Estimating Land surface Temperature Changes Using Landsat Satellite Imagery and Three Algorithms, Mono Window, Single Channel and Planck, Case Study of Bojnourd Plain

Land surface temperature (LST) is considered as an important variable in the study of microclimate and radiation transmission in the atmosphere, which shows the environmental factors affecting land cover patterns using the temperature variable. In this study, thermal band images of Landsat 5 and Landsat 8 satellites have been used to estimate the surface temperature of Bojnourd plain. Initially, the processes of geometric and atmospheric correction, calculation of vegetation index, land emission index, water vapor in the air and atmospheric temperature were performed based on Kelvin. Then, using QGIS software, ground surface temperature estimation is obtained using Planck algorithm, single window algorithm and single channel algorithm. The results show that the areas with vegetation have the lowest temperature and the highest amount of temperature in areas without vegetation and barren lands. Comparison of the temperature of the nearest cell with the temperature of Bojnourd synoptic station and Asadli evaporating station and Grivan station shows that the temperature obtained through the models used is higher than the temperature measured in the stations and shows a comparison of the maps. The highest temperature of the warm period has been recorded in the barren lands of Bojnourd suburbs. Also, based on the mean square error (RMSE), (MAD) and (NS) among the studied algorithms, the temperature obtained from the single channel algorithm shows less difference than the temperature of the existing stations.