基于地统计的商品住宅价格时空分布研究——以重庆市中心城区为例  

Study on Spatial and Temporal Distribution of Commodity Housing Price Based on Geostatistics--Take the Central City of Chongqing as an Example

作　　者：陈静 何兴富[1] 王国牛[1] CHEN Jing;HE Xingfu;WANG Guoniu(Chongqing Survey Institute,Chongqing 401121,China)

机构地区：[1]重庆市勘测院,重庆401121

出　　处：《城市勘测》2023年第5期9-14,共6页Urban Geotechnical Investigation & Surveying

基　　金：国家重点研发计划项目资助(2018YFB0505400)。

摘　　要：随着我国房地产市场的蓬勃发展,房价问题已成为当前社会各界和学界关注的焦点问题,商品住宅更是关乎民生的重中之重。本文以空间量化研究见长的地统计理论为基础,以重庆市中心城区二手房均价为研究对象,结合链家网站2015—2020年重庆市二手房交易时空大数据,利用探索性空间分析、空间插值、时空立方体等地统计理论、空间数据处理及可视化技术,研究商品住宅价格的空间分布格局和时空演化特征,进而辅助城市管理和决策。研究表明:“房住不炒”提出5年以来,重庆市二手房住宅价格整体上呈现上升趋势;空间上呈现以多个中心为基点、逐渐向外部降低的空间格局;以渝中区为核心的房价高值时空热点聚集效应显著,北碚组团等区域有脱离低值的趋势。With the vigorous development of China's real estate market,the issue of house price has become the focus of attention of all walks of life and academia,and commercial housing is the top priority related to people's livelihood.Based on the geostatistics theory,which is good at spatial quantitative research,this paper takes the average price of second-hand housing in the central urban area of Chongqing as the research object,combined with the time-space big data of second-hand housing transactions in Chongqing from 2015 to 2020 on Lianjia website,and uses exploratory spatial analysis,spatial interpolation,spatial-time cube and other geostatistics theories,spatial data processing and visualization technologies to study the spatial distribution pattern and spatial-temporal evolution characteristics of commodity housing prices,And then assist urban management and decision-making.The research shows that the price of second-hand housing in Chongqing has shown an upward trend as a whole since the proposal of“housing without speculation”was put forward for five years;Spatially,it presents a spatial pattern with multiple centers as the base point and gradually decreasing to the outside;The space-time hot spot aggregation effect of high-value housing prices with Yuzhong District as the core is significant,and Beibei cluster and other regions tend to leave the low value.

关 键 词：房价 地统计 空间格局 时空演化 

分 类 号：P208[天文地球—地图制图学与地理信息工程]