An Analyze of Urban Temperature Using Energy Balance Algorithm for Land (SEBAL) in Yogyakarta City

Abstract

This study examines the Land Surface Temperature (LST) using the Surface Energy Balance Algorithm for Land (SEBAL) model in Yogyakarta. SEBAL is relied upon for its accurate LST predictions because it takes into account the influence of vegetation and soil. This study identified LST in various land cover/land use (LULC) types extracted from Landsat 8 remote sensing images recorded in April 2019 (wet day) and June 2019 (dry day). The LULC classification results in the study area show that built-up land is the dominant land use, with 93.30% of the total area, and the rest is non-developed land (vegetation, open land, and water body). The average LST value on a wet day is 26.79 °C, while on a dry day, it is 30°C. The highest temperature occurs on the dry day, 35.17 °C, and the lowest on the wet day, which is 13.63°C. The correlation between LST and LULC shows the same pattern on the two different days, in which the value of vegetation temperature is lower than that of open and developed land. This research proves that vegetation influences a decrease in land surface temperature. Judging from the dominant land use being the built-up area in Yogyakarta, urban planners need to consider increasing green open spaces.