Comparative analysis of split-window and single-channel algorithms for land surface temperature retrieval of a pseudo-invariant target

Abstract

Land surface temperature (LST) acquired from remote sensing observations is essential to monitor surface energy and water exchange processes at the land-atmosphere interface. Most LST retrieval methodologies are developed focusing on Northern hemisphere. Consequently, Southern hemisphere has a great need for investigating the performance of LST retrieval algorithms already consolidated in the literature. In this paper, we compared a Split-window (SW) and a Single-channel (SC) method to retrieve LST from Landsat 8 OLI/TIRS images in a dune field, Southern Brazil. To validate the results, the Atmospheric Correction Parameter Calculator (ACPC) tool and Radiative Transfer Equation (RTE) were used. Results demonstrated that both methodologies are in accordance with the RTE, despite they overestimated the LST. Analysis of variance (ANOVA) indicated that the means are not statistically significant (0.05 level). The correlations between LST retrieved and RTE were strong, producing R² of 0.984 and 0.973 for the SW and SC, respectively, and RMSE values of 1.18 and 1.6. SW also exhibited the best values of MSD (±0.983) and Bias (0.773), thus reinforcing its superior performance. SW can be applied with an accuracy of 1.18 K in Southern Brazil, without needing complex modeling or specific radiosonde.