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• W2884748395 abstract "Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perceived by a person at eye-level on the ground. Furthermore, those studies are often criticized for the limitation of residential self-selection bias. In this study, urban greenness was extracted and assessed from profile view of streetscape images by Google Street View (GSV), in conjunction with deep learning techniques. We also explored a unique research opportunity arising in a citywide residential reallocation scheme of Hong Kong to reduce residential self-selection bias. Two multilevel regression analyses were conducted to examine the relationships between urban greenness and (1) the odds of walking for 24,773 public housing residents in Hong Kong, (2) total walking time of 1994 residents, while controlling for potential confounders. The results suggested that eye-level greenness was significantly related to higher odds of walking and longer walking time in both 400 m and 800 m buffers. Distance to the closest Mass Transit Rail (MTR) station was also associated with higher odds of walking. Number of shops was related to higher odds of walking in the 800 m buffer, but not in 400 m. Eye-level greenness, assessed by GSV images and deep learning techniques, can effectively estimate residents’ daily exposure to urban greenness, which is in turn associated with their walking behavior. Our findings apply to the entire public housing residents in Hong Kong, because of the large sample size." @default.
• W2884748395 created "2018-08-03" @default.
• W2884748395 creator A5043711460 @default.
• W2884748395 date "2018-07-25" @default.
• W2884748395 modified "2023-10-17" @default.
• W2884748395 title "The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents’ Exposure to Urban Greenness" @default.
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• W2884748395 cites W1964853204 @default.
• W2884748395 cites W1965577911 @default.
• W2884748395 cites W1966267313 @default.
• W2884748395 cites W1967652349 @default.
• W2884748395 cites W1974353382 @default.
• W2884748395 cites W1975793762 @default.
• W2884748395 cites W1984042903 @default.
• W2884748395 cites W1986351906 @default.
• W2884748395 cites W1990553815 @default.
• W2884748395 cites W1993204132 @default.
• W2884748395 cites W1998003247 @default.
• W2884748395 cites W2005544339 @default.
• W2884748395 cites W2006767569 @default.
• W2884748395 cites W2007157531 @default.
• W2884748395 cites W2009870422 @default.
• W2884748395 cites W2018781231 @default.
• W2884748395 cites W202456592 @default.
• W2884748395 cites W2027502995 @default.
• W2884748395 cites W2027808287 @default.
• W2884748395 cites W2029639376 @default.
• W2884748395 cites W2031144416 @default.
• W2884748395 cites W2045135809 @default.
• W2884748395 cites W2055589130 @default.
• W2884748395 cites W2055613674 @default.
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• W2884748395 cites W2073534662 @default.
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• W2884748395 cites W2499937126 @default.
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• W2884748395 doi "https://doi.org/10.3390/ijerph15081576" @default.
• W2884748395 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6121356" @default.
• W2884748395 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30044417" @default.
• W2884748395 hasPublicationYear "2018" @default.
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