Estimating Land Surface Temperature in the Central Part of Isfahan Province Based on Landsat-8 Data Using Split- Window Algorithm

Land surface temperature (LST) is used as one of the key sources to study land surface processes such as evapotranspiration, development of indexes, air temperature modeling and climate change. Remote sensing data offer the possibility of estimating LST all over the world with high temporal and spatial resolution. Landsat-8, which has two thermal infrared channels, provides an opportunity for the retrieval of LST using the split- window method. The main objective of this research was to analyze the LST of land use/land cover types of the central part of Isfahan Province using the split- window algorithm. The obtained results demonstrated that the "other" class which had been mainly covered with bare lands exhibited the highest LST (50.9°C). Impervious surfaces including residential areas, roads and industries had the LST of 45°C. The lowest temperature was observed in the "water" class, which was followed by vegetation. Vegetation recorded a mean LST of 42.3°C. R2 was 0.63 when regression was carried out on LST and air temperature.