ESTIMATION OF THE RADIATION BALANCE OF IRRIGATED AÇAÍ THROUGH REMOTE SENSING IN EAST AMAZONIA

Abstract

Many areas in the Amazon have been modified, altering the energy exchanges in this environment. This change is one of the factors responsible for variations in the radiation balance (R_n), as they affect the energy exchange between the surface and the atmosphere. The objective was to estimate the R_n in an açaí irrigated area in Eastern Amazon. Landsat 8 satellite images of the sequential day of the year (DAS) 151/2018 and DAS 241/2019, referring to orbits/points: 222/61 and 223/61, respectively, were used. The R_n was obtained through the Surface Energy Balance Algorithm for Land - SEBAL algorithm, which is based on the radiance of the reflective and thermal bands of the sensor. The results (sensor x surface) were satisfactory with mean absolute error (EAM) values ​​equal to 4.92 W/m² and 15.66 W/m², mean relative error (ERM) equal to 0.98% and 3 .4% for DAS 151 and DAS 241, respectively. SEBAL's ability to differentiate types of land cover was observed, which provided the elaboration of the spatial distribution of Rn in the analyzed scene and in the açaí planting, so demonstrating the sensitivity of the model and the importance of spatial variability in the area, these information can help in decision-making regarding irrigation management.