Abstract

Land surface parameters are highly integrated and have a direct effect on water and energy balance and weather predictions. Due to the difficulties in correcting the influences of the atmosphere absorbability and the earth surface emissivity diversification, the retrieval of land surface temperature (LST) from satellite data is a challenging task. To retrieve microwave land emissivity, infrared surface skin temperatures have been used as surface physical temperature. However, passive microwave emissions originate from deeper layers with respect to the skin temperature. So, this inconsistency in sensitivity depths between skin temperatures and microwave temperatures may introduce a discrepancy in the determined emissivity. In this research work, 6 sample sites were chosen on the globe for 2013 and 2014 and then derive land surface temperature from AMSR-2, Landsat and ASTER brightness temperature values. The algorithm is developed from a surface brightness temperature dataset, which uses a range of surface parameters and atmospheric quantities as inputs. The retrieved LST is compared within AMSR-2, Landsat and ASTER for the same period and area. Maximum time ASTER shows highest temperature than other data and AMSR-2 has lowest temperature on same area. Landsat and ASTER is closer to ground measured temperature than AMSR-2 data. It will be interesting to see how the satellite-derived surface temperature will behave in an assimilation scheme in a follow-up study.

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