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

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Ore, Gian ; Alcantara, Marlon S. ; Goes, Juliana A. ; Teruel, Barbara ; Oliveira, Luciano P. ; Yepes, Jhonnatan ; Castro, Valquiria ; Bins, Leonardo S. ; Castro, Felicio ; Luebeck, Dieter ; Moreira, Laila F. ; Cintra, Rodrigo ; Gabrielli, Lucas H. ; Hernandez-Figueroa, Hugo E.
Número total de Autores: 14
Tipo de documento: Artigo Científico
Fonte: REMOTE SENSING; v. 14, n. 7, p. 24-pg., 2022-04-01.
Resumo

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 (RI) with the AGB measurements by radar, an indirect estimate of the RI by the radar is obtained. It is observed that the AGB reaches its maximum approximately 280 days after planting and the maximum RI, which defines the harvesting date, approximately 360 days after planting for the species IACSP97-4039. Starting from an AGB map collected by the radar, it is then possible to predict the harvesting date and the corresponding productivity with competitive average errors of 8 days and 10.7%, respectively, with three months in advance, whereas typical methods employed on a test site achieve an average error of 30 days with three months in advance. To the best of our knowledge, it is the first time that a multi-band radar is employed for productivity prediction in sugarcane crops. (AU)

Processo FAPESP: 17/19416-3 - Radar transportado por drone para agricultura de precisão na cana de açúcar
Beneficiário:Hugo Enrique Hernández Figueroa
Modalidade de apoio: Auxílio à Pesquisa - Parceria para Inovação Tecnológica - PITE
Processo FAPESP: 18/00601-8 - Radar de sensoriamento remoto transportado por drone
Beneficiário:Dieter Lubeck
Modalidade de apoio: Auxílio à Pesquisa - Pesquisa Inovativa em Pequenas Empresas - PIPE