利用MGWR模型分析深圳市商品住宅租金空间影响因素  

Research on the Influence Factors of Commercial Housing Rent in Shenzhen City Based on MGWR Model

作　　者：甘金宝 韩念龙 林舒林 莫家静 尹辉 GAN Jinbao;HAN Nianlong;LIN Shulin;MO Jiajing;YIN Hui(School of Geography and Tourism,Huizhou University,Huizhou 516000,China)

机构地区：[1]惠州学院地理与旅游学院,广东惠州516000

出　　处：《地理空间信息》2025年第3期51-53,76,共4页Geospatial Information

基　　金：惠州学院科研启动资助项目(2022JB080);惠州哲学社会科学规划资助项目(HZ2023GJ145);广东省大学生创新创业训练计划资助项目(S202310577050)。

摘　　要：在深圳市人口规模大、住房租赁需求高的背景下,研究租金空间分异规律和影响因素对促进住房租赁市场的健康发展具有重要意义。基于深圳市商品住宅租金和POI数据,通过内生因素、区位特征和邻里特征构建深圳市商品住宅租金特征价格模型,并利用多尺度地理加权回归(MGWR)模型探索各因素对住宅租金影响的空间分异规律。结果表明,MGWR模型具有更好的拟合优度,各因素对租金的影响存在显著的空间差异。Under the background of large population size and high demand for housing rent in Shenzhen City,it is of great significance to study the spatial differentiation of rent and its influence factors to promote the healthy development of housing rent market.Based on the commercial housing rent and POI data in Shenzhen City,we constructed a characteristic price model of commercial housing rent by endogenous factors,location and neighborhood characteristics,and used multi-scale geographically weighted regression(MGWR)model to explore the spatial differentiation rules of influence of each factor on rent.The results show that MGWR model performs better than the traditional models,and there is significant spatial differentiation in the effects of factors on rent.

关 键 词：MGWR 商品住宅租金 空间分异 深圳市 

分 类 号：P208[天文地球—地图制图学与地理信息工程]