Land Surface Temperature Retrieval of Beijing City using MODIS and TM Data

Abstract

Land surface temperature (LST) retrieval has always been a key issue in the thermal infrared remote sensing research area. Landsat5 TM data with a higher spatial resolution thermal infrared band of 120 m was often used to retrieve land surface temperature. However, the fact that Landsat 5 possesses only one thermal infrared band is also a critical limitation for LST retrieval, which does not allow applying a split-window method. LST retrieval from the radiative transfer equation using in situ radiosounding data is often not practical because of the scarcity of in situ radiosounding data. Therefore in most cases, only at-satellite brightness temperature was 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 date 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. A significantly high precision with a root mean square deviation (rmsd) of 1.67 K has been achieved by the approach introduced in this paper, which shows the advantages of synthetically utilizing multi-satellite data.