Comparison of water surface temperature retrieval methods from Landsat 9 satellite data

Abstract

Water surface temperature (WST) is a crucial parameter in aquatic systems, influencing both water quality and hydrodynamic conditions of these systems. Landsat 9, the latest satellite in the Landsat program, offers a unique opportunity for retrieving Earth's surface temperature data. Despite numerous efforts to develop methods for retrieving surface temperature from remote sensing data, there have been relatively few studies comparing the performance of these methods. The main objective of this study was to evaluate and compare the effectiveness of various methods for estimating WST in a reservoir on Argentina using thermal images from the new Landsat 9 satellite. WST retrievals were obtained from Landsat Collection 2 (C2), Level 2 products, as well as from the Single-Channel (SC) method and a Split-Window (SW) algorithm applied to Landsat C2, Level 1 images. The comparative analysis showed that, although all three methods performed similarly, the Split-Window method proved to be the most effective for estimating WST in the Río Tercero reservoir (R2 = 0.99, RMSE = 0.77 °C). Finally, this method was used to produce detailed WST distribution maps for the studied reservoir.