Study On The Influential Factor Of Commercial Housing Price By GIS

Housing as a commodity, which is indispensable of city life, whether it is government, real estate developers and urban residents are highly concerned about the change in its price. The spatial position affects the housing price to a large extent. Housing price vary considerably in different locations. Therefore, studying housing price combined with the geographical position becomes so necessary. This paper, Chengdu an the research object, study the space distribution rule and influence factors of urban commodity residential housing price, combined GIS with the Hedonic price model.In this paper, starting from the collecting and sorting data, first write program to obtain automatically the commodity residential house data listed from soufun, then take simple pretreatment, and outlier analysis., finally determine the study data for 567. Then based on ArcGIS technology platform, do trend analysis, interpolation analysis and cluster analysis to the house price, mastering the spatial distribution characteristic of the commodity residential housing price of Chengdu on the whole; Finally, embarking from the micro level, use the Hedonic model to analyze the influencing factors of Chengdu’s housing price, and draw the following conclusion:To the study area of this article, Gao-xin zone has the highest housing price and PI county has the lowest housing price. Overall, the center of city and extending southward to Gao-xin zone are the core of housing price. Housing price is gradient descent. Falling grades, while part of the bulging area, spatial variation phenomenon is obvious. Housing price of Chengdu overall present spatial agglomeration phenomenon. Namely, the high price is in a certain region of space, low price is in another region of space, and housing price is in the continuous space. In addition, both the central city and surrounding county have the phenomenon that the price of south is higher than the north. Combination of chengdu road loop circle and housing price, find chengdu housing price has obvious envelops effect, but not strictly follow the road to the distribution ring. Subsequently, using the location characteristics, construction characteristics and neighborhood characteristics three types of 15 variables as independent variables, establish chengdu housing Hedonic model, to study the influencing factors of housing prices and degree of results show that the factors that affect the housing prices are 11, and the characteristics of 11 have different degrees of influence on prices.