中国地理科学 ›› 2018, Vol. 28 ›› Issue (3): 505-515.doi: 10.1007/s11769-018-0954-6

• 论文 • 上一篇    下一篇

Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model

YANG Jun1,2, BAO Yajun1, ZHANG Yuqing1, LI Xueming1, GE Quansheng2   

  1. 1. Human Settlements Research Center, Liaoning Normal University, 116029 Dalian, China;
    2. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 收稿日期:2017-09-08 修回日期:2017-12-29 出版日期:2018-06-27 发布日期:2018-04-27
  • 通讯作者: YANG Jun.E-mail:yangjun@lnnu.edu.cn E-mail:yangjun@lnnu.edu.cn
  • 基金资助:

    Under the auspices of National Natural Science Foundation of China (No. 41471140, 41771178), Liaoning Province Outstanding Youth Program (No. LJQ2015058)

Impact of Accessibility on Housing Prices in Dalian City of China Based on a Geographically Weighted Regression Model

YANG Jun1,2, BAO Yajun1, ZHANG Yuqing1, LI Xueming1, GE Quansheng2   

  1. 1. Human Settlements Research Center, Liaoning Normal University, 116029 Dalian, China;
    2. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • Received:2017-09-08 Revised:2017-12-29 Online:2018-06-27 Published:2018-04-27
  • Contact: YANG Jun.E-mail:yangjun@lnnu.edu.cn E-mail:yangjun@lnnu.edu.cn
  • Supported by:

    Under the auspices of National Natural Science Foundation of China (No. 41471140, 41771178), Liaoning Province Outstanding Youth Program (No. LJQ2015058)

摘要:

This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows:first, the average house price is 12 436 yuan (RMB)/m2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.

关键词: geographically weighted regression model, accessibility, house price, Dalian City

Abstract:

This paper studies the relationship between accessibility and housing prices in Dalian by using an improved geographically weighted regression model and house prices, traffic, remote sensing images, etc. Multi-source data improves the accuracy of the spatial differentiation that reflects the impact of traffic accessibility on house prices. The results are as follows:first, the average house price is 12 436 yuan (RMB)/m2, and reveals a declining trend from coastal areas to inland areas. The exception was Guilin Street, which demonstrates a local peak of house prices that decreases from the center of the street to its periphery. Second, the accessibility value is 33 minutes on average, excluding northern and eastern fringe areas, which was over 50 minutes. Third, the significant spatial correlation coefficient between accessibility and house prices is 0.423, and the coefficient increases in the southeastern direction. The strongest impact of accessibility on house prices is in the southeastern coast, and can be seen in the Lehua, Yingke, and Hushan communities, while the weakest impact is in the northwestern fringe, and can be seen in the Yingchengzi, Xixiaomo, and Daheishi community areas.

Key words: geographically weighted regression model, accessibility, house price, Dalian City