This study explores the Olomouc region’s thermal dynamics and energy balance in northeastern Czech Republic during the spring and summer of 2022. Using Landsat 8 and Landsat 9 imagery, meteorological data and the S-SEBI model to determine Bowen Index (BI). Analysis of Solar Net Radiation and Sensible and Latent Heat Fluxes contributes to our understanding of energy exchanges at the surface. The S-SEBI algorithm helps determine Bowen Index, highlighting patterns across land cover classes. Urban and artificial areas consistently exhibit higher Bowen Index values, suggesting a higher sensible heat flux. Areas with vegetation showcase lower BI values, indicating the dominance of latent heat flux and the cooling effect of vegetation. Temporal trends in BI vary during specific sensing days. Despite challenges associated with atmospheric variability, our integration of meteorological data and remote sensing techniques contributes to understanding the local climate. Validation with EUMETSAT evaluation data indicates a consistent relationship with some biases, implying potential reliability of our approach and the derived heat fluxes and Bowen Index values.