guanwen(), Song Chengzhen, Hou Yiming

College of Geography and Environment, Shandong Normal University, Jinan 250358, Shandong, China

Received:2021-11-16 Revised:2022-01-20 Accepted:2022-06-28 Online:2022-09-10 Published:2022-11-14
Contact: Yin Guanwen E-mail:1181457880@qq.com;yingw@sdnu.edu.cn
Supported by:
National Natural Science Foundation of China(41601156);National Natural Science Foundation of China(41701177);Shandong Province Higher Educational Youth Innovation Science and Technology Support Program(2019RWE-014)

摘要/Abstract

摘要：

基于道路网络数据和兴趣点（POI）数据，以青岛市主城区为研究区域，分析道路网络中心性及餐饮业空间分布特征，采用全局和局部回归模型探究道路网络中心性对餐饮业分布的影响机制。结果表明：① 中介中心性高值区集中于城市主干道，邻近中心性呈现由中心向四周递减的环状分布特征，特征向量中心性的空间分布表现为多核心结构；② 青岛市餐饮业呈现出块状聚集、区域差异明显的空间分布格局，中餐厅、西餐厅和休闲餐饮具备多中心结构特征；③ 道路网络中心性指标与餐饮业的核密度值具有较高的空间相似性，高-高与低-低聚集区构成了主要的空间关联模式；④ 青岛市餐饮业分布受到道路网络中心性的显著影响，其中，中介中心性对餐饮业分布的影响程度较低，邻近中心性和特征向量中心性的影响程度较高。从局部来看，道路网络中心性对餐饮业分布的影响具有空间异质性，对不同类型餐饮业的影响具有明显的差异。

关键词: 道路网络中心性, 餐饮业, 空间异质性, 青岛市

Abstract:

Based on road network data and point of interest (POI) data, taking Qingdao in Qingdao main urban area as the research area, this article analyzes the centrality of road network and the spatial distribution characteristics of catering, and uses global and local regression models to explore the impact mechanism of road network centrality on the distribution of catering. The results show that: 1) The high value area of betweenness centrality is mainly concentrated in three main traffic trunk roads. The closeness centrality presents a circular distribution characteristic of decreasing from the center of the study area to the surrounding, and the spatial distribution of eigenvector centrality shows a multi-core structure. 2) Qingdao’s catering industry generally presents a spatial pattern of massive agglomeration and obvious regional differences. Chinese restaurants, Western restaurants and leisure catering have the characteristics of multi center structure. 3) The centrality index of road network has high spatial similarity with the kernel density value of catering. High-high and low-low aggregation areas constitute the main spatial correlation mode. 4) The distribution of catering in Qingdao is significantly affected by the centrality of road network. Among them, the betweenness centrality is mainly negative, and the positive effects of closeness centrality and eigenvector centrality are obvious. The impact of road network centrality on the distribution of catering has spatial heterogeneity. The imbalance of road network conditions leads to regional differences in economic activities, thus changing the spatial structure of catering. From the perspective of the impact of centrality on different types of catering, the western restaurant is most significantly affected by the road transit capacity and the importance of the road, the Chinese restaurant is the most sensitive to the improvement of road accessibility.

Key words: road network centrality, catering industry, spatial heterogeneity, Qingdao City

中图分类号:

TU984.113

陈玥莹, 陈延斌, 殷冠文, 宋成镇, 侯毅鸣. 道路网络中心性对餐饮业空间布局的影响——以青岛市主城区为例[J]. 地理科学, 2022, 42(9): 1609-1618.

Chen Yueying, Chen Yanbin, Yin Guanwen, Song Chengzhen, Hou Yiming. The Influence of Road Network Centrality on the Spatial Distribution of Catering: A Case Study of Qingdao Main Urban Area[J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(9): 1609-1618.

