Bakhtiar Feizizadeh; Khalil Didehban; Khalil Gholamnia
Abstract
Abstract
Land Surface Temperature (LST) is one of important criteria in 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 the basis ...
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Abstract
Land Surface Temperature (LST) is one of important criteria in 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 the basis of many meteorological data. One of the most important practical aspects of remote sensing in climate studies is the estimation of surface temperature. In this regard, the split window algorithm is considered as an effective method for extracting surface temperature, which provides the highest accuracy based on scientific resources. In this research, Landsat 8 satellite’s multi-spectral and thermal images have been used to estimate the land temperature in Mahabad catchment. To accomplish the goal, modeling and analyzing of the images were performed after radiometric corrections. The vegetation index, the vegetation shortage, the temperature of the satellite illumination, the emissivity of the land surface, the column water vapor (CWV) are of effective criteria for estimating the land surface temperature by the method of split window algorithm. The values necessary to calculate the land surface temperature were obtained by performing mathematical relation computation. Eventually, the land surface temperature was accurately estimated with an error of 1.4 degrees Centigrade. Areas with high vegetation cover and covered with water show low temperatures and, areas with low vegetation cover and bare soil show a high temperature, all of which are effective in temperature variations in the studied area. The results of the research indicate that the method of split window algorithm provides exact and reliable results in the estimation of land surface temperature, which can be used in environmental studies and geosciences.
