Using a split-window algorithm for the retrieval of the land surface temperature via landsat-8 OLI/TIRS

Abstract

Climate change has worsened and has widespread impact. This is partly due to the release of greenhouse gases from human activities, which cause the greenhouse effect. This leads to the global temperature rising to an unusual level, otherwise known as global warming. This study aimed to use a split-window algorithm to retrieve the land surface temperature via Landsat-8 OLI/ TIRS data in the Roi Et province area. The research methodology included 1) separating the Landsat-8 OLI data into four types of land use, i.e. the agricultural, forest, urban and water areas and 2) the data for Landsat-8 OLI bands 4 and 5 and Landsat-8 TIRS (bands 10, 11) being analysed to retrieve the land surface temperature using a split-window algorithm. The results from the land-use separation showed that the total area of Roi Et was 8,299.46 km2 divided into a 4,787 km2 agricultural area, which accounted for 60.81%; a 1,555 km2 forest area, accounting for 19.75%; a 1,212 km2 urban area, accounting for 15.39% and a 317.44 km2 water area, accounting for 4.03%. The land surface temperature analysis result using a split-window algorithm indicated that the average temperature of Roi Et was 34.74°C. Moreover, it was found that the land surface temperature of the urban area had the highest mean land surface temperature, followed by the forest area, the agricultural area and the water source area, respectively.