Research On The Spatial Variation Of The Urban Housing Land Prices Of Fuzhou

Urban housing land prices are closely related to people’s basic living and the healthy development of the society. As the result of a variety of factors functioning together in inner city, Urban housing land prices can also reflect the comprehensive development level and the pros and cons of urban land. The influencing factors of Urban housing land prices are various and complex. And each of them is always changing with the social and economic development, which leads to urban housing land prices being different not only among cities, but also in inner city. Exploring the differentiation mode of the urban housing land price and the impact of various factors on the premium contributes to a clearer understanding of the formation and mechanism of change of the urban housing land prices. Revealing the distribution pattern of urban housing land price and its influencing factors is of great theoretical and practical significance to the development of the urban land market, the government’s macro-control, and the relative theories of urban land.In this paper, based on the existing land price differentiation theories and research methods, this paper does empirical research on the housing market in Fuzhou. Besides, applying exploratory spatial to analyze the housing land price in the space as a whole autocorrelation and spatial partial autocorrelation and the method combining the statistical analysis with GIS spatial analysis and using Kriging spatial interpolation of land price data, this paper explores the differentiation mode of Fuzhou housing land price. And through the establishment of linear regression models and geographically weighted regression model, it analyzes urban housing land prices and its impact the correlation between the factors and finds the reasons that cause spatial variation of urban housing land price. In this study, the conclusions are as follows:(1) time correcting the Housing land prices in Fuzhou City. The corrected data is not normal, and land prices there show obvious quadratic trend on both east-west direction and the north-south direction. Moran’s I index, Moran scatterplot, LISA gathering Figure indicate that there are agglomeration effects, regardless of the space as a whole or in space local housing land prices.Through trend analysis, a conclusion can be reached:whether it is from north to south or from west to east, housing land prices gradually increase from the edge of the city to its center, to the center of the city and to its surroundings, reaching its maximum value, and then slowly decrease from the city center to the edge of the city.The center of Fuzhou city, which also refers to the places near Dong jie kou. it owns Apartments nearby premium and its surrounding area Apartments premium; GMA estate price level is relatively low and the housing premium for its peripheral region is at a lower level; the vast majority of other regions high premium is surrounded by low land or low land surrounded is surrounded by the defendant land prices. It is a relatively common phenomenon in the study area.(2) by applying the ordinary Kriging spatial interpolation into the Fuzhou housing land price data, it can be concluded that the distribution of the Fuzhou housing land price are double-core spatial structure. Land prices change outward from the the Drum Tower the circle center taijiang circle center. Within the Second Ring Road, land prices still hold at a higher level. The land price reaches its peak in the north side of the Square guanglu, mainly because Guanglu Square is located in the Gulou District San Fang Qi Xiang historical and cultural district, and is also near to the city center Dong Jie Kou, thus forming the highest point of the land price. Land prices gradually drop out of the circle in the lower edge of the city region and change smoothly, which arrives to the lowest in the Jinshan housing area, Cangshan district, the eastern part of Metro and north of Jinan Metro.(3) Through the establishment of the general linear regression model and geographically weighted regression model, it proves that Fuzhou housing land prices are affected not only by their own factors but also by the peripheral location elements. There is negative correlation between the distance of the city center, with the Park, the volume rate and the housing land prices. The housing land prices are positively correlated with the distance of supermarkets, shopping malls, and the fast road distance. By comparing the linear regression model with Geographically Weighted Regression Model, it concludes that the ground weighted regression model can better justify the the degree of correlation between housing land price and its influencing factors.