Extraction of Land Surface Temperature (LST) based on landsat satellite images and split window algorithm Study area: Mahabad Catchment

Land Surface Temperature (LST) is an important criterion for regional planning and management. LST can be used in many practical programs of environment, agriculture, meteorology and relevant surveys. Due to the limitations of meteorological stations, remote sensing can be used as base of meteorological data. One the practical approach of remote sensing is this important that it can be used for monitoring of LST. For this goal, the split window algorithm is well known technique among the remote sensing based methods for evaluating of LST. According to relevant literature this method has offered minimum error for evaluating the LST. In this survey LST of Mahabad’s catchment was derived, by using multi-spectral and thermal bands of Landsat 8. For this goal, after the atmospheric/ radio-metrical correction, image analysis process was performed.Normalized difference vegetation index, fraction of vegetation cover, satellite brightness temperature, land surface emissivity and column water vapor (CWV), are of the vital criteria in land surface temperature in split Window algorithm. For the task of LST modeling, the temperature was calculated based on relevant mathematical equations. Eventually, we managed to evaluate the LST being derived with an error of 1.4 Centigrade. And regions with high vegetation index and covered with water low temperature and regions with low vegetation index, and bare shows a high temperature which are all effective in temperature changes in researching area. Results of this research indicated, the method of split window algorithm is presenting exact, and reliable results for the scientific environmental researches and geoscience.