| 采用Rel-Copypaste的京津冀地区尾矿库内部要素提取 |
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| 引用本文： | 王浩洋,张小咏,吴 凯,陈正超.采用Rel-Copypaste的京津冀地区尾矿库内部要素提取[J].福州大学学报(自然科学版),2023,51(4):525-531. |
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| 作者姓名： | 王浩洋 张小咏 吴 凯 陈正超 |
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| 作者单位： | 北京信息科技大学高动态导航技术北京市重点实验室,北京信息科技大学高动态导航技术北京市重点实验室,内蒙古自治区大数据中心,中国科学院空天信息创新研究院 |
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| 基金项目： | 国家自然科学基金资助项目(42071407)；高分辨率对地观测系统重大专项(03-Y30F03-9001-20/22) |
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| 摘 要： | 准确提取尾矿库坝体、干滩、废水内部要素对尾矿库的安全隐患监测具有重要意义。本研究利用国产高分六号数据构建针对尾矿库内部要素分割的Rel-Copypaste数据增强方法，实现数据集扩充；基于深度学习语义分割SE-ResUNet网络实现京津冀地区尾矿库内部要素轮廓提取。该模型平均提取精度高达85.06%，分别高出无数据增强方法、Copypaste数据增强方法2.53%，1.77%，实现京津冀地区尾矿库的面积统计、尾矿库的分类以及头顶库的筛查等。
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| 关 键 词： | 尾矿库内部要素提取 京津冀地区 深度学习 数据增强 语义分割 |
| 收稿时间： | 2022/7/14 0:00:00 |
| 修稿时间： | 2022/10/17 0:00:00 |
Extraction of internal elements of tailings pond in Beijing-Tianjin-Hebei region based on Rel-Copypaste |
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| WANG Haoyang,ZHANG Xiaoyong,WU Kai,CHEN Zhengchao.Extraction of internal elements of tailings pond in Beijing-Tianjin-Hebei region based on Rel-Copypaste[J].Journal of Fuzhou University(Natural Science Edition),2023,51(4):525-531. |
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| Authors: | WANG Haoyang ZHANG Xiaoyong WU Kai CHEN Zhengchao |
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| Affiliation: | Beijing Key Laboratory of High Dynamic Navigation Technology,Beijing Key Laboratory of High Dynamic Navigation Technology,Inner Mongolia Big Data Center,Aerospace Information Research Institute, Chinese Academy of Sciences |
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| Abstract: | Accurate extraction of the internal elements of tailings pond dam, dry beach and waste water is of great significance to the monitoring of potential safety hazards in tailings ponds. In this study, a Rel-Copypaste Data augmentation method for the segmentation of internal elements of tailings ponds is constructed by using the domestic high-definition No. 6 data to realize data set expansion; based on deep learning semantic segmentation SE-ResUNet network to achieve contour extraction of internal elements of tailings pond in Beijing-Tianjin-Hebei region. The average extraction accuracy of the model is as high as 85.06%, which is 2.53% and 1.77% higher than the no Data augmentation method and the Copypaste Data augmentation method, respectively. The model realizes the area statistics of tailings ponds in the Beijing-Tianjin-Hebei region, the classification of tailings ponds, and the screening of overhead ponds. |
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