Land surface temperature(LST) retrieval has been a key issue in the thermal infrared remote sensing research area. Landsat5 TM data with a higher spatial resolution thermal infrared band of 120m was of ten used to retrieve land surface temperature. However

the fact that Landsat5 possesses only one thermal infrared band is also a critical limitation for LST retrieval. In most cases

only at-satellite brightness temperature was thus obtained from TM6 data

which is far different from the land surface temperature. Hence the precision of land surface temperature retrieval was actually not so satisfied. While the proposal of the generalized single-channel algorithm in 2003 makes it possible to figure out land surface temperature from TM6 data with high precision. Based on this algorithm

a test for land surface temperature retrieval of Beijing region was carried out with Landsat5 TM data acquired on 6 May 2005. MODIS data received on the same day was used to compute the total atmospheric water vapor content which is necessary for the algorithm. Furthermore

the retrieving result has been validated using simultaneously measured in situ data

and compared with that of using standard atmosphere data. A significantly high precision with a rootmean square deviation(rmsd) of 1.67℃ has been achieved by the approach introduced in this paper

which shows the advantages of synthetically utilizing multi-satellite data.