Determination of surface temperature in Sistan region using remote sensing technology

Earth skin temperature including soil، water، snow، and vegetation surface temperature is one of the main variables in geo-science studies. Generally، spatial distribution of surface temperature is needed in such studies. Spatial monitoring of surface temperature is possible using remote sensing data، and the time series of images provide a continuous spatio-temporal framework required in modeling energy balance of regional evaporation، optimization of energy demands or dispersion of atmospheric pollutions. In this paper، some common methods of surface temperature estimation using satellite imagery were introduced and calibrations of several forms of split window equation were addressed for Sistan area، Iran. Split window method is based on the fact that the atmospheric transmittance varies with wave length and uses a combination of thermal infra-red brightness temperature and emissivity. To calibrate the split window equation، ground observations and 22 NOAA/AVHRR images during 1992 to 2002 were used to develop regression models. Statistical tests were performed to evaluate the equations and coefficients. Ten AVHRR images were used to verify the developed equations. The results indicated that three different forms of split window equations successfully passed the χ2 statistical test. Both، F and Kruskal-Wallis tests showed that they are not statistically different at 95 percent significant level. Therefore، the simplest form of equation was used to derive surface temperature maps in the Sistan region، and is recommended as the most applicable one.