Predicting Sugarcane Harvest Date and Productivity with a Drone-Borne Tri-Band SAR

This article presents a novel method for predicting the sugarcane harvesting date and productivity using three-band imaging radar. Taking advantage of working with multi-band radar, this system was employed to estimate above-ground biomass (AGB), achieving root-mean-square error (RMSE) 2 kg m−2 in crops, which is an unprecedented result compared other works based on Synthetic Aperture Radar (SAR) system. By correlating field measurements ripening index (RI) AGB by indirect RI radar obtained. It observed that reaches its maximum approximately 280 days after planting RI, defines date, 360 species IACSP97-4039. Starting from map collected it then possible predict corresponding competitive average errors 8 10.7%, respectively, three months advance, whereas typical methods test site achieve 30 advance. To best our knowledge, first time prediction crops.