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    The comparison of surface temperature and air temperature trends using landsat 8 satellite images / Landsat 8 uydu görüntüleri kullanılarak hava sıcaklığı, yüzey sıcaklığının karşılaştırılması
    (Maltepe Üniversitesi, 2019) Salehiyan, Sona; Khalaji, Amin
    Surface temperature is an important indicator in the study of energy balance models on the Earth’s surface and also a strong indicator of the interactions between the Earth and its atmosphere on a regional and global scale. Surface temperature can be used in many environmental, agricultural, and meteorological applications. Traditional methods in field measurements of surface temperature are not capable of providing optimum spatial and temporal variations of the surface. Due to the coverage of the earth and other temperature conditions, the temperature at different points in one place could be several degrees lower or higher; in other words, physical conditions and land cover lead to the change in surface temperature. This requires the use of scientific methods (separate algorithms) that allow for calculating the temperature of each point of the earth so that researches and projects can be carried out in the Earth sciences fields in relation to surface temperature. Since meteorological stations only measure temperature data for specific points, infrared and thermal remote sensing images due to their extensive coverage are among the suitable information sources for the preparation of surface temperature maps at regional and global scales. The surface temperature (Ts) was calculated using a single-channel algorithm developed by JiménezMuñoz et al. Moreover, in order to calculate the air temperature (Ta), a linear relationship was first established between Ts and Ta. The comparison was implemented on seven Landsat 8 satellite images acquired in Ahvaz, Iran, in the period 2016 to 2018. The purpose in this study was to investigate trends of changes in Ta and Ts. The results showed that in the warm months of the year (July and October), according to the four pictures of 2016 and 2017, Ts was more than Ta. However, in the cold months of the year (according to the three pictures of 2017 and 2018), Ta was more than Ts. The results of the seasonal variation of the two parameters Ts and Ta were highly similar, and their changes were sinusoidally variable. Finally, the approximate equality of Ts derived from images taken in the same month in a year, as the images captured in July and October of 2016 and 2017, indicated the relative accuracy of the obtained temperatures.