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The roles of surrounding 2D/3D landscapes in park cooling effect: Analysis from extreme hot and normal weather perspectives
被引:79
作者:
Han, Dongrui
[1
]
Xu, Xinliang
[2
]
Qiao, Zhi
[3
]
Wang, Fei
[1
]
Cai, Hongyan
[2
]
An, Hongmin
[4
,9
]
Jia, Kun
[5
]
Liu, Yihui
[6
]
Sun, Zongyao
[7
]
Wang, Shihao
[2
]
Han, Wei
[8
]
机构:
[1] Shandong Acad Agr Sci, Inst Agr Informat & Econ, Jinan 250100, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
[3] Tianjin Univ, Sch Environm Sci & Engn, Tianjin 300350, Peoples R China
[4] Shandong Univ, Sch Management, Jinan 250100, Peoples R China
[5] Shandong Jianzhu Univ, Sch Management Engn, Jinan 250101, Peoples R China
[6] Linyi Bur Nat Resources & Planning, Urban & Rural Planning Res Ctr, Linyi 276000, Peoples R China
[7] Tianjin Univ, Sch Architecture, Tianjin 300272, Peoples R China
[8] Beijing Meteorol Serv, Beijing Meteorol Observat Ctr, Beijing 100176, Peoples R China
[9] 27 Shanda Nanlu, Jinan, Peoples R China
关键词:
Urban parks;
Cooling effect;
2D;
3D landscapes;
Extreme hot weather;
Urban heat island;
LAND-SURFACE TEMPERATURE;
URBAN HEAT-ISLAND;
GREEN SPACE;
DESIGN PARAMETERS;
IMPACTS;
PATTERN;
SUMMER;
COVER;
ZONES;
WATER;
D O I:
10.1016/j.buildenv.2023.110053
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
Urban parks are regarded as a promising measure to alleviate urban heat island (UHI) effects. Park cooling effects have been widely investigated, however, the impacts of surrounding 2D/3D landscapes on it remain uncertain, especially in extreme hot weather. Therefore, taking 70 parks in Beijing as the samples, this study investigated the impacts of surrounding 2D/3D landscapes (vegetation, water, impervious surface, and buildings) on the park cooling effects in the extreme hot and normal days. First, based on buffer method, park cooling efficiency (PCE) was determined in the extreme hot and normal days. Then, both 2D (percentage of landscape (PLAND), landscape shape index (LSI), and aggregation index (AI)) and 3D (building density (BD), building height (BH), sky view factor (SVF), and frontal area index (FAI)) metrics were used to explore how surrounding 2D/3D landscapes influence PCE based on boosted regression tree (BRT) approach. The results showed that parks demonstrated the cooling islands, and the average PCE were 7.01 and 7.49 in the extreme hot and normal days, respectively. Surrounding buildings and vegetation metrics are the most important indicator in the extreme hot and normal days, respectively, which account for 30.6% and 47.1% of the contribution of PCE. The relationships between the key surrounding landscape metrics and PCE were nonlinear in the extreme hot and normal days. This study emphasized that surrounding 2D/3D landscapes can significantly affect park cooling effects, and the impacts are nonlinear. The findings are conducive to enhance the park cooling effects by optimizing the surrounding landscapes.
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页数:11
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