Evaluation of landuses temperature changes in Zanjan in the period 2013 to 2019 using ‎comparison of land surface temperature‏ ‏estimation algorithms

Land surface temperature is one of the essential parameters in land use change studies, energy balance, climatology studies. In this study, Landsat 8 satellite images and weather station data during 2013 and 2019 in Zanjan have been used. Also to estimate the land surface temperature from four algorithms; Single channel, Mono window, Planck Equation and radiation transfer equation in PyQGIS open source software environment and support vector machine algorithm in Google Earth engine platform were used to prepare land use maps. Error Root Mean Square Error (RMSE) and Mean Absolute Percentage (MAPE) statistical methods were used to select the best algorithm for estimating the land surface temperature. The results obtained from the comparison of land surface temperature estimation algorithms, single channel algorithm in 2013 and 2019 have the lowest RMSE and MAPE and the highest accuracy. In 2013, RMSE and MAPE of this algorithm were equal to 1.472 and 5.579, respectively, and in 2019, 0.131 and 0.537. The high accuracy of this method can be due to the direct use of atmospheric transmittance coefficients in the single channel method process. In terms of accuracy, the Planck function, Mono window and the radiation transfer equation are in the next position. Based on the results of accuracy assessment of land use maps, kappa coefficient of 0.94 and 0.98 were obtained for 2013 and 2019, respectively. The results of studying the temperature changes of different land uses in 2013 and 2019 showed that fallow lands with an average temperature of 49.86 and 45.16, respectively, and Rainfed and rangeland land uses are in the next categories in terms of maximum temperature. Areas without vegetation have higher surface temperatures than areas with vegetation. In general, according to the results, it is clear that impermeable surfaces have a heating effect through absorption and storage of solar energy and heat production, as well as pollution and soil production through absorption and storage of solar energy, while vegetation through heat balance to Evaporator - transpiration and shade production have a cooling effect.