Research On Spatial Differentiation And Influencing Factors Of Second-hand House Prices In The Third Ring Road Of Wuhan

The urbanization process in Wuhan has promoted rapidly,it boosts development of the real estate industry in Wuhan,and it causes that the housing prices rise rapidly at the same time,which leads to the overheated investment in real estate,and has brought many social problems.In the context of the big data era,house price data and POI data are relatively easy to obtain,which provides data support for house price analysis.This article analyzes the spatial distribution characteristics of housing prices and the factors which can affect the house prices taking the main urban area within the Third Ring Road of Wuhan as a research area.According to these analyses,on the one hand,it can provide some theoretical basis for the relevant departments to grasp the price level of the Wuhan residential market,so as to formulate reasonable and effective policies.On the other hand,it can help residents who purchase houses to choose the ideal housing quickly and reasonably.This article mainly completes the following work:(1)Obtaining Wuhan secondhand housing transaction data in 2019 from Lianjia and POI data which includes business districts,subways,key middle schools,key primary schools,parks,attractions and class 3A comprehensive hospitals.(2)Determine the characteristic variables,including building characteristic variables such as age,area,total floor,location characteristic variables such as distance to rivers and lakes,distance to subway stations,distance to commercial districts,distance to key middle schools,distance to key elementary schools,distance to parks,distance to attractions and distance to class 3A comprehensive hospitals.The correlation coefficient matrix was constructed to exclude the three variables of house age,key elementary schools and scenic spots,and finally the remaining 9 feature variables participated in the regression analysis.(3)Respectively,the Hedonic price model and the GWR model are used to regress the unit price of the house and 9 characteristic variables,and the factors which can influence of house prices are analyzed according to the GWR regression results.The study draws the following main conclusions:(1)Judging from the spatial trend of housing price distribution,the housing prices of second-hand houses in the Third Ring Road of Wuhan present an inverted “U” shaped curve distribution.The housing prices as a whole show significant spatial agglomeration,while local areas have spatial differences.(2)Judging from the results of house price interpolation,the spatial distribution pattern of housing prices in Wuhan in 2019 shows an obvious multi-center distribution.The high-price areas are mainly distributed in the Yongqing area along the Hankou River Beach,the Jiyuqiao area in Wuchang,and area near the fruit lake.The low-price areas are mainly concentrated in the areas near the Third Ring Road,and the low-price areas in Hanyang are larger.(3)Eestablish the Hedonic price model and GWR model of second-hand house prices and their influencing factors.Among the three forms of the Hedonic price model,the half-logarithm model has the best results,while the GWR model has a better fitting effect than the half-logarithm model..According to the median of the influencing factor coefficients in the GWR results,it is found that different characteristic variables have different influences on second-hand house prices.The total floor has a greater impact on house prices among the architectural features.The higher the total floor,the higher the house price.The key middle schools have the greatest influence on house prices among the location characteristics and neighborhood characteristics.The closer to the key middle school,the higher the house price.The coefficients of impact factors are interpolated by Kriging interpolation tool in Arc GIS and the impact of factors on housing prices are analyzed.It is found that the construction area factor has the most significant influence near Wuhan Tiandi in the Yongqing area,the total floor factor has the most significant influence in the central area.The subway station has a greater impact on the area near the Third Ring Road,while the impact on the city center is smaller.Among rivers and lakes,Hankou River Beach,Wuchang River Beach and the surroundings of East Lake have a greater impact.The business district has the most obvious influence on Wuchang among three towns.From the perspective of educational resources,key middle schools have a greater impact on Wuchang District and Jiang’an District.These two regions have more high-quality key middle schools.The impact of the park in the central area is more significant,and the peripheral area and the area around lakes such as East Lake and South Lake are less affected.The impact of the class 3A comprehensive hospitals on house prices changes with distance.When the distance is too close,the farther away from the hospital,the higher the house price.When the distance to the hospital is moderate,the farther away from the hospital,the lower the house price.While after exceeding a certain range,the greater the distance from the hospital,the higher the house price.