Document Type : Research Paper
Authors
1 Assistant Professor, Faculty of Technology, Imam Khomeini International University, Iran
2 Associate Professor, Faculty of Civil Engineering, Sharif University of Technology, Iran
3 Associate Professor, Soil Conservation and Watershed Management Research Institute, Iran
Abstract
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.
Keywords
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