Prediction of copper contamination in soil across EU using spectroscopy and machine learning: Handling class imbalance problem

Prediction of copper contamination in soil across EU using spectroscopy and machine learning: Handling class imbalance problem

Soil copper (Cu) pollution is a significant global environmental challenge, necessitating accurate assessment methods for effective control. However, existing classification approaches for Cu content in soil spectral datasets often face imbalances in data distribution, resulting in unreliable identi...

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Bibliographic Details
Main Authors: Chongchong Qi, Nana Zhou, Tao Hu, Mengting Wu, Qiusong Chen, Han Wang, Kejing Zhang, Zhang Lin
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Smart Agricultural Technology
Subjects:
Soil contamination
Hyperspectral
Continental scale
Copper
Spectral preprocessing
Imbalanced classification
Online Access:http://www.sciencedirect.com/science/article/pii/S2772375524003320
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