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首页> 外文期刊>Modeling Earth Systems and Environment >Relation between urban biophysical composition and dynamics of land surface temperature in the Kolkata metropolitan area: a GIS and statistical based analysis for sustainable planning
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Relation between urban biophysical composition and dynamics of land surface temperature in the Kolkata metropolitan area: a GIS and statistical based analysis for sustainable planning

机译:Kolkata Metropolitan地区城市生物物理构成与土地温度动力学的关系:可持续规划的GIS和统计学分析

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The major environmental impacts of urbanization have changed urban biophysical components which ultimately promoted land surface temperature (LST) as well as urban heat island (UHI). This study explores the upshot of land use land cover (LULC) and resultant effect on biophysical components to understand the heat island mechanism in the Kolkata Metropolitan Area (KMA) for four selected time period of 1991, 2001, 2011 and 2017. Six satellite-derived biophysical components were selected for the presentanalysis: NDBI, NDVI, NDWI, MNDWI, NDBaI and SAVI. Selected bands of Landsat-5 TM and OLI-8 were used for this purpose. The result shows that the built-up area has been increased from 322.68 km2 in 1991 to 982.86 km2 in 2017 and accordingly, LST also rises from 18.47 °C mean LST of 1991 to 23.30 °C mean LST of 2017. The correlation coefficient among the biophysical parameters and LST shows that the highest continuous increasing positive relationship between NDBI and LST (R = 0.71). Moreover, multiplelinear regression model (MLR) is adapted to the prediction on LST with the variation of biophysical parameters. Finally, we produced hot spot maps using Getis-Ord-Gi* statistics for the selected year to highlights the hot spot and cold spot area in KMA.The methodology presented in this paper can be broadly applied for the planning purposes because LST monitoring is an important parameter of sustainable urban planning.
机译:城市化的主要环境影响改变了城市生物物理组件,最终促进了土地表面温度(LST)以及城市热岛(UHI)。本研究探讨了土地使用土地覆盖(LULC)的结果,并产生了对生物物理成分的效果,以了解Kolkata大都市区(KMA)的热岛机制,为1991年,2001年,2011年和2017年的四个选定时间段。六卫星 - 选择衍生的生物物理组分用于纯分析:NDBI,NDVI,NDWI,MNDWI,NDBAI和SAVI。为此目的使用了Landsat-5 TM和OLI-8的选定带。结果表明,建筑面积从1991年的322.68平方公里增加到2017年的982.86平方公里,因此,LST也从1991年到23.30°C的18.47°C的平均值增加到2017年的23.30°C。相关系数生物物理参数和LST表明,NDBI和LST之间的最高连续关系(r = 0.71)。此外,多平板回归模型(MLR)适用于LST的预测,其具有生物物理参数的变化。最后,我们使用Getis-Ord-Gi *统计数据产生了所选年份的热点地图,以突出显示KMA的热点和冷点区域。本文提出的方法可以广泛地申请规划目的,因为LST监测是一个可持续城市规划的重要参数。

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