矿产保护与利用2026，Vol.46Issue(1)：68-77,10.DOI:10.13779/j.cnki.issn1001-0076.2026.01.002
基于改进YOLOv8s算法的离子型稀土矿非法开采检测方法
An Identification Method for Illegal Mining of Ionic Rare Earth Ores Based on the Improved YOLOv8 Algorithm
摘要
Abstract
The intelligent monitoring of ion-type rare earth mining operations is of great significance for ecological environment monitoring and the sustainable development of resources.With the rapid advancement of drone remote sensing,computer technology,and deep learning,high-resolution image data has provided new methods for detecting and extracting illegal mining activities in ion-type rare earth mining areas.Against this backdrop,a detection method for illegal mining in rare earth mining areas based on an improved YOLOv8s algorithm was proposed.This method incorporates a small-object detection layer,enhancing the accuracy of detecting illegal mining with small and concealed targets.Finally,the VoVGSCSP feature extraction module was introduced into the neck network to further optimize the feature transmission network,thereby improving the algorithm's detection performance and operational efficiency.Experimental results demonstrate that the proposed improved method significantly enhances the detection of illegal mining in rare earth mining areas,achieving an average precision and F1 score of 78.7%and 77%,respectively.Compared to the baseline algorithm,the improved YOLOv8s algorithm achieves a 2.8%increase in average detection precision and a 4%improvement in F1 score.When compared to various object detection algorithms,the proposed method exhibits clear advantages,surpassing Faster R-CNN by 19.22%and 31%in average precision and F1 score,respectively.Additionally,this algorithm enables rapid and precise detection of concealed illegal mining activities in complex natural environments of rare earth mining areas while effectively improving the identification and localization capabilities of illegal mining targets.This method can provide accurate and effective technical support for the intelligent monitoring of ion-type rare earth mining operations.关键词
离子型稀土矿/非法开采/YOLOv8算法/深度学习/目标检测Key words
ion-type rare earth ore/illegal mining/YOLOv8 algorithm/deep learning/object detection分类
矿业与冶金引用本文复制引用
刘锟铭,龙北平,孟祥龙,李兴梅..基于改进YOLOv8s算法的离子型稀土矿非法开采检测方法[J].矿产保护与利用,2026,46(1):68-77,10.基金项目
自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室开放基金项目(MEMI-2023-02) （MEMI-2023-02）
江西省地质局青年科学技术带头人培养计划项目(2024JXDZKJRC07) （2024JXDZKJRC07）
