The impact of"blue-green spaces"on urban thermal comfort:an analysis of the cooling island effect in Lanzhou city
To investigate the impact of climate warming and urbanization on the thermal environment and thermal comfort in Lanzhou's urban center and suburban mountainous areas,particularly the role of the cooling is-land effect of urban"blue-green spaces"in improving local climate comfort,Landsat remote sensing imagery data was utilized in combination with the single-window algorithm to invert the land surface temperature(LST)of Lan-zhou.The strength of the"blue-green spaces"cooling effect was assessed using indicators of cooling distance and cooling intensity.Additionally,an improved temperature-humidity index(MTHI)was employed to analyze the spati-otemporal variation characteristics of the cool island effect of"blue-green spaces"and its relationship with local thermal comfort from 1993 to 2021.The results indicated that the average cooling distance of urban green spaces was 274.1 m,with an average cooling intensity of 5.16 ℃;the cooling distance around rivers was 140 m,with a cooling intensity of 4.23 ℃;the cooling distance in mountainous forest areas ranged from 500 to 1 000 m,with a cooling intensity between 5 ℃ and 10 ℃.Furthermore,the cool island index in urban areas showed a downward trend,while the index in mountainous areas was on the rise,indicating a general decline in surface temperatures in the mountains.In urban areas,green spaces and river-adjacent areas were cooler and more comfortable during the summer,while in mountainous areas,the perceived heat in the summer was between comfort and heat.The study suggested that urban areas should increase"blue-green spaces"to mitigate the urban heat island effect and enhance residents'thermal comfort.Meanwhile,the improvement of cool island effects and thermal comfort in mountainous areas highlights the importance of vegetation in maintaining and enhancing land surface temperature regulation.
"blue-green spaces"cooling island effectthermal comfortsurface thermal environmentLan-zhou city
国家科技期刊平台
NSTL
万方数据
