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

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 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...

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Bibliographic Details
Main Authors: Gian Oré, Marlon S. Alcântara, Juliana A. Góes, Bárbara Teruel, Luciano P. Oliveira, Jhonnatan Yepes, Valquíria Castro, Leonardo S. Bins, Felicio Castro, Dieter Luebeck, Laila F. Moreira, Rodrigo Cintra, Lucas H. Gabrielli, Hugo E. Hernandez-Figueroa
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Remote Sensing
Subjects:
sugarcane biomass estimation
harvest prediction
drone-borne SAR
back-projection processor
Online Access:https://www.mdpi.com/2072-4292/14/7/1734

Internet

https://www.mdpi.com/2072-4292/14/7/1734

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