Yang Jun1; Bao Yajun1; Zhang Yuqing1; Li Xueming1; Ge Quansheng2
Source Publicationchinesegeographicalscience
AbstractThis 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)/m(2), 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.
Funding Project[National Natural Science Foundation of China] ; [Liaoning Province Outstanding Youth Program]
Document Type期刊论文
Recommended Citation
GB/T 7714
Yang Jun,Bao Yajun,Zhang Yuqing,et al. impactofaccessibilityonhousingpricesindaliancityofchinabasedonageographicallyweightedregressionmodel[J]. chinesegeographicalscience,2018,28(3):505.
APA Yang Jun,Bao Yajun,Zhang Yuqing,Li Xueming,&Ge Quansheng.(2018).impactofaccessibilityonhousingpricesindaliancityofchinabasedonageographicallyweightedregressionmodel.chinesegeographicalscience,28(3),505.
MLA Yang Jun,et al."impactofaccessibilityonhousingpricesindaliancityofchinabasedonageographicallyweightedregressionmodel".chinesegeographicalscience 28.3(2018):505.
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