Estimation of Land Surface Heat Fluxes Based on Landsat 8 Satellite Data

Land surface heat fluxes encompass net radiation flux (Rn), soil heat flux (G), sensible heat flux (H), and latent heat flux (LE), all of which play a crucial role in understanding energy transfer within earth–atmosphere interactions. This study utilized Landsat 8 data to estimate land surface heat fluxes over the Navsari district of South Gujarat, India using the SEBAL (Surface Energy Balance Algorithm for Land) model. Rn followed a seasonal trend of summer > autumn > spring > winter, with median values ranging from 607.7 W/m2 in summer to 459.9 W/m² in winter. G exhibited a similar pattern, while H varied as summer > winter > spring > autumn. LE showed the opposite trend, peaking in autumn (427.3 W/m2) and decreasing through spring, winter, and summer. Notably, the LE remained higher than the H across all seasons. Rn was primarily allocated to LE across most LULC types, except in water bodies, where it was nearly evenly distributed between LE and G. In the absence of ground-based instruments, SEBAL outputs were validated using EEFlux METRIC, a cloud-based evapotranspiration (ET) estimation tool. The validation showed strong agreement for land surface temperature (LST) (R2 = 0.976, RMSE = 5.63 K) and moderate agreement for ET (R2 = 0.632, RMSE = 1.40 mm/day), albedo (R2 = 0.532, RMSE = 0.06), and crop coefficient Kc (R2 = 0.452, RMSE = 0.18). The SEBAL model was also applied to estimate seasonal ET and determine the total water requirement for sugarcane.