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邴磊,邹娜娜,过杰,丛旭东,林勐,史湘君.基于星载SAR和AIS构建海面溢油监测方法[J].广西科学院学报,2016,32(2):79-82. [点击复制]
- BING Lei,ZOU Nana,GUO Jie,CONG Xudong,LIN Meng,SHI Xiangjun.Conception of Method for Marine Oil Spill Monitoring Based on Spaceborne SAR and AIS[J].Journal of Guangxi Academy of Sciences,2016,32(2):79-82. [点击复制]
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基于星载SAR和AIS构建海面溢油监测方法 |
邴磊1,2,3, 邹娜娜4, 过杰1, 丛旭东3, 林勐5, 史湘君3
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(1.中国科学院烟台海岸带研究所, 山东烟台 264003;2.中国科学院大学, 北京 100049;3.烟台海事局, 山东烟台 264000;4.烟台五中, 山东烟台 264001;5.北京市遥感信息研究所, 北京 100085) |
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摘要: |
溢油事故对海洋环境造成的危害越来越严重,多种遥感技术被应用于海洋环境的监测,卫星遥感技术,特别是合成孔径雷达(SAR)遥感技术已成为海面溢油监测的重要手段;但由于海面溢油成像特征的复杂性,单一的遥感识别仍然存在较大难度。本研究提出结合船舶自动识别系统(AIS)等辅助信息,对海面溢油进行判别,再利用边缘检测算法自动提取溢油信息的方法,并以Radarsat-2数据为例进行案例分析。结果表明,该方法能够有效提高溢油识别和检测的准确性。 |
关键词: 溢油 合成孔径雷达 自动识别系统 边缘检测 Radarsat-2数据 |
DOI: |
投稿时间:2015-11-10 |
基金项目:交通运输部海事局2015年科技项目(2015-13)资助。 |
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Conception of Method for Marine Oil Spill Monitoring Based on Spaceborne SAR and AIS |
BING Lei1,2,3, ZOU Nana4, GUO Jie1, CONG Xudong3, LIN Meng5, SHI Xiangjun3
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(1.Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, Shandong, 264003, China;2.University of Chinese Academy of Sciences, Beijing, 100049, China;3.Yantai Maritime Safety Administration, Yantai, Shandong, 264000, China;4.Yantai No. 5 Middle School, Yantai, Shandong, 264001, China;5.Beijing Institute of Remote Sensing Information, Beijing, 100085, China) |
Abstract: |
In recent years, the frequent occurrence of marine oil spill accidents give a serious threat to marine environment and transportation safety. Satellite remote sensing, especially Synthetic Aperture Radar (SAR) is considered as a powerful tool to be used for marine oil spill monitoring. Because of the complexity of the imaging features, it is difficult to detect oil spills based on SAR images itself. In this paper, we focuse on identification technology of oil spills by using spaceborne SAR images and AIS. Then, discusses method of extracting the scope and area of pollution automatically by using edge detection algorithm. A case study of Radarsat-2 was discussed finally. The results show that this method was proved to be effective on SAR images in improving accuracy of oil spill detection. |
Key words: oil spill SAR AIS edge detection Radarsat-2 data |
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