Estimation of large-scale land surface temperature from satellite images is of great importance for the study of climate change. This is especially true for the most challenging areas, such as the Tibetan Plateau （TP）. In this paper, two split window algorithms （SWAs）, one for the NOAA’s Advanced Very High Resolu-tion Radiometer （AVHRR）, and the other for the Moderate Resolution Imaging Spectroradiometer （MODIS）, were applied to retrieve land surface temperature （LST） over the TP simultaneously. AVHRR and MODIS data from 17 January, 14 April, 23 July, and 16 October 2003 were selected as the cases for winter, spring, summer, and autumn, respectively. Firstly, two key parameters （emissivity and water vapor content） were calculated at the pixel scale. Then, the derived LST was compared with in situ measurements from the Coordinated Enhanced Observing Period （CEOP） Asia-Australia Monsoon Project （CAMP） on the TP （CAMP/Tibet） area. They were in good accordance with each other, with an average percentage error （PE） of 10.5% for AVHRR data and 8.3% for MODIS data, meaning the adopted SWAs were applicable in the TP area. The derived LST also showed a wide range and a clear seasonal difference. The results from AVHRR were also in agreement with MODIS, with the latter usually displaying a higher level of accuracy.
