An investigation on the best-fit models for sugarcane biomass estimation by linear mixed-effect modelling on unmanned aerial vehicle-based multispectral images: A case study of Australia

An investigation on the best-fit models for sugarcane biomass estimation by linear mixed-effect modelling on unmanned aerial vehicle-based multispectral images: A case study of Australia

Due to the worldwide population growth and the increasing needs for sugar-based products, accurate estimation of sugarcane biomass is critical to the precise monitoring of sugarcane growth. This research aims to find the imperative predictors correspond to the random and fixed effects to improve the...

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Bibliographic Details
Main Authors:	Sharareh Akbarian, Chengyuan Xu, Weijin Wang, Stephen Ginns, Samsung Lim
Format:	Article
Language:	English
Published:	Elsevier 2023-09-01
Series:	Information Processing in Agriculture
Subjects:	Sugarcane biomass estimation Unmanned Aerial Vehicle (UAV) Random effects Nitrogen fertilizer treatment Model selection Vegetation Index (VI)
Online Access:	http://www.sciencedirect.com/science/article/pii/S2214317322000324

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