图/表 7

图1

图2

图3

图4

图5

表1

图6

参考文献 31

[1]	夏令军, 刘艳芳, 刘国炜. 中国地级城市餐饮业分布格局及影响因素——基于“大众点评网”数据的实证研究[J]. 经济地理, 2018, 38(5) 133-141.
	Xia Lingjun, Liu Yanfang, Liu Guowei. Spatial distribution pattern and influencing factors of catering industry in prefecture level and above cities in China: An empirical study based on the dianping. com Data. Economic Geography, 2018, 38(5) 133-141.
[2]	李启瑄, 王录仓, 乔杰, 等. “物象·意象, 经济·情感”新数据环境的餐饮业空间特征: 以兰州市为例[J]. 经济地理, 2018, 38(7) 126-135.
	Li Qixuan, Wang Lucang, Qiao Jie et al. "Object·image, economic·feelings" research on catering spatial pattern by newdata: Take Lanzhou as an example[J]. Economic Geography, 2018, 38(7) 126-135.
[3]	Yin G W, Liu Y G, Wang F L. Emerging Chinese new towns: Local government-directed capital switching in inland China[J]. Cities, 2018, 79(9) 102-112.
[4]	Dock J P, Song W, Lu J. Evaluation of dine-in restaurant location and competitiveness: Applications of gravity modeling in Jefferson County, Kentucky[J]. Applied Geography, 2015, 60: 204-209. doi: 10.1016/j.apgeog.2014.11.008
[5]	Thornton L E, Lamb K E, Ball K. Fast food restaurant locations according to socioeconomic disadvantage, urban-regional locality, and schools within Victoria, Australia[J]. SSM-Population Health, 2016, 2: 1-9. doi: 10.1016/j.ssmph.2015.12.001
[6]	Jung S, Jang S C. To cluster or not to cluster?: Understanding geographic clustering by restaurant segment[J]. International Journal of Hospitality Management, 2019, 77: 448-457. doi: 10.1016/j.ijhm.2018.08.008
[7]	Hollands S, Campbell M K, Gilliland J et al. A spatial analysis of the association between restaurant density and body mass index in Canadian adults[J]. Preventive Medicine, 2013, 57(4) 258-264. doi: 10.1016/j.ypmed.2013.07.002
[8]	Lan T, Yu M, Xu Z B et al. Temporal and spatial variation characteristics of catering facilities based on POI data: A case study within 5th ring road in Beijing[J]. Procedia Computer Science, 2018, 131: 1260-1268. doi: 10.1016/j.procs.2018.04.343
[9]	翟青, 高玉洁, 魏宗财. 南京市线上-线下餐饮空间分布格局——以大众点评网和饿了么为例[J]. 经济地理, 2020, 40(12) 119-127.
	Zhai Qing, Gao Yujie, Wei Zongcai. Spatial pattern of online and offline catering service in Nanjing: A case study of dianping and eleme. Economic Geography, 2020, 40(12) 119-127.
[10]	陈蔚珊, 柳林, 梁育填. 基于POI数据的广州零售商业中心热点识别与业态集聚特征分析[J]. 地理研究, 2016, 35(4) 703-716.
	Chen Weishan, Liu Lin, Liang Yutian. Retail center recognition and spatial aggregating feature analysis of retail formats in Guangzhou based on POI data. Geographical Research, 2016, 35(4) 703-716.
[11]	涂建军, 唐思琪, 张骞, 等. 山地城市格局对餐饮业区位选择影响的空间异质性[J]. 地理学报, 2019, 74(6) 1163-1177. doi: 10.11821/dlxb201906007
	Tu Jianjun, Tang Siqi, Zhang Qian et al. Spatial heterogeneity of the effects of mountainous city pattern on catering industry location. Acta Geographica Sinica, 2019, 74(6) 1163-1177. doi: 10.11821/dlxb201906007
[12]	杨帆, 徐建刚, 周亮. 基于DBSCAN空间聚类的广州市区餐饮集群识别及空间特征分析[J]. 经济地理, 2016, 36(10) 110-116.
	Yang Fan, Xu Jiangang, Zhou Liang. Cluster identification and spatial characteristics of catering in Guangzhou based on DBSCAN spatial clustering. Economic Geography, 2016, 36(10) 110-116.
[13]	方嘉雯. 北京五道口地区韩国餐饮业空间布局特征与集聚机理分析[J]. 经济地理, 2014, 34(12) 106-113.
	Fang Jiawen. The distribution characteristics and clustering mechanism of Korean catering service in Wudaokou District, Beijing. Economic Geography, 2014, 34(12) 106-113.
[14]	秦萧, 甄峰, 朱寿佳, 等. 基于网络口碑度的南京城区餐饮业空间分布格局研究——以大众点评网为例[J]. 地理科学, 2014, 34(7): 810-817.
	Qin Xiao, Zhen Feng, Zhu Shoujia et al. Spatial pattern of catering industry in Nanjing urban area based on the degree of public praise from Internet: A case study of dianping. com. Scientia Geographica Sinica. 2014, 34(7): 810-817.
[15]	艾少伟, 乔增轩, 李江苏. 城市民族餐馆空间分布的区位选择及文化邻近性[J]. 人文地理, 2020, 35(3) 76-85.
	Ai Shaowei, Qiao Zengxuan, Li Jiangsu. Location selection and cultural proximity of spatial distribution of urban ethnic restaurants. Human Geography, 2020, 35(3) 76-85.
