Estimating Soybean Yields Using Causal Inference and Deep Learning Approaches With Satellite Remote Sensing Data

Estimating Soybean Yields Using Causal Inference and Deep Learning Approaches With Satellite Remote Sensing Data

Timely and accurate crop yield estimation is crucial for managing crops, trade, and food security. The combination of remote sensing technology with machine learning methods is increasingly popular for global yield prediction. However, traditional machine learning methods rely on data correlation ra...

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Bibliographic Details
Main Authors: Fumin Wang, Jiale Li, Dailiang Peng, Qiuxiang Yi, Xiaoyang Zhang, Jueyi Zheng, Siting Chen
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Causal inference
deep learning
graph attention network (GAT)
soybean yield prediction
structural causal model (SCM)
Online Access:https://ieeexplore.ieee.org/document/10614767/
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