Developing Model for Predicting Land Surface Temperature Change in The Three Southernmost Provinces of Thailand Using MODIS data

The objectives of this study were (i) to analyze the seasonal pattern and trend of land surface temperature (LST) change in the three southernmost provinces of Thailand (ii) to investigate the suitable models for predicting an average temperature in the three southernmost provinces of Thailand, and (iii) to evaluate the predicting performance of constructed models by using root mean square error (RMSE). The observation data used in this study were obtained from MODIS LST Data in NASA website which were collected every 8 days during January 1, 2001 to December 31, 2020 .Time lags of Land Surface Temperature has been used for being predicting variable and Land Surface Temperature as an outcome of the proposed model. The accuracy of proposed model has been evaluated by using Root Mean Square Error (RMSE). All finding results detail will be described later in the extended abstract. However, it cannot be guaranteed that the same performance for each model will be the same for other study areas.