Land Surface Temperature (LST) Calibration for Accurate Estimation of Air Temperature Using Mathematical Models and Meteorological Station Observations

The temperature of the Earth's surface is a very important parameter in environmental studies, climate change, soil moisture content, Evapotranspiration and urban thermal islands at different scales. Currently, there is no perfect method for accurately measuring the temperature of the surface of the earth, but since high spectral resolution sensors prevent the vapor spectral absorption in the infrared bands, this Increases computational accuracy in determining vegetation index. The purpose of this paper is to calculate the surface temperature using satellite images of OLI and TIRS sensors of Landsat 8. In this research, the separate window algorithm has been used to calculate ground temperature. The algorithm uses spectral radiance and emissivity to calculate the surface temperature. To estimate the spectral radiance in Landsat 8, the bands of 10 and 11 have been used. Emissivity is also obtained by using the NDVI threshold technique by using the OLI bands 2, 3, 4 and 5. Also, In this paper the temperature is calculated by The algorithm has been calibrated and corrected by a two-dimensional projective mathematical model, which tried to bring the calculated temperature closer to the actual ground temperature. In the present paper, the RMSE value is equal to 0.3678°C and the correlation between Meteorological data and temperature estimated by the model is equal to 0.9791. Also, the performance of the model that used to estimate the Earth's surface temperature is equal to 0.9751.