中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地理科学与资源研究所
  3. 中国科学院地理科学与资源研究所
Assessing the Effects of Subjective and Objective Measures on Housing Prices with Street View Imagery: A Case Study of Suzhou

文献类型：期刊论文

作者Zhu, Jin1,4; Gong, Yao4; Liu, Changchang4; Du, Jinglong4; Song, Ci1,2; Chen, Jie1,2; Pei, Tao1,2,3
刊名LAND
出版日期2023-12-01
卷号12期号:12页码:25
关键词street view imagery housing prices human perception Simpson's paradox geographically weighted regression
DOI10.3390/land12122095
通讯作者Zhu, Jin(zhujin@usts.edu.cn) ; Pei, Tao(peit@lreis.ac.cn)
英文摘要The price of a house is affected by both the subjective and objective factors of the street environment in a neighborhood. However, the relationships between these factors and housing prices are not fully understood. Street view imagery (SVI) has recently emerged as a new data source for housing price studies. The SVI contains both objective and subjective information and can be used to extract objective measurements describing the physical environment and subjective measurements depicting human perceptions. Compared to conventional methods, there is consistency between subjective and objective information extracted from SVIs, and the two types of information are acquired from the perspective of the human visual perceptual system. Therefore, using both objective and subjective information extracted from street view images to study their relationship with housing prices has several advantages. In this study, focusing on the city of Suzhou, China, we extracted subjective perception and objective view indices from SVIs and systematically assessed their effects on housing prices. The global ordinary least squares (OLS) regression model and the local geographically weighted regression (GWR) model were used to model the correlations between these measures and housing prices. The OLS reveals that overall objective measures have stronger explanatory power, and built environment factors have a greater impact on housing prices. GWR shows that subjective factors can explain more variance in housing prices on the local scale and that home buyers care more about the subjective perceptions of the neighborhood's surroundings. The map of the GWR local coefficients demonstrates that the perception indicators have both positive and negative effects on housing prices in different places. In addition, a Monte Carlo test was performed to verify the spatially varying relationships between these measures. Our findings provide important references for urban designers and guide various applications, such as safe neighborhood design and sustainable city planning.
WOS关键词MACHINE-LEARNING ALGORITHMS ; GREEN ; ASSOCIATIONS ; PERCEPTIONS ; ENVIRONMENT ; SPACES
资助项目Jiangsu Province Industry-University-Research Cooperation Program
WOS研究方向Environmental Sciences & Ecology
语种英语
出版者MDPI
WOS记录号WOS:001131399800001
资助机构Jiangsu Province Industry-University-Research Cooperation Program
源URL[http://ir.igsnrr.ac.cn/handle/311030/201447]  
专题中国科学院地理科学与资源研究所
通讯作者Zhu, Jin; Pei, Tao
作者单位1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100101, Peoples R China
3.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China
4.Suzhou Univ Sci & Technol, Sch Geog Sci & Geomat Engn, Suzhou 215009, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Jin,Gong, Yao,Liu, Changchang,et al. Assessing the Effects of Subjective and Objective Measures on Housing Prices with Street View Imagery: A Case Study of Suzhou[J]. LAND,2023,12(12):25.
APA Zhu, Jin.,Gong, Yao.,Liu, Changchang.,Du, Jinglong.,Song, Ci.,...&Pei, Tao.(2023).Assessing the Effects of Subjective and Objective Measures on Housing Prices with Street View Imagery: A Case Study of Suzhou.LAND,12(12),25.
MLA Zhu, Jin,et al."Assessing the Effects of Subjective and Objective Measures on Housing Prices with Street View Imagery: A Case Study of Suzhou".LAND 12.12(2023):25.

入库方式： OAI收割

来源：地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。