Java and Bali land surface temperature decrease variation

The world is facing global warming due to natural processes and human activities. From 1880–1980, the global average temperature increased by 1°C per century. Land Surface Temperature (LST) is a crucial climatic variable for analyzing the interaction between the Earth's surface and the atmosphere. Java Island has the highest population and is more urbanized than other islands in Indonesia. From January 2001 to January 2020, LST daytime data were downloaded from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) Land Products Global Subsetting and Visualization Tool. This study aims to investigate the LST seasonal patterns and trends of Bali and Java islands. The appropriate distance between sub-regions was also observed, with 105 pixels and 52.5 pixels producing two and six super-regions, respectively. It was found that seasonal patterns could be represented with pixel distances of 105 and 52.5, using eight knots of cubic splines. From 2001–2020, the lowest LST was recorded in January, while the highest was in September. The highest average daily LST, 38.32 °C, was found in Cikande, Serang, and Banten, likely due to industrial activity. This study also analyzed LST fluctuations using seven knots of the cubic spline. It was found that the average daily LST decreased by −0.113 °C per decade in Java and Bali. The western super-regions of Java showed significant LST increases, while the eastern super-regions showed slight decreases. For the 52.5-pixel distance, there was no substantial variation in average LST, though Jakarta and Banten showed significant increases. The 105-pixel distance is useful for examining LST variations on small islands like Java, while the 52.5-pixel distance can detect deeper variations in smaller super-regions. This study also noted that monsoon season and precipitation impact LST decline, and suggested that further research is needed to validate these findings. Additional variables like NDVI, land elevation, and land cover should be considered for more accurate estimations, especially on larger islands or continents farther from the equator.