How Landsat 9 Is Superior to Landsat 8: Comparative Assessment of Land Use Land Cover Classification and Land Surface Temperature

Abstract. This study aims (i) to analyze the performance of Landsat 8 and 9’s multispectral bands in Land Use Land Cover (LULC) mapping by applying Random Forest (RF) method, and (ii) to compare the LST results of Landsat 8 and 9 using ground-based measurements obtained from Surface Radiation Budget Network (SURFRAD). RF-based classification and pixel-based LST information extraction were conducted in the Google Earth Engine (GEE) environment. Considering the LULC classification, Iğdır province of Türkiye was chosen as the study area, whereas for LST analysis, the location of two SURFRAD stations (FPK and GWN) was selected. Collection 2 Level 2 Surface Reflectance (SR) Products of Landsat 8 and Landsat 9, acquired on 14 May 2022 and 22 May 2022, respectively, were used for LULC mapping. On the other hand, the products of Collection 2 Level 2 Surface Temperature (ST) were utilized for LST analysis. The obtained LULC results showed that Kappa value and Overall Accuracy (OA) for Landsat 9 and Landsat 8 were 87.4 %, 0.83, and 82 %, 0.76, respectively, presenting Landsat 9 achieved better performance in this case study. Concerning the thermal analysis, Landsat 9-based LST provided 1.77 K RMSE, which was lower than Landsat 8-based LST (RMSE=2.31 K). Consequently, Landsat 9 provided better accuracies in both LULC classification and LST analysis, and this study proved that Landsat 9 has more improved OLI and TIRS sensors than Landsat 8.