Thailand Land Surface Temperature Variation and Forecasting 10.32526/ennrj/25/20260027
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Abstract
Climate change has emerged as a global challenge, influenced by human activities, industrial operations and energy systems that depend on non-renewable energy such as carbon, gas, and petroleum. These activities have contributed to long-term shifts in temperature and broader climatic conditions. Land Surface Temperature (LST) has become an important standard for informing weather-related strategies at regional scales. This study aims to examine the seasonal pattern and variation of LST, including forecasting. Thailand is organized into six super-regions, each comprising nine sub-regions, for a total of 54 units. The sub-regions were delineated according to cardinal and intercardinal directions, with the central sub-region following the island’s shape. The separation between sub-regions is defined by a 150-pixel grid in latitude and longitude, approximately 95 km, covering the entire country. This study utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) data from NASA’s Terra Satellite, spanning the years 2000-2025. Cubic spline models incorporating eight, four, and three knots were applied to examine seasonal cycles, long-term variability, and LST projections for 2021-2031. The estimated mean increase in LST is 0.117oC per decade (1.17oC per century), statistically significant at the 5% level, [0.082, 0.272]oC of the confidence interval. The mean projected LST change designates a further significant increase of 0.219oC per decade. No statistically significant acceleration in LST is detected across Thailand’s super-regions, as the estimated acceleration of 0.103oC per decade2 does not meet the 0.05 significance threshold, and the associated p-value is 0.177.
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