COMPARISON OF SPLIT WINDOWS ALGORITHM AND PLANCK METHODS FOR SURFACE TEMPERATURE ESTIMATION BASED ON REMOTE SENSING DATA IN SEMARANG

Abstract

Surface temperature is one of the parameters in land–surface physical processes and is applied to global warming, climate change, and cycle hydrology. Two thermal bands in Landsat 8 imagery can be used as input for surface temperature extraction using the Split Windows Algorithm (SWA) and Planck method. This study aims to compare surface temperature estimates using the SWA and Planck methods and determine the surface temperature distribution based on the condition of land cover and its changes. The remote sensing data used are Landsat-8 OLI/TIRS Aqua MODIS images on August 27, 2013, and October 1, 2020. The results showed that Landsat 8 could obtain land cover information with an accuracy of 90% in 2013 and 91% in 2020. Planck surface temperature in 2013 was 1-3°C higher than SWA, while in 2020, Planck was 0.001-0.05°C lower than SWA but had similar distribution and pattern. The vegetation in the study area's central and south sides has a lower surface temperature than the built-up area on the north side. Land cover changes from non-built up to build-up area cause surface temperatures to increase. Each land cover has a different emissivity value and affects the surface temperature value, i.e., the lower the emissivity, the higher the surface temperature. The emissivity with surface temperature has a pearson correlation value ≥-0.8**.Keywords: Surface Temperature, Split Windows Algorithm, Planck