Font Size: a A A

Study On Spatial Differentiation Of The Housing Price And Its Influencing Factors In Fuzhou

Posted on:2020-11-10Degree:MasterType:Thesis
Country:ChinaCandidate:L M WuFull Text:PDF
GTID:2439330620956989Subject:Physical geography
Abstract/Summary:PDF Full Text Request
The formation of urban housing price is the result of the combined action of various factors in the urban area,which can reflect the urban location and the level of urban comprehensive development.The analysis of the spatial differentiation law of urban housing price and its driving force influence mechanism can provide a more powerful theoretical basis for the supervision of the real estate market.This study takes the second-hand housing in the central urban area within the five urban areas of fuzhou city as the research object to explore the spatial differentiation of housing prices and analyze its influencing factors.The results show that the housing prices in the study area show an inverted u-shaped distribution,and show a very significant polycentric annular decline pattern,which is manifested in the large change of price gradient within the central radiation range,and irregular variation of price gradient outside the central radiation range.Then OLS,GWR and MGWR regression models were constructed to quantitatively study the different effects of various influencing factors on spatial differentiation of housing prices.The results showed that the fitting degree of OLS regression model was not high,and the adjusted R2 value was only 0.5143.Subsequently,through the study on the non-stationarity of the GWR model's regression coefficient space,it is confirmed that the regression coefficient of most influencing factors changes with the change of space,and only the middle school distance and the degree of influence of interference factors on the housing price do not change significantly in space.Further research on the results of MGWR model shows that: among global variables,there is a significant negative correlation between the distance of middle school and housing price.Among local variables,subway distance,hospital distance,CBD distance,minjiang distance and park distance were negatively correlated with housing price.However,the distance between railway station(bus station)and square changed significantly with the spatial location.
Keywords/Search Tags:Urban residential price, residential price space differentiation, OLS regression model, geographically weighted regression model(GWR), mixed geographic weighted regression model(MGWR)
PDF Full Text Request
Related items