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The determination of the surface energy balance fluxes (SEBFs) and evapotranspiration (E  T) is fundamental in environmental studies involving the effects of land use change on the water requirement of crops. SEBFs andE  Thave been estimated by remote sensing techniques, but with the operation of new sensors, some variables need to be parameterized to improve their accuracy. Thus, the objective of this study is to evaluate the performance of algorithms used to calculate surface albedo and surface temperature on the estimation of SEBFs andE  Tin the Cerrado-Pantanal transition region of Mato Grosso, Brazil. Surface reflectance images of the Operational Land Imager (OLI) and brightness temperature (T  b) of the Thermal Infrared Sensor (TIRS) of the Landsat 8, and surface reflectance images of the MODIS MOD09A1 product from 2013 to 2016 were combined to estimate SEBF andE  Tby the surface energy balance algorithm for land (SEBAL), which were validated with measurements from two flux towers. The surface temperature (T  s) was recovered by different models from theT  band by parameters calculated in the atmospheric correction parameter calculator (ATMCORR). A model of surface albedo (a   s  u  p) with surface reflectance OLI Landsat 8 developed in this study performed better than the conventional model (a   c  o  n) SEBFs andE  Tin the Cerrado-Pantanal transition region estimated witha   s  u  pcombined withT  sandT  bperformed better than estimates witha   c  o  n. Among all the evaluated combinations, SEBAL performed better when combininga   s  u  pwith the model developed in this study and the surface temperature recovered by the Barsi model (T    s   b  a  r  s  i). This demonstrates the importance of ana   s  u  pmodel based on surface reflectance and atmospheric surface temperature correction in estimating SEBFs and  ET  by SEBAL.

Surface Albedo and Temperature Models for Surface Energy Balance Fluxes and Evapotranspiration Using SEBAL and Landsat 8 over Cerrado-Pantanal, Brazil