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Evaluating the Effects of Landscape on Housing Prices in Urban China
Author(s) -
Du Qingyun,
Wu Chao,
Ye Xinyue,
Ren Fu,
Lin Yongjun
Publication year - 2018
Publication title -
tijdschrift voor economische en sociale geografie
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 55
eISSN - 1467-9663
pISSN - 0040-747X
DOI - 10.1111/tesg.12308
Subject(s) - geographically weighted regression , real estate , china , urbanization , database transaction , geography , urban planning , field (mathematics) , contrast (vision) , hedonic pricing , regional science , economic geography , environmental planning , econometrics , computer science , business , civil engineering , economics , economic growth , statistics , engineering , mathematics , archaeology , finance , artificial intelligence , pure mathematics , programming language
The rapid urbanisation of China has received growing attention regarding its urban residential environments. In this article, we model the spatial heterogeneity of housing prices and explore the spatial discrepancy of landscape effects on property values in Shenzhen, a large Chinese city. In contrast to previous studies, this paper integrates the official housing transaction records and housing attributes from open data along with field surveys. Then, the results using the hedonic price model (HPM), geographically weighted regression (GWR) without landscape metrics and GWR with landscape metrics are compared. The results show that GWR with landscape metrics outperforms the other two models. In summary, this research provides new insights into landscape metrics in real estate studies and can guide decision‐makers plan and design cities while also providing guidance to regulate and control urban property values based on local conditions.