Analysis Of Residential Land Spatial Variability Based On GWR

Land price is the main tool of the government’s macroeconomic regulation and control. Studying the land price and its spatial structure scientifically can provide a reference for calculating urban management, urban planning, the preparation for the program and policies to manage the real estate market. And it improve the theoretical content of the relevant disciplinesIn the past, the research of spatial structure and its influencing factors of land price mostly use qualitative research or linear regression. This approach see the region as a homogeneous space. The evaluation results most use words and tables to express it, and it lack of intuitive. In addition, the formation mechanism of the spatial structure of land price is less mention, and the relationship between the sample data and the surrounding land can not be clearly expressed. So it need to improve the premium impact of technology to help researchers analyze land price formation mechanism better, and then provide the basis for government departments to draft control policies and macro-planning.We use advanced spatial econometric model Geographically Weighted Regression Model (GWR) to research the influence factors of land price. This paper take Jiangning District as an example, collecting residential plot data of2004-2010through the official website and Jiangning District Land Bureau to form the formation of residential land price point. Meanwhile, the collect the residential real estate transaction price data, the use of the Remaining Law to restore land price, and add the land price data to form a relatively complete residential land transfer spatial structure in Jiangning District.After the validation of the data, we use the Kriging to analyze the space distribution of the study area. Analysis found that compared to the other plates, the price of Baijiahu Plates, the Dongshan Plate, Jiulonghu Plates is higher, section of the premium relative to other plates higher, and it gradually decreasing to outside.In the analysis of the impact of urban residential land based on the GWR model, we combined with the results of previous studies and the land price distribution in Jiangning to determine the influencing factors in this study. We can see rate of volume, the subway exit, waters and urban green space, hospitals, airports, living facilities, markets, schools, highway trunk, the CBD as the residential land price factors. We simulation and analysis the residential land price and its factors based on GWR model. Contrast results of the fixed model and the adjust model by the results of the optimal bandwidth, the regression coefficient distribution, events intelligent diagnosis, analysis of variance, Monte Carlo significance test. The result showed that1the adjust model is better thanthe fixed mode. So we use the adjust model. We found the rate of volume, metro, CBD, waters and urban green space was the most significant factors from the result of Monte Carlo significance test.On the basis of calculating the regression coefficients of the117samples, we describes the various factors of the distribution of premium space, and it more intuitive than describing by the text and table.