TY - JOUR
T1 - Associations between urban thermal environment and physical indicators based on meteorological data in Foshan City
AU - Zhang, Qian
AU - Xu, Duo
AU - Zhou, Dian
AU - Yang, Yujun
AU - Rogora, Alessandro
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/9
Y1 - 2020/9
N2 - Recent trends in increasing global extreme weather patterns have led to a proliferation of studies about urban climate. However, most current studies have been conducted with insufficient urban climate and spatial data. Nearly 33,000 meteorological data were obtained from Foshan Meteorological Bureau to accurately identify whether and how urban spatial form affects urban thermal environment. Correlation and regression analyses were conducted on these meteorological data and 14 selected urban physical indicators, eight of which exhibited correlations with urban thermal environment. Unitary regression analysis showed that building footprint ratio is the most reliable predictor among the 14 urban physical indicators. The building footprint ratio explained about 70 % of the variance in daytime air temperature (AT) and urban heat island temperature (UHIT). According to the fitting equation, maximum daytime temperature, average daytime UHIT and average night UHIT will increase by 0.91 °C, 0.39 °C and 0.44 °C, respectively for every 10 % addition in building footprint ratio. Besides, the most surprising aspect of the regression analysis is that the daytime thermal environment and nighttime thermal environment are affected by different urban physical indicators. It can be seen from the results of unitary regression analysis that water area ratio has a strong correlation with daytime thermal environment, while impervious surface area ratio has a more obvious influence on night thermal environment. Multiple regression analysis revealed that the model composed of building footprint, green area, and water ratios explained about 83.3 % of the variance in average daytime UHIT. The model composed of building footprint, impervious surface area, and green area ratios explained about 80 % of the variance in average night UHIT.
AB - Recent trends in increasing global extreme weather patterns have led to a proliferation of studies about urban climate. However, most current studies have been conducted with insufficient urban climate and spatial data. Nearly 33,000 meteorological data were obtained from Foshan Meteorological Bureau to accurately identify whether and how urban spatial form affects urban thermal environment. Correlation and regression analyses were conducted on these meteorological data and 14 selected urban physical indicators, eight of which exhibited correlations with urban thermal environment. Unitary regression analysis showed that building footprint ratio is the most reliable predictor among the 14 urban physical indicators. The building footprint ratio explained about 70 % of the variance in daytime air temperature (AT) and urban heat island temperature (UHIT). According to the fitting equation, maximum daytime temperature, average daytime UHIT and average night UHIT will increase by 0.91 °C, 0.39 °C and 0.44 °C, respectively for every 10 % addition in building footprint ratio. Besides, the most surprising aspect of the regression analysis is that the daytime thermal environment and nighttime thermal environment are affected by different urban physical indicators. It can be seen from the results of unitary regression analysis that water area ratio has a strong correlation with daytime thermal environment, while impervious surface area ratio has a more obvious influence on night thermal environment. Multiple regression analysis revealed that the model composed of building footprint, green area, and water ratios explained about 83.3 % of the variance in average daytime UHIT. The model composed of building footprint, impervious surface area, and green area ratios explained about 80 % of the variance in average night UHIT.
KW - Correlation analysis
KW - Predictor
KW - Regression analysis
KW - Urban heat island
KW - Urban spatial characteristics
UR - https://www.scopus.com/pages/publications/85085736247
U2 - 10.1016/j.scs.2020.102288
DO - 10.1016/j.scs.2020.102288
M3 - 文章
AN - SCOPUS:85085736247
SN - 2210-6707
VL - 60
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 102288
ER -