Estimation of land surface temperature from three thermal infrared channels of MODIS data for dust aerosol skies

Studies indicated that a root mean square error (RMSE) of 3.7 K was found if dust aerosol was not considered in the traditional land surface temperature (LST) retrieval algorithm. To reduce the influence of dust aerosol on LST estimation, a three-channel algorithm is proposed using MODIS channels 29, 31, and 32 with model coefficients irrelevant to the aerosol optical depth (AOD). Compared with actual and estimated LSTs, the RMSEs are 1.8 K and 1.6 K for dry and wet atmospheres, respectively, when the AOD is 1.0. Sensitivity analyses considering instrument noise, land surface emissivity uncertainties, and the algorithm error itself show that the LST errors are 2.5 K and 1.7 K for dry and wet atmospheres, respectively, when the AOD is 1.0. Finally, some in situ measured LSTs at the Jichanghuangmo, Huazhaizi, and Yingke sites in northwest China are taken as referenced LST values and compared with the MODIS LST products MOD11_L2/MYD11_L2 and those estimated with the proposed method. The results show that the proposed method can improve the LST retrieval accuracy from 1.4 K to 2.2 K in dust aerosol atmospheres. (c) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement