A Seasonal Fresh Tea Yield Estimation Method with Machine Learning Algorithms at Field Scale Integrating UAV RGB and Sentinel-2 Imagery

A Seasonal Fresh Tea Yield Estimation Method with Machine Learning Algorithms at Field Scale Integrating UAV RGB and Sentinel-2 Imagery

Traditional methods for estimating tea yield mainly rely on manual sampling surveys and empirical estimation, which are labor-intensive and time-consuming. Accurately estimating fresh tea production in different seasons has become a challenging task. It is possible to estimate the seasonal yield of...

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Bibliographic Details
Main Authors: Huimei Liu, Yun Liu, Weiheng Xu, Mei Wu, Leiguang Wang, Ning Lu, Guanglong Ou
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Plants
Subjects:
fresh tea yield estimation
machine learning
uncrewed aerial vehicle
feature selection
multiple regression models
Online Access:https://www.mdpi.com/2223-7747/14/3/373
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