PRODUCTION POTENTIAL AND CROP EVAPOTRANSPIRATION ESTIMATION FOR BEAN, SOYBEAN, AND MAIZE USING THE SEBAL ALGORITHM

Abstract

The replacement of satellite images by those obtained using unmanned aerial vehicle (UAV) can increase the level of detail of field information, since surface images reach precision of centimeters and can be taken at any time, generating advantages over some orbital platforms that are dependent on time and space. The objective of this work was to estimate the crop evapotranspiration (ETc) for irrigated common bean, soybean, and maize, using the Surface Energy Balance Algorithms for Land (SEBAL), through UAV and satellite (Landsat 8) images. The experiment was carried out under field conditions, with common bean, soybean, and maize crops, at the experimental station of the IFGoiano, which is in the Cerrado biome, southwestern state of Goiás, Brazil. The study was conducted using images obtained from the satellite Landsat 8 during the crop cycles. The Landsat 8 and DEM images have been taken as input data for the Surface Energy Balance Algorithms for Land (SEBAL). The mapping of the area with the UAV was conducted on the same day of the passage of the satellite for comparison of ETc values obtained by both approaches. The production potential of common bean, soybean, maize crops based on NDVI can be considered high.