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随机森林模型在遥感水深反演中的应用
引用本文:邱耀炜,沈蔚,纪茜.随机森林模型在遥感水深反演中的应用[J].海洋技术,2019,38(5).
作者姓名:邱耀炜  沈蔚  纪茜
作者单位:上海海洋大学海洋科学学院,上海201306;上海河口海洋测绘工程技术研究中心,上海201306;上海海洋大学海洋科学学院,上海201306;上海河口海洋测绘工程技术研究中心,上海201306;上海海洋大学海洋科学学院,上海201306;上海河口海洋测绘工程技术研究中心,上海201306
基金项目:上海市科委重点科研资助项目
摘    要:随着我国浅海测绘需求的日益增长,文中利用四波段的WorldView-2高分辨率遥感影像,选取我国南海西沙群岛中的甘泉岛和台湾南湾地区作为典型试验区,开展水深反演研究。引入随机森林算法构建了随机森林水深反演模型,并同常用的3种水深反演模型进行精度对比。结果表明,在甘泉岛和南湾地区随机森林模型反演的水深值和真实水深值的RMSE分别为0.85 m和1.59 m,MRE分别为8%和12%,均优于其他3种模型。

关 键 词:水深遥感  Worldview-2  随机森林  甘泉岛  台湾南湾

Satellite-Derived Bathymetry using Random Forest Model
QIU Yao-wei,SHEN Wei and JI Qian.Satellite-Derived Bathymetry using Random Forest Model[J].Ocean Technology,2019,38(5).
Authors:QIU Yao-wei  SHEN Wei and JI Qian
Institution:1. College of Marine Science, Shanghai Ocean University, Shanghai 201306, China; 2. Shanghai Engineering Research Center of Estuarine and Oceanographic Mapping, Shanghai 201306, China,1. College of Marine Science, Shanghai Ocean University, Shanghai 201306, China; 2. Shanghai Engineering Research Center of Estuarine and Oceanographic Mapping, Shanghai 201306, China and 1. College of Marine Science, Shanghai Ocean University, Shanghai 201306, China; 2. Shanghai Engineering Research Center of Estuarine and Oceanographic Mapping, Shanghai 201306, China
Abstract:With the growing demand for shallow sea surveying and mapping in China, this paper uses four-bands high resolution WorldView-2 images to conduct satellite-derived bathymetry experiments in the Ganquan Island and the Nanwan area in Taiwan. The random forest satellite-derived bathymetry model is constructed by using the random forest algorithm, and the accuracy is compared with three classic satellite-derived bathymetry model. The results show that the bathymetry accuracy of the random forest model is optimal in Ganquan Island and Nanwan area, with RMSE are 0.85m and 1.59m, and MRE are 8% and 12%, respectively.
Keywords:satellite-derived bathymetry  Worldview-2  random forest  Ganquan Island  Nanwan Taiwan
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