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| 基于多核学习遥感解译的水边线提取及海岸侵蚀风险评估方法研究与应用——以大蒲河-滦河岸段为例 |
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徐栋1,2, 杨敏1,2, 孟云闪3,2, 孙苗3,2
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1.国家海洋局北海海洋技术保障中心, 山东 青岛 266033;2.国家海洋局数字海洋科学技术重点实验室, 天津 300171;3.国家海洋信息中心, 天津 300171
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| 摘要: |
| 为了对典型海岸带的侵蚀风险程度进行量化统计与评估，采用卫星遥感技术对目标岸段开展动态监测，以多核学习技术进行图像分类及岸线提取，基于水边线逐年位置变化提出一种海岸侵蚀风险评估方法，并以大蒲河-滦河岸段为例进行了应用，得出了该岸段所处的侵蚀风险级别，为下一步海岸带的保护与修复提供了数据支撑。 |
| 关键词: 海岸带 大蒲河-滦河口 多核学习 图像分类 海岸侵蚀风险评估 |
| DOI：10.11759/hykx20190605003 |
| 分类号:P76 |
| 基金项目:国家海洋局数字海洋科学技术重点实验室2018年开放基金（20181120B1413） |
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| Research and application of a waterline extraction and coastal erosion risk assessment method based on multi-kernel learning for remote sensing interpretation—Taking the Dapu River-the Luan River estuary as an example |
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XU Dong1,2, YANG Min1,2, MENG Yun-shan3,2, SUN Miao3,2
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1.North China Sea Marine Technical Support Center, State Oceanic Administration, Qingdao 266033, China;2.Key Laboratory of Digital Ocean, State Oceanic Administration, Tianjin 300171, China;3.National Marine Data and Information Service, Tianjin 300171, China
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| Abstract: |
| To quantify and evaluate the erosion risk of typical coastal zones, we use satellite remote sensing images to monitor the change in the target bank and multi-kernel learning technology to classify and recognize the coastal line. A coastal erosion risk assessment method is proposed according to the position change of the waterline, applied in the area of the Dapu River-the Luan River estuary to obtain the erosion risk level of this section. |
| Key words: coastal zone the Dapu River-the Luan River estuary multi-kernel learning image classification coastal erosion risk assessment |