Urban Land Price Spatial Distribution Pattern And Influence Factors Analysis

Urban land price is the consequence of urban land’s geographical environment quality different. From an economic point it reflects the relationship between human and land, and to some extent reflects urban land use activities’spatial layout. Having difference in spatial distribution, urban land price shows that different location has different land price, and form land price’s spatial distribution pattern. With the development of GIS technology, GIS application domain is gradually expanding. GIS developing and perfecting in drawing, spatial analysis, data management provides a strong supporting role for the research on urban land price analysis. Applying GIS to analyse land price’s spatial distribution pattern, reveals spatial distribution regularity, and qualitatively analyse the causes. Urban land price influence factors analysis has the trend from qualitative analysis to quantitative analysis. The method of rough set can dig out the inner objective regularity only according to the data itself, avoiding the inaccuracy caused by subjective factors. However, the rough set method of a single attribute importance to determine attribute weights appears that attribute weights are zero and attribute weights are equal which does not conform to the actual situation, and ignore the mutual influence between the two factors. In order to solve these problems, with an improved rough set method which combining a single attribute importance with combined attribute importance determine attribute weights quantitatively analyse land price influence factors.In this paper, residential land, commercial land and industrial land as the research object, with GIS technology analyse spatial data (such as point pattern analysis, spatial correlation analysis, statistical analysis), acquire various land use types’land spatial distribution pattern; Based on rough set theory, quantitatively analyse various land use types’ decision attribute table data with improved rough set, acquire various land use types’influence factors, and give intuitively explanation to land price’s spatial distribution pattern. Paper main research contents are as follows:(1) Classify research data, classify the urban land price data as residential land, commercial land and industrial land, and number one by one according to the different category. Then modify the data, calculate sample land price, and map sample land price with ArcGIS software.(2) With nearest neighbor domain analysis of point pattern analysis analyse spatial distribution characteristic of space objects, do spatial autocorrelation analysis synthetically considering space objects’land attribute information and location information, use QQPlot analyse normality, using ordinary kriging interpolation obtain various land use types’land price spatial distribution pattern on the basis of land price data meeting the normality and spatial correlation.(3) Through GIS buffer analysis and range analysis analyse spatial data, obtain study area’s land price attribute values, dimensionless standardise and discretize influence factors and land price values, establish decision attribute table.(4) With C#programming language realize the calculation of land price influence, factors’attribute importance and weight based on an improved rough set method, acquire each land use type’s land price influence factors and influence size according to the values of weights, compare the results acquired by the rough set method that single attribute importance determin weight with the improved rough set method. Results show that with the improved rough set method obtain the ideal results. The improved rough set method eliminates the condition that attribute weights are0and attribute weights are equal. And at the same time give a reasonable explanation to the land price spatial distribution pattern.The above research provides scientific reference basis for related government department arranging land use and determining land use intensity, improving land use efficiency, etc., provides a certain reference value for urban residents purchase, and provides a new perspective to study the influence factors of urban land price.