[16]	曾璇, 崔海山, 刘志根. 广州市餐饮店分布演变特征与影响因素[J]. 经济地理, 2019, 39(3) 143-151. doi: 10.15957/j.cnki.jjdl.2019.03.017
	Zeng Xuan, Cui Haishan, Liu Zhigen. Spatial and temporal evolution characteristics and influencing factors of restaurants in Guangzhou. Economic Geography, 2019, 39(3) 143-151. doi: 10.15957/j.cnki.jjdl.2019.03.017
[17]	赵炜, 程易易, 周麟, 等. 成都市老城中心区特色餐饮空间结构特征研究[J]. 规划师, 2018, 34(10) 93-98. doi: 10.3969/j.issn.1006-0022.2018.10.014
	Zhao Wei, Cheng Yiyi, Zhou Lin et al. Spatial structure characters of special catering industry in the central area of Chengdu. Planners, 2018, 34(10) 93-98. doi: 10.3969/j.issn.1006-0022.2018.10.014
[18]	Porta S, Crucitti P, Latora V. The network analysis of urban streets: A primal approach[J]. Environment & Planning B:Planning & Design, 2005, 33(5) 705-725.
[19]	Al-Saaidy H J E, Alobaydi D. Studying street centrality and human density in different urban forms in Baghdad, Iraq[J]. Ain Shams Engineering Journal, 2021, 12(1) 1111-1121. doi: 10.1016/j.asej.2020.06.008
[20]	Yu W H. Assessing the implications of the recent community opening policy on the street centrality in China: A GIS-based method and case study[J]. Applied Geography, 2017, 89: 61-76. doi: 10.1016/j.apgeog.2017.10.008
[21]	Alattar M A, Cottrill C, Beecroft M. Modelling cyclists’ route choice using Strava and OSMnx: A case study of the city of Glasgow[J]. Transportation Research Interdisciplinary Perspectives, 2021, 9: 100301 doi: 10.1016/j.trip.2021.100301
[22]	Lin G, Chen X X, Liang Y T. The location of retail stores and street centrality in Guangzhou, China[J]. Applied Geography, 2018, 100: 12-20. doi: 10.1016/j.apgeog.2018.08.007
[23]	Wang F H, Chen C, Xiu C L et al. Location analysis of retail stores in Changchun, China: A street centrality perspective[J]. Cities, 2014, 41(pt.A) 54-63.
[24]	Wang F H, Antipova A, Porta S. Street centrality and land use intensity in Baton Rouge, Louisiana[J]. Journal of Transport Geography, 2011, 19(2) 285-293. doi: 10.1016/j.jtrangeo.2010.01.004
[25]	Rui Y K, Ban Y F. Exploring the relationship between street centrality and land use in Stockholm[J]. International Journal of Geographical Information Science, 2014, 28(7) 1425-1438. doi: 10.1080/13658816.2014.893347
[26]	吕永强, 郑新奇, 周麟. 道路网络中心性与城市功能用地空间分布相关性研究——以北京城市中心区为例[J]. 地理研究, 2017, 36(7): 1353-1363.
	Lv Yongqiang, Zheng Xinqi, Zhou Lin, Relationships between street centrality and spatial distribution of functional urban land use: A case study of Beijing central city. Geographical Research, 2017, 36(7): 1353-1363.
[27]	任会明, 叶明确, 祝影. 基于教育网络的上海城市网络空间结构研究[J]. 经济地理, 2019, 39(8) 77-86.
	Ren Huiming, Ye Mingque, Zhu ying. The spatial structure of Shanghai City network based on education network. Economic Geography, 2019, 39(8) 77-86.
[28]	李巍, 赵敏, 严江平, 等. 基于空间互动模型的兰州市乡村旅游网络中心性分析[J]. 地理科学, 2017, 37(7) 1059-1068.
	Li Wei, Zhao Min, Yan Jiangping et al. Rural tourism network centrality of Lanzhou City based on spatial interaction model. Scientia Geographica Sinica, 2017, 37(7) 1059-1068.
[29]	肖琛, 陈雯, 袁丰, 等. 大城市内部连锁超市空间分布格局及其区位选择——以南京市苏果超市为例[J]. 地理研究, 2013, 32(3) 465-475.
	Xiao Chen, Chen Wen, Yuan Feng et al. Spatial pattern and location decision of chain supermarkets within large cities: A case study of Suguo supermarkets in Nanjing. Geographical Research, 2013, 32(3) 465-475.
[30]	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[J]. 地理科学进展, 2016, 35(9) 1155-1166. doi: 10.18306/dlkxjz.2016.09.010
	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. doi: 10.18306/dlkxjz.2016.09.010
[31]	Wei Z C, Zhen F, Mo H T et al. Travel behaviours of sharing bicycles in the central urban area based on geographically weighted regression: The case of Guangzhou[J]. Chinese Geographical Science, 2021, 31(1) 54-69. doi: 10.1007/s11769-020-1159-3

