Predicting Sugarcane Yield Through Temporal Analysis of Satellite Imagery During the Growth Phase

Predicting Sugarcane Yield Through Temporal Analysis of Satellite Imagery During the Growth Phase

This research investigates how to estimate sugarcane (<i>Saccharum officinarum</i> L.) yield at harvest by using an average satellite image time-series collected during the growth phase. This study aims to evaluate the effectiveness of various modeling approaches, including a heteroskeda...

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Bibliographic Details
Main Authors: Julio Cezar Souza Vasconcelos, Caio Simplicio Arantes, Eduardo Antonio Speranza, João Francisco Gonçalves Antunes, Luiz Antonio Falaguasta Barbosa, Geraldo Magela de Almeida Cançado
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Agronomy
Subjects:
digital agriculture
<i>Saccharum</i> spp.
precision farming
crop yield
statistical model
machine learning
Online Access:https://www.mdpi.com/2073-4395/15/4/793
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