TY - JOUR
T1 - The influence of the landscape pattern on the urban land surface temperature varies with the ratio of land components
T2 - Insights from 2D/3D building/vegetation metrics
AU - Zeng, Peng
AU - Sun, Fengyun
AU - Liu, Yaoyi
AU - Tian, Tian
AU - Wu, Jian
AU - Dong, Qianqian
AU - Peng, Shengjing
AU - Che, Yue
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2022/3
Y1 - 2022/3
N2 - Recently, the impact of multidimensional building/vegetation landscape patterns on urban land surface temperature (LST) has received extensive attention. However, investigations on how two-dimensional (2D)/three-dimensional (3D) building and vegetation landscape patterns affect the urban thermal environment under different cover types are still limited. Thus, we use the boosted regression tree model to explore the separate and combined relative contributions and marginal effects of 2D/3D building and vegetation landscape patterns on the LST and to examine the impacts of differences in building and vegetation coverage. The results indicate that the mean architecture height, building coverage ratio, high building ratio, vegetation coverage ratio, and architecture height standard deviation are the main metrics affecting the LST, with relative contributions of 24.8%, 14.9%, 14.7%, 8.2%, and 7.6%, respectively. The building landscape roughness and fragmentation have the greatest influence on the LST, with contributions of 1.2 °C and 0.8 °C, respectively. Furthermore, changes in the building and vegetation coverage can significantly affect the LST. When building coverage dominates, building-based metrics largely affect the LST. When vegetation coverage dominates, the impact of vegetation landscape diversity, roughness, and fragmentation on the LST gradually increases. This study provides insights for improving urban thermal environment.
AB - Recently, the impact of multidimensional building/vegetation landscape patterns on urban land surface temperature (LST) has received extensive attention. However, investigations on how two-dimensional (2D)/three-dimensional (3D) building and vegetation landscape patterns affect the urban thermal environment under different cover types are still limited. Thus, we use the boosted regression tree model to explore the separate and combined relative contributions and marginal effects of 2D/3D building and vegetation landscape patterns on the LST and to examine the impacts of differences in building and vegetation coverage. The results indicate that the mean architecture height, building coverage ratio, high building ratio, vegetation coverage ratio, and architecture height standard deviation are the main metrics affecting the LST, with relative contributions of 24.8%, 14.9%, 14.7%, 8.2%, and 7.6%, respectively. The building landscape roughness and fragmentation have the greatest influence on the LST, with contributions of 1.2 °C and 0.8 °C, respectively. Furthermore, changes in the building and vegetation coverage can significantly affect the LST. When building coverage dominates, building-based metrics largely affect the LST. When vegetation coverage dominates, the impact of vegetation landscape diversity, roughness, and fragmentation on the LST gradually increases. This study provides insights for improving urban thermal environment.
KW - 3d landscape pattern
KW - Boosted regression tree
KW - Building/vegetation landscape metrics
KW - Coverage ratio difference
KW - Land surface temperature
UR - https://www.scopus.com/pages/publications/85121269382
U2 - 10.1016/j.scs.2021.103599
DO - 10.1016/j.scs.2021.103599
M3 - 文章
AN - SCOPUS:85121269382
SN - 2210-6707
VL - 78
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 103599
ER -