Abstract

Rapid global urbanization has made environmental amenities scarce despite their considerable advantages, ranging from aesthetics to health benefits. Street greenness is a key urban environmental amenity. This study developed a green index as an objective measure of greenness using street view images and assessed its predictive power along with that of other environmental amenities for metropolitan housing prices. Spatial interpolation was used to transform point data into areal data, enabling effective analysis of a dataset covering an entire metropolis. A series of hedonic models revealed that (1) street greenness is significantly and negatively associated with housing prices, (2) a traditional greenness indicator and the green index provide complementary information, indicating that they could be used for different purposes, and (3) environmental amenities, in general, demonstrated significant relationships with housing prices. Our analysis strategy including spatial interpolation can be widely employed for studies using different types of data. The findings demonstrating a complementary relationship between our two greenness indicators provide valuable insights for policymakers and urban planners to improve street-level greenness and green accessibility. Considering the significance of environmental amenities, this study provides practical approaches for executing sustainable and healthy city development.

Details

Title
Assessment of street-level greenness and its association with housing prices in a metropolitan area
Author
An, Sihyun 1 ; Jang, Hanwool 2 ; Kim, Hwahwan 3 ; Song, Yena 3 ; Ahn, Kwangwon 1   VIAFID ORCID Logo 

 Yonsei University, Department of Industrial Engineering, Seoul, South Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454); Yonsei University, Center for Finance and Technology, Seoul, South Korea (GRID:grid.15444.30) (ISNI:0000 0004 0470 5454) 
 Glasgow Caledonian University, Department of Finance, Accounting and Risk, Glasgow, UK (GRID:grid.5214.2) (ISNI:0000 0001 0669 8188) 
 Chonnam National University, Department of Geography, Gwangju, South Korea (GRID:grid.14005.30) (ISNI:0000 0001 0356 9399) 
Pages
22577
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2903745037
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.