 This paper presents a comprehensive assessment of four land surface temperature, LST, retrieval algorithms using different land surface emissivity, LSE, models and data of Landsat missions, Landsat 5, 7, and 8. The authors compared the performance of the algorithms using the Normalize Difference Vegetation Index, NDVI, based LSE models. The algorithms were tested on 45 daytime Landsat images acquired over five surfrat rural sites in the mid-latitude region, in the Northern Hemisphere. The results showed that the radiative transfer equation, RT, algorithm outperformed the other algorithms in terms of accuracy. Additionally, the authors found that the MWA algorithm performed similarly across all sensors and seasons, while the RT algorithm had a slight advantage in summer. This article was authored by Alia Sansecotecan and Stefania Bonifoni.