Machine Learning Strategies for the Retrieval of Leaf-Chlorophyll Dynamics: Model Choice, Sequential Versus Retraining Learning, and Hyperspectral Predictors

Machine Learning Strategies for the Retrieval of Leaf-Chlorophyll Dynamics: Model Choice, Sequential Versus Retraining Learning, and Hyperspectral Predictors

Monitoring leaf Chlorophyll (Chl) in-situ is labor-intensive, limiting representative sampling for detailed mapping of Chl variability at field scales across time. Unmanned aeria-l vehicles (UAV) and hyperspectral cameras provide flexible platforms for observing agricultural systems, overcoming this...

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Bibliographic Details
Main Authors: Yoseline Angel, Matthew F. McCabe
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-03-01
Series:Frontiers in Plant Science
Subjects:
chlorophyll
hyperspectral image
SPAD – leaf greenness
machine learning
UAV
multitemporal analyses
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2022.722442/full

Internet

https://www.frontiersin.org/articles/10.3389/fpls.2022.722442/full

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