Influences of greening and structures on urban thermal environments: A case study in Xuzhou City, China

[Display omitted] •Green view index was used to study the urban thermal environment.•Construction view index was newly proposed to study the urban thermal environment.•Mobile observation and deep learning were used to study the urban thermal environment.•Objects within vision made synergistic effect...

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Veröffentlicht in:Urban forestry & urban greening 2021-12, Vol.66, p.127386, Article 127386
Hauptverfasser: Zhou, Hongxuan, Tao, Guixin, Yan, Xinye, Sun, Jing
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Sprache:eng
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Zusammenfassung:[Display omitted] •Green view index was used to study the urban thermal environment.•Construction view index was newly proposed to study the urban thermal environment.•Mobile observation and deep learning were used to study the urban thermal environment.•Objects within vision made synergistic effects to the urban thermal environment. Under the influences of global warming and urbanization, the urban thermal environment has gradually deteriorated, threatening human health. Based on the mobile sampling method, urban thermal environment data and street images were collected synchronously at pedestrian height in Xuzhou City, China, in late summer of 2020. Images were predicted and identified by SegNet, and the proportions of various objects were calculated in separate images, including the green view index (GVI, the vegetation proportion), construction view index (CVI, proposed to represent constructions proportion) and other view index (OVI, proposed to represent rest objects proportion). Various statistical methods were used to analyse urban thermal environment data and the above indices. Correlation analysis indicated that air temperature (Ta) was negatively and positively correlated with GVI and CVI (at the 0.01 level), while absolute humidity (H) was positively and negatively correlated with GVI and CVI (at the 0.01 level), respectively. Stepwise regression indicated the relative importance of GVI to Ta, and the relative importance of CVI to H was 100 %. The analytical hierarchy process indicated the joint effect of the three indicators explained only 50 % of the spatial variations in Ta and H over the sampling route, indicating that other factors influenced the urban thermal environment. Through a comparison between the two clustering analyses, we identified outliers located near crossroads, water bodies, mountains and high-rise buildings, which could be attributed to the hard surface, high openness or strong shading effect of high-rise buildings. In conclusion, a variety of urban elements influence the urban thermal environment, and the complex synergistic effect is worthy of further study to provide scientific input for urban planning, urban design and landscape design.
ISSN:1618-8667
1610-8167
DOI:10.1016/j.ufug.2021.127386