基于POI数据的西安市零售业空间格局及影响因素研究

doi:10.13249/j.cnki.sgs.2020.05.005

地理科学 ›› 2020, Vol. 40 ›› Issue (5): 710-719.doi: 10.13249/j.cnki.sgs.2020.05.005

基于POI数据的西安市零售业空间格局及影响因素研究

高岩辉¹(), 杨晴青²(), 梁璐¹, 赵永宏¹

1.西安外国语大学旅游学院/人文地理研究所,陕西西安710128
2.陕西师范大学西北国土资源研究中心,陕西西安710119

收稿日期:2018-12-31 修回日期:2019-03-27 出版日期:2020-05-10 发布日期:2020-08-18
通讯作者: 杨晴青 E-mail:rwdl_gyh@163.com;yqq@mails.ccnu.edu.cn
作者简介:高岩辉（1981-）,男,山东滨州人,讲师,博士,主要研究方向为区域发展、劳动力转移等。E-mail: rwdl_gyh@163.com
基金资助:
国家自然科学基金项目(41871168);国家自然科学基金项目(41831284);陕西省自然科学基础研究计划项目(2018JM4006);陕西省自然科学基础研究计划项目(2018JM4022);中央高校基本科研业务费专项资金项目(GK202003100)

Spatial Pattern and Influencing Factors of Retailing Industries in Xi'an Based on POI Data

Gao Yanhui¹(), Yang Qingqing²(), Liang Lu¹, Zhao Yonghong¹

1. School of Tourism & Research Institute of Human Geography, Xi'an International Studies University, Xi'an 710128, Shaanxi, China
2. Northwest Land and Resource Research Center, Shaanxi Normal University, Xi'an 710119, Shaanxi, China

Received:2018-12-31 Revised:2019-03-27 Online:2020-05-10 Published:2020-08-18
Contact: Yang Qingqing E-mail:rwdl_gyh@163.com;yqq@mails.ccnu.edu.cn
Supported by:
National Natural Science Foundation of China(41871168);National Natural Science Foundation of China(41831284);Shaanxi Province Natural Science Basic Research Program(2018JM4006);Shaanxi Province Natural Science Basic Research Program(2018JM4022);Fundamental Research Funds for the Central Universities(GK202003100)

摘要/Abstract

摘要：

基于POI数据,利用核密度估计、缓冲区分析等方法刻画西安零售业空间集聚状态,确定零售业分布核心范围,并利用双变量空间自相关分析、近邻分析等方法探究零售行业之间的空间集聚关系,以及零售业与居住小区、交通因素的空间关系。研究表明： ① 西安市零售业呈“中心-外围”结构,以钟楼为中心连片集聚分布,在距离钟楼16 km范围内为零售业分布核心区,在阎良、高陵、临潼、鄠邑4个郊区呈“孤岛”状集聚。② 文化、体育用品及器材零售,纺织、服装及日用品零售业更倾向于在内城分布,而汽车、摩托车、零配件和燃料及其他动力销售业,五金、家具及室内装饰材料零售集中在租金低但交通方便的城市中心外围。③ 集聚效应、人口分布与路网影响零售业的空间分布。与居民日常生活关系密切的零售行业如综合零售,食品、饮料及烟草制品零售,纺织、服装及日用品零售等在空间上集聚以接近消费者,分享消费市场和空间场地,而耐用品零售行业如汽车、摩托车、零配件销售业,家具及室内装饰材料零售等倾向于自身集聚,以共享品牌效应。交通干线尤其是城市二级道路明显影响零售网点的空间分布。

关键词: 零售业, POI数据, 核密度, 空间自相关, 西安

Abstract:

