Urban Land Surface Temperature and Vegetation Correlation in the Kumasi Metropolis

S. Adanu, Eunice Amponsem, M. Adanu
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Abstract

Urban heat is considered as a worrying issue in cities because of the unbearable feelings associated with heat especially on sunny days. Urban heat is not as a result of any one time event but a chain of processes associated with land use activities such as infrastructure development that replaces the green vegetation. This paper investigated how land surface temperature has changed in the Kumasi Metropolis in 10 years from an environment of low temperature to much warmer land surface temperature due to the loss of trees in the city. The objectives of the study were to assess the extent of Land Surface Temperature (LST) in the metropolis, determine the kind of correlation that exist between Land Surface Temperate and vegetation health and examine the extent to which vegetation has influenced the city temperature. Multiple methods were used to calculate Land Surface Temperature (LST) such as converting the digital numbers of Landsat 2009, 2015 and 2019 images to radiance, top of brightness temperature and at-sensor brightness temperature using the Plank’s inverse function. NDVI analysis was done by subtracting the near infrared bands from the red band, divided by addition of the near infrared band to the red Band. Study results showed a linear increase in LST from an average of about 18°C to 31°C. The NDVI result showed decline in vegetation cover as such the correlation analysis was a negative correlation showing places of high temperature had minimal vegetation cover while places of low temperature had more vegetation cover. 
库马西大都市区地表温度与植被相关性研究
城市炎热被认为是一个令人担忧的问题,因为人们难以忍受炎热,尤其是在阳光明媚的日子里。城市热量并不是某个单一事件的结果,而是与土地利用活动(如取代绿色植被的基础设施开发)相关的一系列过程。本文研究了近10年来库马西大都市区由于树木的消失,地表温度由低到高的变化过程。研究的目的是评估大都市的地表温度(LST)程度,确定地表温度与植被健康之间存在的相关类型,并检查植被对城市温度的影响程度。利用Plank反函数将Landsat 2009年、2015年和2019年图像的数字数转换为辐射、顶亮温度和at-sensor亮度温度,采用多种方法计算地表温度。NDVI分析的方法是将近红外波段从红色波段中减去,再将近红外波段加到红色波段中。研究结果表明,从平均约18°C到31°C,地表温度呈线性增加。NDVI结果显示植被覆盖度下降,因此相关分析为负相关,高温地区植被覆盖度最小,低温地区植被覆盖度较大。
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