GOA-optimized deep learning for soybean yield estimation using multi-source remote sensing data

GOA-optimized deep learning for soybean yield estimation using multi-source remote sensing data

Abstract Accurately estimating large-area crop yields, especially for soybeans, is essential for addressing global food security challenges. This study introduces a deep learning framework that focuses on precise county-level soybean yield estimation in the United States. It utilizes a wide range of...

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Bibliographic Details
Main Authors: Jian Lu, Hongkun Fu, Xuhui Tang, Zhao Liu, Jujian Huang, Wenlong Zou, Hui Chen, Yue Sun, Xiangyu Ning, Jian Li
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
GOA
Deep learning framework
Multi-source remote sensing data
Soybean yield estimation
Photosynthesis-related parameters
Online Access:https://doi.org/10.1038/s41598-024-57278-6

Internet

https://doi.org/10.1038/s41598-024-57278-6

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