SPATIAL DIFFERENTIATION AND INFLUENCING FACTORS ANALYSIS OF HOUSING PRICES IN NANJING: BASED ON GEOGRAPHICALLY WEIGHTED REGRESSION MODEL

doi:10.13959/j.issn.1003-2398.2018.03.009

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HUMAN GEOGRAPHY ›› 2018, Vol. 33 ›› Issue (3) : 68-77. DOI: 10.13959/j.issn.1003-2398.2018.03.009

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-yan^1,3

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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.

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housing prices / spatial differentiation / influencing factors / geographically weighted regression

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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[J]. HUMAN GEOGRAPHY. 2018, 33(3): 68-77 https://doi.org/10.13959/j.issn.1003-2398.2018.03.009

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