Improvements in land surface temperature retrieval from the Landsat series thermal band using water vapor and air temperature

Land surface temperature (LST) is involved in many land surface processes such as evapotranspiration, net radiation, or air temperature modeling. In this paper we present an improved methodology to retrieve LST from Landsat 4 TM, Landsat 5 TM, and Landsat 7 ETM+ using four atmospheric databases covering different water vapor ranges (from 0 to 8 g cm(-2)) to build the LST retrieval models and using both water vapor and air temperature as input variables. We also compare this with LST retrievals using only water vapor or only air temperature, as well as with an existing LST retrieval algorithm. In order to validate the results, we have selected 77 Landsat images taken between 2002 and 2006 (Catalonia, northeast of the Iberian Peninsula) and two sources of water vapor (radiosounding data and remote sensing estimations) and air temperature (radiosounding data and air temperature modeling). The best results using radiosounding data are obtained when both air temperature and water vapor are present in the LST retrieval models with a mean RMSE of 0.9 K, followed by only water vapor models with a mean RMSE of 1.5 K and only air temperature models with a mean RMSE of 5.6 K. The results obtained using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 water vapor product and at-satellite-pass air temperature modeling as input data also show that this kind of input data offers best results, with a mean RMSE of 0.9 K, followed by water vapor models with a mean RMSE of 2.1 K and only air temperature models with a mean RMSE of 5.6 K. Similar errors when using radiosounding or modeled water vapor and air temperature as input data suggest the avoidance of radiosounding data to retrieve LST over extensive areas. Finally, when comparing the presented methodology with another methodology also using water vapor and air temperature as input data, the improvement is of more than 0.5 K.