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作 者:李阳东[1,2,3] 温远超 笪亨融 梁君豪 LI Yangdong;WEN Yuanchao;DA Hengrong;LIANG Junhao(College of Marine Science,Shanghai Ocean University,Shanghai 201306,China;Key Laboratory of Oceanic Fisheries Exploration,Ministry of Agriculture and Rural Affaires,Shanghai 201306,China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources,Ministry of Education,Shanghai 201306,China)
机构地区:[1]上海海洋大学海洋科学学院,上海201306 [2]农业农村部大洋渔业开发重点实验室,上海201306 [3]大洋渔业资源可持续开发教育部重点实验室,上海201306
出 处:《海洋通报》2022年第3期281-289,共9页Marine Science Bulletin
基 金:国家自然科学基金(41506211);国家重点研发计划(2019YFD0901404)。
摘 要:准确提取海岸水边线是海岸线变迁研究中必不可少的基本工作。本文以海南省陵水黎族自治县2016年的GF-2影像为数据源,在大气校正和正射校正等预处理的基础上,结合数学形态学处理等方法,采用NDWI(Normalized Difference Water Index)阈值法、ISOADTA(Iterative Self-Organizing Data Analysis Technique Algorithm)、SVM(Support Vector Machine)和面向对象法(Object-Oriented Classification,OOC)等4种不同方法来对海岸水边线进行提取,并对其提取结果进行定性和定量评估,进而分析比较了这4种方法在提取人工海岸、砂质海岸和基岩海岸等3种不同海岸类型的水边线时的提取效果和提取精度。结果表明,SVM方法在3种海岸水边线上的总体提取效果最好,总体提取精度最高。It is essential to extract the coastal waterline accurately in the study of coastline change. In this paper, one GF-2 image of Lingshui Autonomous County of Hainan Province in 2016 was taken as the data source. On the basis of atmospheric correction and orthorectification, combined with mathematical morphology processing and other methods, NDWI(Normalized Difference Water Index) Threshold Segmentation, ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm),SVM(Support Vector Machine) and OOC(Object-Oriented Classification) were used to extract the coastal waterlines. The extraction results were qualitatively and quantitatively evaluated. Then, the extraction effects and extraction accuracy of these four methods in extracting the coastal waterlines of three different coastal types, namely artificial coast, bedrock coast and sandy coast,were analyzed. The results show that the SVM method has the best overall extraction effect and the highest over-all extraction accuracy on the three types of coastal waterlines.
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