Estimation of Land Surface Temperature of Khost Province, Afghanistan, using Satellite Remote Sensing Technologies
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Abstract
One particularly important metric for examining the thermal flux and heat energy balance of land surfaces is land surface temperature (LST). It can be used for developing models of urban heat transmission, managing water resources, simulating climate change, and conducting environmental studies. This investigation focuses on determining the surface temperature of Khost province in Afghanistan, with an additional goal of assessing the correlation between the Normalized Difference Vegetation Index (NDVI) and the city's ground temperature. Utilizing data from the Landsat 8 Thermal Infrared Remote Sensor (TIRS), this study employs the Top of the Atmosphere Radiance method to estimate surface temperature. The findings indicate that the surface temperature exhibits a relatively low range of 10 to 48 °C in June 2023. Notably, areas abundantly covered with forest and vegetation manifest lower temperatures, while industrial or vegetation-deprived regions demonstrate higher temperatures, reaching up to 48 °C. The study leveraged NDVI to explore the relationship between thermal behavior and the extent of vegetation cover. Employing a regression technique, the investigation establishes a negative correlation between NDVI and LST, with the regression coefficient from NDVI to LST also being negative. In conclusion, the study determines that there is a negative correlation between NDVI and LST, highlighting the cooling effect of vegetation on surface temperatures.
Keywords
Remote, Sensing, Geographical, Information, Land, Surface, Temperature, Climate, Change##plugins.themes.academic_pro.article.details##
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