多组团山地城市房价时空分布特征及影响因素分析  

Analysis of Influencing Factors and Changes in the Temporal and Spatial Patterns of Housing Prices in Multi-clusters of Mountainous Cities

作　　者：何建 戴技才[1,2] He Jian;Dai Jicai(School of Geography and Tourism,Chongqing Normal University,Chongqing 401331,China;Chongqing University Key Laboratory of Geographic Information System Application Research,Chongqing 401331,China)

机构地区：[1]重庆师范大学地理与旅游学院,重庆401331 [2]地理信息系统应用研究重庆市高校重点实验室,重庆401331

出　　处：《绿色科技》2023年第7期234-240,共7页Journal of Green Science and Technology

基　　金：国家自然科学基金(编号:42071217);教育部人文社科规划基金项目(编号:20XJAZH002)。

摘　　要：针对多组团山地城市房价时空分布特征及影响因素不同于平原城市的问题,以重庆市2015、2020年住宅价格为研究单元,利用500m格网分析、空间自相关、地理加权回归(GWR)等方法分析重庆市房价的时空分布特征及影响因素。结果表明:重庆市房价总体呈上升趋势,各组团房价涨幅不同。空间上房价具有显著的正相关性,高-高和低-低聚类是主要的空间聚类模式,总体上表现为“多中心,组团式”结构。GWR模型分析发现,住宅房龄、中心位势对五大商圈组团房价影响最大,超市配套、轻轨配套、服务管理对近郊组团房价影响最大,景观稀缺对沿江组团影响减弱。The spatial and temporal distribution characteristics and influencing factors of housing price in multi-cluster mountain cities are different from those in flat cities.This paper takes the housing price of Chongqing in 2015 and 2020 as the research unit.500m grid analysis,spatial autocorrelation,geographical weighted regression(GWR)and other methods are used to analyze the spatial and temporal distribution characteristics and influencing factors of housing price in Chongqing.The results show that:the overall housing price of Chongqing is on the rise,but the price increase of each group is different.In terms of spatial housing price,there is a significant positive correlation.High-high and low-low clustering are the main spatial clustering patterns,which generally shows a"multi-center and group-type"structure.GWR model analysis shows that the housing age and central location have the greatest impact on the housing price of the five business districts.The supermarket,light rail and service management have the greatest impact on the suburban housing price,and the landscape scarcity has a weaker impact on the riverside housing price.

关 键 词：房价 时空分布 影响因素 组团 地理加权回归 

分 类 号：F726[经济管理—产业经济]