Spatio-Temporal Estimation of Biomass Growth in Rice Using Canopy Surface Model from Unmanned Aerial Vehicle Images

Spatio-Temporal Estimation of Biomass Growth in Rice Using Canopy Surface Model from Unmanned Aerial Vehicle Images

The awareness of spatial and temporal variations in site-specific crop parameters, such as aboveground biomass (total dry weight: (TDW), plant length (PL) and leaf area index (LAI), help in formulating appropriate management decisions. However, conventional monitoring methods rely on time-consuming...

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Bibliographic Details
Main Authors: Clement Oppong Peprah, Megumi Yamashita, Tomoaki Yamaguchi, Ryo Sekino, Kyohei Takano, Keisuke Katsura
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Remote Sensing
Subjects:
precision agriculture
unmanned aerial vehicle
digital surface model
leaf area index
rice
biomass
Online Access:https://www.mdpi.com/2072-4292/13/12/2388

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