Global de-trending significantly improves the accuracy of XGBoost-based county-level maize and soybean yield prediction in the Midwestern United States

The application of machine learning in crop yield prediction has gained considerable traction, yet uncertainties persist regarding the impact of the yield trends on these predictions and the differences between the detrending methods. In our study, we utilized extreme gradient boosting (XGBoost) to...

Full description

Saved in:
Bibliographic Details
Main Authors: Yuanchao Li, Hongwei Zeng, Miao Zhang, Bingfang Wu, Xingli Qin
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:GIScience & Remote Sensing
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/15481603.2024.2349341
Tags: Add Tag
No Tags, Be the first to tag this record!