With the rapid development of new satellite thermal sensors and applications of land surface temperature (LST), research on finding effective algorithms to retrieve accurate LST from satellite thermal infrared (TIR) data is becoming more and more important. In this study, multiple algorithms for retrieving LST from Landsat-8 Thermal Infrared Sensor (TIRS) data are validated and intercompared in an extremely arid region, Northwest China. According to the validation and intercomparison, we find that the radiative transfer equation (RTE) based method with TIRS band 1 (10.60–11.19 µm) has the highest accuracy, while the single-channel (SC) method using TIRS band 2 (11.50–12.51 µm) yielded the lowest accuracy. The accuracies of split-window (SW) algorithms are slightly lower than the RTE based method. However, the SW algorithms have better applicability than the RTE based method. The most suitable SW algorithm for Landsat-8 TIRS data in the study area is recommended. This study will be beneficial for developing the LST product from Landsat-8 data for the study area.
['Yujia Wang', 'Ji Zhou', 'Mingsong Li', 'Xiaodong Zhang']
Validation of Landsat-8 TIRS LAND surface temperature retrieved from multiple algorithms in an extremely arid region