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Statistical analysis of surface urban heat island intensity variations: A case study of Babol city, Iran

机译:地表城市热岛强度变化的统计分析:以伊朗巴博尔市为例

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The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon's entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.
机译:城市热岛被认为是城市地区最重要的气候变化现象之一,可能对植物区系,污染物浓度,空气质量,能源和水的消耗,人类健康,生态和经济影响以及对环境的严重影响。即使全球变暖。地表城市热岛强度(SUHII)的变化分析对于理解城市化和城市规划的影响非常重要。这项研究的目的是提出一种基于Shannon熵和Pearson卡方统计的新策略,以研究SUHII的时空变化。在这项研究中,使用了1985年至2017年伊朗巴博尔市的Landsat TM,ETM +,OLI和TIRS图像,MODIS产品,气象数据,地形图和人口图以及2017年地面记录仪设备记录的气温数据。首先,使用单通道算法估计陆地表面温度(LST),并使用最大似然分类器对Landsat图像进行分类。然后,基于LST图,使用城市地表热岛比率指数来计算SUHII。此外,使用了一些统计方法,例如自由度、,散度和良善度,来分析SUHII在不同地理方向和不同时间段内的变化。最后,研究了空气温度,SUHII,人口变化和良好程度指数值等各种参数之间的相关性。结果表明,在不同时间段,Babol中的SUHII值增加了24%。相关系数在城市和郊区的平均气温与地理方向的SUHII值之间的差值之间达到0.82。此外,人口变化与良好程度指数值之间的相关系数达到0.8。结果表明,巴博尔市的SUHII变异具有较高的自由度,较高的蔓延度和负的良好度。

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