SPATIAL DIFFERENTIATION AND INFLUENCING FACTORS ANALYSIS OF HOUSING PRICES IN NANJING: BASED ON GEOGRAPHICALLY WEIGHTED REGRESSION MODEL
YIN Shang-gang1, SONG Wei-xuan2, MA Zhi-fei1, LI Zai-jun1, WU Qi-yan1,3
1. School of Geographical Sciences, Nanjing Normal University, Nanjing 210023, China;
2. Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China;
3. School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an 710049, China
Abstract：Based on 2009-2017 in Nanjing city "one main city and three subsidiary cities" commercial housing community as the research unit, using ordinary Kriging interpolation statistical analysis GIS in the simulation and estimation of the "one main city and three subsidiary cities" housing price spatial distribution, and the use of geographically weighted regression (GWR) model to explore the impact of community property, commercial location, traffic location, service location and landscape location to the housing price. The results of the study show that:1)The housing price of Nanjing city generally shows the central peripheral mode of the main city decrement to the vice city, and the residential price space structure of "one main city and three subsidiary cities" presents a mixed model of concentric circles and fan-shaped fusion. 2) Center of potential impact on the urban housing price relative decline, affect the relative increase of vice city, the transportation potential showed the opposite trend. 3)The main and deputy city house price influence factors of spatial heterogeneity, including central city by the distance from the CBD, residential building age and the influence of green area is larger.
尹上岗, 宋伟轩, 马志飞, 李在军, 吴启焰. 南京市住宅价格时空分异格局及其影响因素分析——基于地理加权回归模型的实证研究[J]. 人文地理, 2018, 33(3): 68-77.
YIN Shang-gang, SONG Wei-xuan, MA Zhi-fei, LI Zai-jun, WU Qi-yan. SPATIAL DIFFERENTIATION AND INFLUENCING FACTORS ANALYSIS OF HOUSING PRICES IN NANJING: BASED ON GEOGRAPHICALLY WEIGHTED REGRESSION MODEL. HUMAN GEOGRAPHY, 2018, 33(3): 68-77.
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