The Impact of Street Space Perception Factors on Elderly Health in High-Density Cities in Macau—Analysis Based on Street View Images and Deep Learning Technology

Lingchao Meng, Kuo-Hsun Wen, Zhijie Zeng, Richard Brewin, Xiaolei Fan and Qiong Wu
Additional contact information
Lingchao Meng: School of Fine Arts, Northwest Minzu University, No 1 Northwest New Village, Chengguan Area, Lanzhou 730030, China
Kuo-Hsun Wen: School of Arts, Macao polytechnic Institute, Rua Luis Gonzaga Gomes 999078, Macau, China
Zhijie Zeng: Urban Planning & Design Institute of Shenzhen, Shenzhen 518000, Guangdong, China
Richard Brewin: Beijing Normal University, Zhuhai, No 18 Jinfeng Road, Tangjiawan Area, Zhuhai 519000, Guangdong, China
Xiaolei Fan: School of Art and Design, Zhengzhou Institute of Finance and Economics, Zhengzhou 450000, China
Qiong Wu: Faculty of Business, City University of Macau, Avenida Padre Tomás Pereira, Taipa 999078, Macau, China

Sustainability, 2020, vol. 12, issue 5, 1-19

Abstract: The urban space environment has been proven to be related to the health of the elderly. However, as a high-density city, Macau’s limited urban space must cope with the growing population and the arrival of an aging society. In the existing studies, less attention has been paid to Macau, especially the relationship between Macanese elderly and urban space. This study uses Baidu Street View (BSV) on the Macau Peninsula and conducts field surveys to obtain street view data to evaluate the openness, greenness, interface coverage, and road area ratio of street space and its association with the physical and mental health of the elderly and social health. The results show that the data truly reflect the overall street space conditions on the Macau Peninsula. The street openness, greenery rate, and interface enclosure are all related to the elderly in various evaluations in areas with a higher population dependency index and aging index. Human space perception is related to health gain, and road area ratio is weaker than other indicators. The research results have certain policy implications and have practical significance for city managers and designers.

Keywords: street view data; deep learning; street space; elderly health; macau (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/5/1799/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/5/1799/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:5:p:1799-:d:325968

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().