根据城市土地覆盖类型的不透水率和绿化率波动计算日最高地表温度的发展

Young-Ran Kim, Se-Hwan Hwang
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引用次数: 0

摘要

热浪是城市热环境变化引起的最常见现象之一。它们主要是由地表不透水区域的蒸散减少引起的,因为温度和反射热量的增加,导致城市环境干燥,从而恶化日常生活的各个方面。本研究旨在计算影响热浪的日最高地表温度,量化通过水循环恢复控制城市热环境的效果,并验证其可行性。根据不同城市土地覆被类型的不透水面积比,导出了最高地表温度的回归方程。将日最高地表温度回归方程的估计值与实际实测值进行比较,验证了计算方法的可行性。通过将土地覆盖分为建筑物、道路、河流和土地,进行土地覆盖分类和具体参数的推导。详细参数采用除河流外各土地覆盖类型的河流面积比、土地不透面积比、绿地面积比进行分类,推导出各土地覆盖类型的地表温度最大回归方程。回归方程可行性评价表明,估算的最高地表温度值在显著性水平内。当绿色面积比增加1%时,最高表面温度降低0.0450℃;当不透水面积比增加1%时,最高表面温度升高0.0321℃。确定表面ISSN(Print): 1225-7672 / ISSN(Online): 2287-822X DOI https://doi.org/10.11001/jksww.2021.35.2.163
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of calculating daily maximum ground surface temperature depending on fluctuations of impermeable and green area ratio by urban land cover types
Heatwaves are one of the most common phenomena originating from changes in the urban thermal environment. They are caused mainly by the evapotranspiration decrease of surface impermeable areas from increases in temperature and reflected heat, leading to a dry urban environment that can deteriorate aspects of everyday life. This study aimed to calculate daily maximum ground surface temperature affecting heatwaves, to quantify the effects of urban thermal environment control through water cycle restoration while validating its feasibility. The maximum surface temperature regression equation according to the impermeable area ratios of urban land cover types was derived. The estimated values from daily maximum ground surface temperature regression equation were compared with actual measured values to validate the calculation method’s feasibility. The land cover classification and derivation of specific parameters were conducted by classifying land cover into buildings, roads, rivers, and lands. Detailed parameters were classified by the river area ratio, land impermeable area ratio, and green area ratio of each land-cover type, with the exception of the rivers, to derive the maximum surface temperature regression equation of each land cover type. The regression equation feasibility assessment showed that the estimated maximum surface temperature values were within the level of significance. The maximum surface temperature decreased by 0.0450 ̊C when the green area ratio increased by 1% and increased by 0.0321 ̊C when the impermeable area ratio increased by 1%. It was determined that the surface ISSN(Print): 1225-7672 / ISSN(Online): 2287-822X DOI https://doi.org/10.11001/jksww.2021.35.2.163
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