基于社区特征分析的扬州市居住−服务业空间关联及机理

doi:10.13249/j.cnki.sgs.2020.07.010

地理科学 ›› 2020, Vol. 40 ›› Issue (7): 1134-1141.doi: 10.13249/j.cnki.sgs.2020.07.010

基于社区特征分析的扬州市居住−服务业空间关联及机理

王丹¹^,²(), 方斌¹^,*(), 张军², 陈正富³

1. 南京师范大学地理科学学院，江苏南京 210023
2. 扬州市职业大学资源与环境工程学院，江苏扬州 225009
3. 江苏易图地理信息科技股份有限公司，江苏扬州 225009

收稿日期:2019-08-13 出版日期:2020-07-10 发布日期:2020-12-07
通讯作者: 方斌 E-mail:yzwangdan@qq.com;wenyanfang731@163.com
作者简介:王丹（1982−），男，江苏扬州人，副教授，博士研究生，主要研究方向为城市与区域规划。E-mail: yzwangdan@qq.com
基金资助:
国家自然科学基金项目（41671174）、江苏省高校哲学社会科学研究基金项目（2018SJA1167）、江苏省社会教育重点课题（JSS-B-2018004）资助

Residential-Service Industry Space Association and Mechanism in Yangzhou City Based on Community Characteristics

Wang Dan¹^,²(), Fang Bin¹^,*(), Zhang Jun², Chen Zhengfu³

1. School of Geography Science, Nanjing Normal University, Nanjing 210023, Jiangsu, China
2. Department of Resource & Environment Engineering, Yangzhou Polytechnic College, Yangzhou 225009, Jiangsu, China
3. Jiangsu E-Map Geographic Information Engineering Co. Ltd., Yangzhou 225009, Jiangsu, China

Received:2019-08-13 Online:2020-07-10 Published:2020-12-07
Contact: Fang Bin E-mail:yzwangdan@qq.com;wenyanfang731@163.com
Supported by:
National Natural Science Foundation of China (41671174), The Philosophy and Social Science Fund of Education Department of Jiangsu Province (2018SJA1167), Key Projects Supported by Social Education Planning of Jiangsu Province (JSS-B-2018004).

摘要/Abstract

摘要：

基于目视调查等方法获取扬州市主城区社区尺度居住空间的物质、社会、经济特征数据，并将之与社区服务业POI数量、密度、多样性指标进行关联分析。结果表明：社区居住空间的物质、社会、经济特征与服务业空间的数量、密度、多样性特征存在关联关系，其中居住空间的建筑年代、人口数量、年龄结构为主关联因子，居住与服务业空间关联过程分为差异化居住空间形成、差异化人群集聚与消费特征形成、消费特征与服务业空间协同演化3个阶段。

关键词: 空间关联, 居住空间, 服务业空间, 兴趣点（POI）, 目视调查法, 扬州

Abstract:

Due to the lack of material, economic, and social data, the research on the spatial association of residential space and service industry space in China is mostly concentrated on the city level, and there is little analysis on spatial association of residential space and service industry space from the perspective of community and multilevel. Based on the visual survey, the data of the material, social and economic characteristics of residential space of communities in Yangzhou, a famous historical and cultural city, were obtained. Ordinary least squares (OLS) and geographically weighted (GWR) regression was used to study the relationship between these characteristics and the number, density and diversity of service industry POI. The result shows that: The building age, population and population age structure are the main factors in the association. The building age is negatively correlated with the POI number, density and diversity index of service industry; the population number is positively correlated with the POI number, density and diversity index of service industry, the middle age ratio is positively correlated with the POI number of service industry, the youth ratio has a negative correlation with the POI density of service industry, and the aging ratio has a negative correlation with the diversity index of service industry. Based on the OLS and GWR regression analysis, the process of spatial association between residential space and service industry space can be divided into three stages: The formation of differentiated residential space, the formation of differentiated population agglomeration and consumption characteristics, and the collaborative evolution of consumption characteristics and service industry space. The spatial association between residential space and service industry space reflects the continuous interaction process of residential space (place)-people agglomeration (person)-service industry space (place).

Key words: spatial association, residential space, service industry space, point of interest (POI), visual survey, Yangzhou

中图分类号:

F259.23

王丹, 方斌, 张军, 陈正富. 基于社区特征分析的扬州市居住−服务业空间关联及机理[J]. 地理科学, 2020, 40(7): 1134-1141.

Wang Dan, Fang Bin, Zhang Jun, Chen Zhengfu. Residential-Service Industry Space Association and Mechanism in Yangzhou City Based on Community Characteristics[J]. SCIENTIA GEOGRAPHICA SINICA, 2020, 40(7): 1134-1141.

图/表 5

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图 4

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因变量	自变量	最小二乘关联模型		地理加权回归模型
因变量	自变量	相关系数	概率	平均值	中间值
数量特征	建筑年代	?6.96	0.00^*	?7.54	?7.08
	人口数量	0.01	0.00^*	0.12	0.11
	住宅均价	?0.01	0.07^*	?0.06	?0.06
	中年比	2.52	0.06^*	2.74	2.44
	校正可决系数	0.53		0.68
密度特征	社区面积	?0.00	0.02^*	?0.00	?0.00
	建筑年代	?0.21	0.00^*	?0.22	?0.22
	青年比	?0.05	0.04^*	?0.05	?0.05
	校正可决系数	0.56		0.59
多样性特征	建筑年代	?0.03	0.00^*	?0.04	?0.04
	人口数量	0.00	0.14^*	0.00	0.00
	老龄比	?0.03	0.01^*	?0.03	?0.02
	中档车占比	0.01	0.06^*	0.01	0.01
	校正可决系数	0.42		0.51

基于社区特征分析的扬州市居住−服务业空间关联及机理

Residential-Service Industry Space Association and Mechanism in Yangzhou City Based on Community Characteristics

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