Matches in SemOpenAlex for { <https://semopenalex.org/work/W4311134071> ?p ?o ?g. }
- W4311134071 endingPage "16634" @default.
- W4311134071 startingPage "16634" @default.
- W4311134071 abstract "Mental health is one of the main factors that significantly affect one’s life. Previous studies suggest that streets are the main activity space for urban residents and have important impacts on human mental health. Existing studies, however, have not fully examined the relationships between streetscape characteristics and people’s mental health on a street level. This study thus aims to explore the spatial patterns of urban streetscape features and their associations with residents’ mental health by age and sex in Zhanjiang, China. Using Baidu Street View (BSV) images and deep learning, we extracted the Green View Index (GVI) and the street enclosure to represent two physical features of the streetscapes. Global Moran’s I and hotspot analysis methods were used to examine the spatial distributions of streetscape features. We find that both GVI and street enclosure tend to cluster, but show almost opposite spatial distributions. The Results of Pearson’s correlation analysis show that residents’ mental health does not correlate with GVI, but it has a significant positive correlation with the street enclosure, especially for men aged 31 to 70 and women over 70-year-old. These findings emphasize the important effects of streetscapes on human health and provide useful information for urban planning." @default.
- W4311134071 created "2022-12-23" @default.
- W4311134071 creator A5025752082 @default.
- W4311134071 creator A5038326444 @default.
- W4311134071 creator A5056961709 @default.
- W4311134071 creator A5064221185 @default.
- W4311134071 creator A5081335102 @default.
- W4311134071 date "2022-12-11" @default.
- W4311134071 modified "2023-09-25" @default.
- W4311134071 title "Investigating the Association between Streetscapes and Mental Health in Zhanjiang, China: Using Baidu Street View Images and Deep Learning" @default.
- W4311134071 cites W1903029394 @default.
- W4311134071 cites W1974091567 @default.
- W4311134071 cites W1979156423 @default.
- W4311134071 cites W1985089814 @default.
- W4311134071 cites W2000492570 @default.
- W4311134071 cites W2021580041 @default.
- W4311134071 cites W2021597034 @default.
- W4311134071 cites W2022275615 @default.
- W4311134071 cites W2023048788 @default.
- W4311134071 cites W2027808287 @default.
- W4311134071 cites W2030353587 @default.
- W4311134071 cites W2071240714 @default.
- W4311134071 cites W2094167708 @default.
- W4311134071 cites W2115846140 @default.
- W4311134071 cites W2117504085 @default.
- W4311134071 cites W2134172371 @default.
- W4311134071 cites W2147031808 @default.
- W4311134071 cites W2148600709 @default.
- W4311134071 cites W2149487489 @default.
- W4311134071 cites W2159567472 @default.
- W4311134071 cites W2163117137 @default.
- W4311134071 cites W2169281914 @default.
- W4311134071 cites W2169368100 @default.
- W4311134071 cites W2174298021 @default.
- W4311134071 cites W2285588445 @default.
- W4311134071 cites W2347145927 @default.
- W4311134071 cites W2404517203 @default.
- W4311134071 cites W2522940576 @default.
- W4311134071 cites W2544339191 @default.
- W4311134071 cites W2588898775 @default.
- W4311134071 cites W2751293097 @default.
- W4311134071 cites W2802467048 @default.
- W4311134071 cites W2885069941 @default.
- W4311134071 cites W2885964551 @default.
- W4311134071 cites W2890231632 @default.
- W4311134071 cites W2904633726 @default.
- W4311134071 cites W2933718005 @default.
- W4311134071 cites W2944824350 @default.
- W4311134071 cites W2948656201 @default.
- W4311134071 cites W2949313313 @default.
- W4311134071 cites W2949652968 @default.
- W4311134071 cites W2961493524 @default.
- W4311134071 cites W2962764844 @default.
- W4311134071 cites W2965251255 @default.
- W4311134071 cites W2993330193 @default.
- W4311134071 cites W3006084244 @default.
- W4311134071 cites W3092250696 @default.
- W4311134071 cites W3094393469 @default.
- W4311134071 cites W3128794575 @default.
- W4311134071 cites W3159388778 @default.
- W4311134071 cites W3186624857 @default.
- W4311134071 cites W3198856759 @default.
- W4311134071 cites W3217795008 @default.
- W4311134071 cites W4284668215 @default.
- W4311134071 cites W622702035 @default.
- W4311134071 cites W631895740 @default.
- W4311134071 doi "https://doi.org/10.3390/ijerph192416634" @default.
- W4311134071 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36554515" @default.
- W4311134071 hasPublicationYear "2022" @default.
- W4311134071 type Work @default.
- W4311134071 citedByCount "2" @default.
- W4311134071 countsByYear W43111340712023 @default.
- W4311134071 crossrefType "journal-article" @default.
- W4311134071 hasAuthorship W4311134071A5025752082 @default.
- W4311134071 hasAuthorship W4311134071A5038326444 @default.
- W4311134071 hasAuthorship W4311134071A5056961709 @default.
- W4311134071 hasAuthorship W4311134071A5064221185 @default.
- W4311134071 hasAuthorship W4311134071A5081335102 @default.
- W4311134071 hasBestOaLocation W43111340711 @default.
- W4311134071 hasConcept C117220453 @default.
- W4311134071 hasConcept C118552586 @default.
- W4311134071 hasConcept C134362201 @default.
- W4311134071 hasConcept C142853389 @default.
- W4311134071 hasConcept C15744967 @default.
- W4311134071 hasConcept C166957645 @default.
- W4311134071 hasConcept C191935318 @default.
- W4311134071 hasConcept C205649164 @default.
- W4311134071 hasConcept C2524010 @default.
- W4311134071 hasConcept C2776035688 @default.
- W4311134071 hasConcept C2987857752 @default.
- W4311134071 hasConcept C33923547 @default.
- W4311134071 hasConcept C46312422 @default.
- W4311134071 hasConcept C542102704 @default.
- W4311134071 hasConcept C58640448 @default.
- W4311134071 hasConcept C71924100 @default.
- W4311134071 hasConcept C99454951 @default.
- W4311134071 hasConceptScore W4311134071C117220453 @default.
- W4311134071 hasConceptScore W4311134071C118552586 @default.