A county-level soybean yield prediction framework coupled with XGBoost and multidimensional feature engineering

A county-level soybean yield prediction framework coupled with XGBoost and multidimensional feature engineering

Yield prediction is essential in food security, food trade, and field management. However, due to the associated complex formation mechanisms of yield, accurate and timely yield prediction remains challenging in remote sensing-based crop monitoring domains. In this study, a framework of soybean yiel...

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Bibliographic Details
Main Authors: Yuanchao Li, Hongwei Zeng, Miao Zhang, Bingfang Wu, Yan Zhao, Xia Yao, Tao Cheng, Xingli Qin, Fangming Wu
Format: Article
Language:English
Published: Elsevier 2023-04-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Soybean
Yield prediction
XGBoost
SHAP
Multidimensional feature engineering
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843223000912

Internet

http://www.sciencedirect.com/science/article/pii/S1569843223000912

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