摘要
城市住房与居住空间格局深刻反映着城市地域上的社会经济状况,是认识城市及其空间结构的重要视角。从住房租金考察居住空间分异是城市居住空间研究的新领域,利用住房租金特征指标研究西安城市居住问题,用定量方法揭示西安市居住空间的分异规律。依据西安市主城区2014年7月份的964处住房租金交易信息,借助GIS、SPSS、Sufer等软件对西安市主城七区住房租金的空间分布以及影响因素进行分析研究。研究结果表明:(1)西安市可供出租的住房主要集中在城市中心偏南的雁塔区、碑林区和莲湖区;(2)西安市住房租金呈现出"中心高、四周低"的空间格局与"居住郊区化"的趋向性,雁塔区租金普遍较高,最高值出现在曲江街道办,长安区租金普遍较低,最低值出现在引镇街道办;(3)通过回归分析,综合西安市主城七区所有租房交易数据,得出影响租金影响因素主要有住房配套设施、装修情况以及商服设施等。本研究具有一定的实用价值,可以为制定相关政策提供理论依据。
Urban housing and living spatial pattern in cities,which is the important visual to recognize cities and their spatial structure,deeply reflects the society economy conditions.It is a new field of residential space analysis to study residential problems from the point of view of residential rents,which provides quantitative analysis method on spatial differentiation law of urban housing.Based on 964 homes' transaction information in Xi'an's seven central districts in July,2014,this paper uses ArcGIS and Sufer software to explore the spatial distribution characteristics and its factors of residential rents in Xi'an's seven districts,and uses SPSS software to discuss the factors affecting the residential rents.The conclusions from the analysis include:(1) The rental housing mainly concentrated within the central-south districts(Yanta,Beilin and Lianhu);(2) the spatial distribution of residential rents takes on a pattern of "center around the high low" and " residence suburbanization",Yanta District has generally high rents,the highest appears in Qujiang subdistrict;Chang'an district has generally low rents,the lowest appears in Yinzhen subdistrict;(3) By means of regression analysis,the main factors affecting the residential rents such as residential facilities,decoration and commercial service facilities have been found.This study has a practical significance,which can provide theoretical reference for policy making.
出处
《西部人居环境学刊》
2015年第4期77-81,共5页
Journal of Human Settlements in West China
基金
国家自然科学基金(41171142)
陕西师范大学中央高校基本科研业务费项目(GK201401006)
关键词
住房租金
空间分布
影响因素
西安市
Residential Rents
Spatial Distribution
Influence Factor
Xi'an City