A Comparative Study of Estimating Hourly Images of MODIS Land Surface Temperature Using Diurnal Temperature Cycle Models in Arid Regions

Thermal monitoring of different regions is usually limited to meteorological data in ground stations. Meteorological networks are limited in arid and semi-arid areas, where monitoring climatic conditions is not possible. The aim of this study is to estimate the land surface temperature (LST) hourly for Yazd-Ardakan plain by modeling the diurnal temperature cycle (DTC) using LST imagery of moderate resolution imaging spectroradiometer (MODIS). First, MODIS imagery are reconstructed using the multi-channel singular spectrum analysis, and the complete time series without missing values are created. Then, six DTC models are compared. The accuracy of DTC models is examined by ground LST measurements, air temperature, humidity, and wind speed. In addition, the results of examining the root mean square error (RMSE) images obtained from cross-validation based on MODIS LST imagery show that DTC2 has the highest error, where 73% of the area has RMSE greater than
$3^{\circ} \text{C}$
. In DTC1 and DTC2, 64% and 5.8% of the study region has RMSE less than
$2^{\circ} \text{C}$
. In general, DTC1, DTC6, DTC5, DTC4, DTC3, and DTC2 models have shown the highest to lowest accuracy in modeling the LST diurnal cycle. In addition, the difference between LST in mountain and plain lands is greater at the time of maximum temperature than at other hours of the day and night. The findings of this research are crucial in studies concerning climate change and land environmental monitoring in arid/semi-arid regions.