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Comparison of the urban heat island intensity quantified by using air temperature and Landsat land surface temperature in Hangzhou, China

文献类型： 外文期刊

作者： Sheng, Li 1 ; Tang, Xiaolu 2 ; You, Heyuan 3 ; Gu, Qing 1 ; Hu, Hao 1 ;

作者机构： 1.Zhejiang Acad Agr Sci, Inst Digital Agr, 198 Shigiao Rd, Hangzhou 310021, Zhejiang, Peoples R China

2.Nanjing Univ, Sch Geog & Oceanog Sci, 163 Xianlin Rd, Nanjing 210023, Jiangsu, Peoples R China

3.Zhejiang Univ Finance & Econ, Coll Publ Management, 18 Xueyuan Rd, Hangzhou 310000, Zhejiang, Peoples R China

关键词： Urban heat island;Intensity;Indicator;Landsat LST;Hourly air temperature

期刊名称：ECOLOGICAL INDICATORS （ 影响因子：4.958； 五年影响因子：5.846 ）

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收录情况： SCI

摘要： This study compared different measures of urban heat island (UHI) intensity, which were calculated using both air temperature (T-air) at a height of 1.5 m and Landsat land surface temperature (LST) in Hangzhou, China. Two UHI-driven indicators (range and magnitude) and two land-cover-driven indicators (urban rural and urban-agriculture) were calculated to quantify the UHI intensity based on hourly T-air from five stations and fifteen Landsat 5 LST images. Pearson correlation testing and a moving average times series of the previous 30 days were used to investigate the relationship between UHI intensities calculated by different indicators and data. The results indicate that the land-cover-driven indicators explain UHI better than the UHI-driven indicators, while the calculated values of UHI intensity using Landsat LST and hourly T-air are not comparable. We also investigated the influence of weather conditions on UHI intensity. Generally, Landsat-LST-based UHI performs best on hot sunny days, while T-air-based UHI has a better chance during the nighttime following a dry sunny day. This study suggests that the value of UHI intensity can be influenced by the selected indicators, the data used, the acquisition time and the weather conditions. Thus, these factors should be considered when comparing UHI intensity between different cities or quantifying their influences (e.g., population size, land use and land cover change) on UHI intensity. (C) 2016 Elsevier Ltd. All rights reserved.

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