Estimating Maize Crop Height and Aboveground Biomass Using Multi-Source Unmanned Aerial Vehicle Remote Sensing and Optuna-Optimized Ensemble Learning Algorithms

Estimating Maize Crop Height and Aboveground Biomass Using Multi-Source Unmanned Aerial Vehicle Remote Sensing and Optuna-Optimized Ensemble Learning Algorithms

Accurately assessing maize crop height (CH) and aboveground biomass (AGB) is crucial for understanding crop growth and light-use efficiency. Unmanned aerial vehicle (UAV) remote sensing, with its flexibility and high spatiotemporal resolution, has been widely applied in crop phenotyping studies. Tra...

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Bibliographic Details
Main Authors: Yafeng Li, Changchun Li, Qian Cheng, Fuyi Duan, Weiguang Zhai, Zongpeng Li, Bohan Mao, Fan Ding, Xiaohui Kuang, Zhen Chen
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Remote Sensing
Subjects:
unmanned aerial vehicle
crop height
accumulated incremental height
aboveground biomass
ensemble learning
Online Access:https://www.mdpi.com/2072-4292/16/17/3176

Internet

https://www.mdpi.com/2072-4292/16/17/3176

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