Improving efficiency of ground-truth data collection for UAV-based rice growth estimation models: investigating the effect of sampling size on model accuracy-Reference-Cited by-同舟云学术

Improving efficiency of ground-truth data collection for UAV-based rice growth estimation models: investigating the effect of sampling size on model accuracy

Published:2024-01-02 Issue:1 Volume:27 Page:1-13
ISSN:1343-943X
Container-title:Plant Production Science
language:en
Short-container-title:Plant Production Science

Author:

Yamaguchi Tomoaki¹²,Sasano Kana³,Katsura Keisuke¹

Affiliation:

1. United Graduate School of Agriculture Science, Tokyo University of Agriculture and Technology, Tokyo, Japan

2. Japan Society for the Promotion of Science, Tokyo, Japan

3. Graduate School of School of Agriculture, Tokyo University of Agriculture and Technology, Tokyo, Japan

Funder

Japan Science and Technology Agency

Japan International Cooperation Agency

Japan Society for the Promotion of Science

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/1343943X.2023.2299641

Reference40 articles.

1. Soil Heterogeneity and Crop Growth

2. Estimating Yield-Related Traits Using UAV-Derived Multispectral Images to Improve Rice Grain Yield Prediction

3. Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley

4. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Review of Crop Phenotyping in Field Plot Experiments Using UAV-Mounted Sensors and Algorithms;Drones;2024-05-21

2. A novel neural network model to achieve generality for diverse morphologies and crop science interpretability in rice biomass estimation;Computers and Electronics in Agriculture;2024-03