		最小值	下四分位数	中值	上四分位数	最大值	平均值	标准差
餐饮业总体	中介中心性	-1.364	-0.145	-0.025	0.146	2.735	0.034	0.445
	邻近中心性	-1.205	0.005	0.164	0.489	2.802	0.247	0.441
	特征向量中心性	-1.552	-0.032	0.056	0.476	3.422	0.244	0.594
中餐厅	中介中心性	-1.116	-0.146	-0.021	0.177	2.304	0.047	0.428
	邻近中心性	-1.073	0.022	0.220	0.571	2.622	0.306	0.430
	特征向量中心性	-1.934	-0.042	0.044	0.388	3.239	0.198	0.568
西餐厅	中介中心性	-4.823	-0.109	-0.012	0.059	3.774	-0.065	0.723
	邻近中心性	-2.473	-0.068	0.027	0.179	3.737	0.013	0.566
	特征向量中心性	-1.106	-0.015	0.037	0.673	4.424	0.428	0.861
休闲餐饮	中介中心性	-1.580	-0.119	-0.028	0.078	2.063	0.003	0.399
	邻近中心性	-1.763	-0.062	0.075	0.292	3.234	0.095	0.494
	特征向量中心性	-1.125	-0.016	0.042	0.594	3.876	0.340	0.660

道路网络中心性对餐饮业空间布局的影响——以青岛市主城区为例

The Influence of Road Network Centrality on the Spatial Distribution of Catering: A Case Study of Qingdao Main Urban Area

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 31

相关文章 8

Metrics

本文评价

推荐阅读 0

[1]	王强, 崔军茹, 崔璨, 古恒宇. 流动人口购房意愿影响因素的空间异质性——基于MGWR模型的研究[J]. 地理科学, 2022, 42(8): 1381-1390.
[2]	张梦雨, 王强, 朱杰. 福州市外卖O2O与传统餐饮业空间分布特征及影响因素对比[J]. 地理科学, 2022, 42(8): 1463-1473.
[3]	宗会明, 季欣. 1999—2018年重庆市主城区住宅用地空间演变特征及驱动因素研究[J]. 地理科学, 2021, 41(7): 1256-1265.
[4]	丁建军, 金宁波, 王璋, 刘超. 湘渝川滇黔桂地市城镇化减贫效应的异质性及演变特征分析[J]. 地理科学, 2021, 41(3): 522-533.
[5]	刘贤赵, 高长春, 张勇, 张东水, 谢金宁, 宋焱, 王志强. 中国省域碳强度空间依赖格局及其影响因素的空间异质性研究[J]. 地理科学, 2018, 38(5): 681-690.
[6]	隋雪艳, 吴巍, 周生路, 汪婧, 李志. 都市新区住宅地价空间异质性驱动因素研究 ——基于空间扩展模型和GWR模型的对比[J]. 地理科学, 2015, 35(6): 683-689.
[7]	王进欣, 黄巧华, 李超, 张威, 郭楠, 王今殊. 苏北海岸带盐沼生态系统对二氯苯的自然吸收通量特征[J]. 地理科学, 2015, 35(4): 491-497.
[8]	牟晓杰, 孙志高, 刘兴土. 黄河口滨岸潮滩湿地土壤碳、氮的空间分异特征[J]. 地理科学, 2012, 32(12): 1521-1529.