Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data

Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data

Accurate soybean yield estimation is critically imperative for modern agricultural systems amid escalating global food security pressures, yet conventional methodologies are constrained for large-scale high-frequency monitoring. To address this, an innovative deep learning framework, TransBiHGRU-PSO...

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Bibliographic Details
Main Authors: Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning (DL)
greenness and water content composite index (GWCCI)
multisource remote sensing data
yield estimation
Online Access:https://ieeexplore.ieee.org/document/11079987/
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https://ieeexplore.ieee.org/document/11079987/

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