In the long-term evolution and competition, the spatial pattern of retailing industries reflects the rules of location selection and residents' needs. Based on POI data, the spatial pattern of retailing industries in Xi'an is analyzed. The spatial distribution pattern and agglomeration state of retailing industries sub sectors are analyzed by using Kernel density estimation, and bivariate spatial autocorrelation, nearest neighbor analysis method. The main conclusions are as follows: 1) Because of close relative to urban residents' daily life, retailing industries' spatial agglomeration reflects the distribution pattern of the urban center and the scope of the economically active area in Xi'an. The overall structure of the retailing industries in Xi'an is classical ‘center-periphery’, with the Bell Tower at the center, and the area within 16 km from the bell tower. The retailing industries act as a ‘single island’ in the four outer suburbs peripheral, Yanliang, Gaoling, Lintong and Huyi. 2) The spatial distribution characteristics of retailing are related to the residents' aligned consumption frequency. Products retailing with large daily consumption tend to be located in inner-city, while the product retailing with durable consumer goods, especially the products that need to occupy a large site, tend to be the peripheral area. The retailing of culture/sports goods and equipment, the retailing of textiles/clothing and daily necessities tend to distribute in inner-cities, while the retailing of automobiles, motorcycles, spare parts/fuel/other power, and the retailing of hardware, furniture and interior decoration materials are more inclined to distribute in the periphery area in Xi'an. 3) The comprehensive retailing, the retailing of food/beverage and tobacco products, the retailing of textiles/clothing and daily necessities, and the retailing of medicine and medical equipment tend to be centralized, to get close to consumers, and share the consumption market and space. While the retailing of automobile, motorcycle, spare parts/fuel/other power, and the retailing of hardware, furniture and interior decoration materials tends to be centralized itself obviously to share the brand effect. The spatial distribution of retailing outlets is obviously affected by traffic hubs, trunk lines, especially urban secondary roads.

Key words: retailing industries, POI, kernel density, bivariate spatial autocorrelation, Xi'an

中图分类号:

K902

高岩辉, 杨晴青, 梁璐, 赵永宏. 基于POI数据的西安市零售业空间格局及影响因素研究[J]. 地理科学, 2020, 40(5): 710-719.

Gao Yanhui, Yang Qingqing, Liang Lu, Zhao Yonghong. Spatial Pattern and Influencing Factors of Retailing Industries in Xi'an Based on POI Data[J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(5): 710-719.

图/表 9

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零售业行业分类（代码）	POI分类	数量(个)	比例(%)
综合零售（521）	商场、综合批发市场、超市、商店、便利店等	8371	26.12
食品、饮料及烟草制品专门零售（522）	蔬菜水果粮油、糕点食品、烟酒、饮品等	4456	13.90
纺织、服装及日用品专门零售（523）	服装、饰品、鞋、皮具、眼镜、化妆品,其他日用品	5053	15.77
文化、体育用品及器材专门零售（524）	书店、音像、文体办公、珠宝钟表玉石、摄影器材、花卉、水族宠物、体育户外用品等	2286	7.13
医药及医疗器材专门零售（525）	药店、医疗器械等	2579	8.05
汽车、摩托车、零配件和燃料及其他动力销售（526）	电动车、摩托车、自行车销售及零配件等	1143	3.57
家用电器及电子产品专门零售（527）	家电、电器、手机通讯、电脑等	1993	6.22
五金、家具及室内装饰材料专门零售（528）	建材家居、厨卫水暖、陶瓷灯饰、家具、五金钢材建材、窗帘布艺	6166	19.24
货摊、无店铺及其他零售业（529）^*

行业代码	521	522	523	524	525	526	527	528
521		0.506	0.426	0.427	0.497	0.093	0.305	0.142
522			0.405	0.393	0.449	0.063	0.297	0.109
523				0.397	0.355	0.047	0.251	0.081
524					0.344	0.050	0.264	0.096
525						0.097	0.266	0.136
526							0.042	0.015
527								0.083
528
全局空间自相关	0.609	0.548	0.460	0.529	0.509	0.144	0.298	0.394

基于POI数据的西安市零售业空间格局及影响因素研究

Spatial Pattern and Influencing Factors of Retailing Industries in Xi'an Based on POI Data

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