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| POI-BASED ANALYSIS ON THE AFFECTING FACTORS OF PROPERTY PRICES' SPATIAL DISTRIBUTION IN THE TRADITIONAL INDUSTRIAL AREA |
| XUE Bing1,2, XIAO Xiao1,2, LI Jing-zhong2,3, XIE Xiao1,2, REN Wan-xia1,2, LU Cheng-peng1,2, JIANG Lu1,2,4 |
1. Key Lab of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;
2. Key Lab for Environmental Computation and Sustainability of Liaoning Province, Shenyang 110016, China;
3. College of Urban Planning and Architecture, Xuchang University, Xuchang 461000, China;
4. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China |
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Abstract Based on the residential POI data of the Tiexi District in Shenyang, a geographical weighted regression (GWR) model was constructed by adding three variables that could affect the traditional industrial area's property prices as well as the traditional variables, the three added variables include house age, residential density and the distance between residences and industries. The results show that:house age, residential density, public transport, public facilities and so on have a significant effect on property prices, while industrial enterprises and other factors have a certain effect on price inhibition. The relativities between all kinds of influence factors and residential prices have remarkable spatial non-stationary, showing that the intensity gradient of the regression coefficient of one-way influencing factors such as residential density, subway station distance, as well as the difference between the positive and negative effects of factors such as factory distance, bus density, shopping mall distance in the traditional and new urban areas.
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Received: 10 April 2018
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2019, Vol. 34 
