High-throughput method for improving rice AGB estimation based on UAV multi-source remote sensing image feature fusion and ensemble learning

High-throughput method for improving rice AGB estimation based on UAV multi-source remote sensing image feature fusion and ensemble learning

IntroductionThe rapid and non-destructive estimation of rice aboveground biomass (AGB) is vital for accurate growth assessment and yield prediction. However, vegetation indices (VIs) often suffer from saturation due to high canopy coverage and vertical organs, limiting their accuracy across multiple...

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Bibliographic Details
Main Authors: Jinpeng Li, Jinxuan Li, Dongxue Zhao, Qiang Cao, Fenghua Yu, Yingli Cao, Shuai Feng, Tongyu Xu
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Plant Science
Subjects:
rice
aboveground biomass
unmanned aerial vehicle (UAV)
multi-source remote sensing images
ensemble learning
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2025.1576212/full
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https://www.frontiersin.org/articles/10.3389/fpls.2025.1576212/full

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