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In recent years, many studies have been conducted combining orbital remote sensing data and crop growth models for vegetation monitoring, evapotranspiration estimation and quantification of biophysical parameters, e.g., NDVI, surface temperature, albedo, and biomass. The aim of the present study was to estimate evapotranspiration (ETr), biomass (BIO), and water productivity (WP) for irrigated seed corn crop using the SAFER algorithm and Landsat 8 satellite images. For this, eight cloud-free images were acquired at different phenological stages over the interest area on the United States Geological Survey website and meteorological data. ETr was estimated by the SAFER algorithm, BIO by the Monteith model, and WP by the BIO/ETr ratio. ETr values ranged from 0 to 6 mm d?1, with the highest values coinciding with the period of high vegetative crop vigor, while the lowest values were found at the sowing season. The highest biomass values were observed from images at 46 and 62 days after sowing (DAS), corresponding to 286 and 289 kg ha?1 d?1, respectively. The highest mean of water productivity was observed at 62 DAS, with 6.9 kg m?3 of water, corresponding to the period of maximum vegetative crop vigor. The application of the SAFER model together with Landsat 8 satellite images was an alternative to identifying the spatial and temporal variation of biophysical parameters of the corn crop. It could assist in the management of water in irrigated agriculture and decision making in large-sized farms.

Remote sensing as a tool to determine biophysical parameters of irrigated seed corn crop