Research On The Spatial Variation And The Influencing Factors Of Beijing's Housing Rent Based On GWR Model

With the rapid urbanization process in China,there are serious imbalance of the economic development levels in different cities.Cities with dominant resources attract a large number of migrant population.The first-tier cites in China,such as Beijing,Shanghai,Shenzhen,etc.,attract a large number of migrant population every year with resort to its rich jobs and various material and cultural life.With the growing number of floating population in cites,the demand of housing is increasing.However,the housing price of the first-tier cities is generally at a high level,which has head and shoulders above the ability to afford for most of the salariat,therefore,a growing number of people choose to rent house.Nevertheless,in recent years,large quantities of property investors have rushed into housing rental market,resulting in the sharp rise of housing rent and the housing is increasing outstanding.Housing is all important to the national economy and the people's livelihood,the spatial variation and influencing factors of housing rent deserve to be discussed.However,the current research is mainly focused on the residential price,research on housing rent is not sufficient.Therefore,this paper takes six core districts and outskirts in Beijing comes to twelve districts as the study area,crawls the rental data from Ziroom website in March,2019 by using Python,research the spatial variation characteristics of Beijing's housing rent by using correlation analysis,multiple stepwise regression,GIS spatial analysis,Geographically weighted regression,LMG,and analyze the influence degree of different influencing factors on housing rent.This research mainly includes the following contents:1.The spatial distribution characteristics of entire or shared housing rent had been studied by using GIS spatial analysis.Found that the housing rent within the study area is generally concentric circles,namely,the housing rent in the central circle is high and gradually decreases outward;the overall trend is higher in north lower in south,the northern housing rent downward gradient is slower than the south,the housing rent level is relatively balanced in the east-west direction and presents radial distribution along the metro line.The spatial distribution characteristics of the entire rent and shared rent are the same on the whole,whereas the distribution of the central circle is slightly different.2.Linear regression model and geographically weighted regression model with housing rent and influencing factors is established.According to the result of regression model,quantitatively analyzing the impact of various influencing factors on the entire rent and shared rent.The spatial variation of influencing factors and housing rent is visualized in the forms of map and qualitatively describing the spatial variation characteristics of different influencing factors,then expounding the reason for the spatial variation of housing rent forms.According to the analysis result,we found that the relative importance of the factors affecting the shared and entire rent is quite different.job accessibility,private toilet and subway stations have the greatest influence on shared rent,while floor area,job accessibility,and house type have the greatest influence on entire rent.Bus station performs relatively low influence degree to both shared and entire rent.Therefore,the government should balance the spatial distribution of job accessibility and improve the job accessibility in the outskirts.