Evaluation of the Seasonal Thermal Environmental Benefits of Urban Green Space in the Core Areas of Urban Heat Island

被引:2
|
作者
Liu, Jiachen [1 ]
Wu, Jianting [2 ]
Yang, Yong [3 ]
Zhang, Baolei [1 ]
Yin, Le [1 ]
机构
[1] Shandong Normal Univ, Coll Geog & Environm, Jinan 250358, Peoples R China
[2] Shandong Prov Inst Land Spatial Data & Remote Sens, Jinan 250014, Peoples R China
[3] Shandong Prov Terr Spatial Ecol Restorat Ctr, Jinan 250014, Peoples R China
来源
FORESTS | 2023年 / 14卷 / 07期
基金
中国国家自然科学基金;
关键词
urban green space; thermal environment benefits; geographical detector; heat core areas; Beijing city; LAND-SURFACE TEMPERATURE; LANDSCAPE; PATTERNS; MITIGATION; QUALITY;
D O I
10.3390/f14071500
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The core areas of the urban heat island (CAUHI) are the most concentrated and closely associated with humans, and they are key to managing the urban heat island (UHI). It is widely acknowledged that one of the best ways to reduce the risk of UHI is the creation of urban green spaces (UGSs). However, most of the current studies are based on the grid or block scale to explore the impact of UGS on UHI. The key to mitigating the urban heat environment is to plan urban UGS rationally in the CAUHI and explore the thermal environmental benefits of UGS. This paper provides an assessment model for the thermal environmental advantages of UGS and uses ten UGS metrics as explanatory factors for seasonal land surface temperature (LST). It quantitatively evaluates the potential differences in landscape characteristics between LST and UGS under different seasons, as well as the seasonal impact on CAUHI. This study found the following: (1) The overall distribution pattern of CAUHI shows a characteristic of spreading from the central part to the surrounding area. Most of the extremely significant CAUHI is dispersed in the center and southeastern regions of the city, where there is a much greater density of impermeable surfaces and essentially no distribution of CAUHI on the natural surface represented by forest land and water bodies. (2) Except for the aggregation index (AI), correlation analysis revealed that other metrics were highly connected with LST. Among the metrics used in this study, the largest patch index (LPI) and landscape division index (DIVISION) had the highest significant correlation with LST. Patch density (PD) was strongly negatively correlated with LST, indicating that fragmented and complex UGS patches could promote vegetation cooling. (3) The green environmental benefit index (GEBI) results showed a significant degree of spatial and temporal variability in the extracted CAUHI. This study found higher GEBI values in the larger thermal patches and lower GEBI in the surrounding smaller patches. The highest mean GEBI was found in winter, at 0.6083, and the largest distribution of large high-value patches. This study revealed the geographical and temporal variability of UGS and CAUHI, and with the help of the constructed scientific evaluation model, it offered suggestions for the optimization of urban greenery.
引用
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页数:15
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