Virtual Channel-Based Split-Window Algorithm for Landsat-8 Land Surface Temperature Retrieval

As a key driving factor of land-atmosphere system, land surface temperature (LST) is widely applied in geoscience studies across various fields. Among numerous LST retrieval methods, the split-window (SW) algorithm has been widely used because of its advantage of free of atmospheric profile data. However, some satellites provide only one single available thermal infrared (TIR) channel, which limits the direct application of the SW algorithm. To overcome this shortcoming, this study takes Landsat-8 as an example, whose TIR Channel-11 is affected by degraded calibration accuracy caused by stray light and develops a method to construct a virtual channel using MODIS TIR data, enabling the application of the SW algorithm to Landsat-8 data for LST retrieval. During the construction, the angular normalization is adopted to the MODIS TIR data in advance. The validation results derived from the simulated dataset show that the RMSE of LST retrieval based on the virtual channel using the SW method is less than 1.2 K. Further validation with ground-based measurements from the FPK station results in an RMSE of 2.44 K, demonstrating better accuracy than the result from single channel (SC) algorithm. Moreover, the angular normalization applied to MODIS data leads to an improvement of 0.36 K in LST retrieval accuracy. The results demonstrate the advantages of LST retrieval from Landsat-8 data with virtual channel and extend the applicability of the SW algorithm.