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Emissivity Determination for Land Surface Temperature estimation of Iran using AVHRR Thermal Infrared Data

Foroogh Beik and M. Reza Saradjian
Remote Sensing Division, Surveying and Geomatics Engineering Department,
Faculty of Engineering, University of Tehran, Tehran, Iran

1. Introduction
Temperature is such an essential factor in understanding all biological, physical, and chemical systems on Earth and in space that we can safely say that is must be considered in any study involving earth sciences. Thermal infrared remote sensing provides a unique tool for estimating LST in large areas. However, the applicability of remote sensing data in quantitative based studies is limited by the accuracy that can be achieved with such measurements. Atmosphere and the emissivity correction are two basic problems related to the accurate measurements of surface temperature from space. Atmospheric effects can be eliminated using two simultaneous measurements at different wavelengths inside the atmospheric window 10.5-12.5mm. This technique is called Split-Window and has been successfully applied for sea surface measurements with AVHRR channels 4 (i.e. 10.3-11.3mm) and 5 (i.e. 11.5-12.5mm) (McClain et al., 1985). This method can be also applied for LST retrieval provided that emissivity effects are accounted for. Various split-window algorithms have been exhibited that differ in both their form and the calculation of their coefficients. The most common form of split-window algorithms is

Ts=T4 +A (T4-T5)-B (1)

where Ts is land surface temperature, T4 and T5 are brightness temperatures in AVHHRR channels 4 and 5, A and B are coefficients in relation to atmospheric effects, viewing angle and ground emissivity. The derivation of many algorithms for SST is based on the assumption that the ground surface acts as a black body with constant e close to 1. However, the Earth’s surface is not a blackbody, which means that its emissivity is less than 1 and is function of the waveband width, vegetation covers, soil moisture, surface roughness, etc.

Iran is a big country with high diversity in land cover. The great difference in land cover and type and accordingly presence of different emissivity values makes the LST algorithm or model development more complicated. An emissivity-box (Cihlar et al., 1997) or a radiometer to determine ground emissivity was not available in this study. Therefore, surface type, NDVI, geological and classification maps have been used and relevant emissivity values for each land cover have been selected from available lists of emissivities in the literature.

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