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Predicting Sugarcane Harvest Date and Productivity with a Drone-Borne Tri-Band SAR
2022
Remote Sensing
This article presents a novel method for predicting the sugarcane harvesting date and productivity using a three-band imaging radar. Taking advantage of working with a multi-band radar, this system was employed to estimate the above-ground biomass (AGB), achieving a root-mean-square error (RMSE) of 2 kg m−2 in sugarcane crops, which is an unprecedented result compared with other works based on the Synthetic Aperture Radar (SAR) system. By correlating the field measurements of the ripening index
doi:10.3390/rs14071734
fatcat:d3cqom6x6zd4hag6qs34rbsydi