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High Resolution Multispectral Remote Sensing for Shallow Sea Topography Detection and Its Application in Lingshui Bay, Hainan

机译:海南岭辉湾浅海地形检测高分辨率多光谱遥感及其应用

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Water depth is an important marine elements, and one of the main contents of marine surveying andmapping. Compared with traditional single-beam and multi-beam sonar measurement methods, remote sensingmethod has become an important supplementary method for bathymetric data of the area that the vessel can notbe directly reached,due to its advantages of large-scale and low-cost.Sun glitter is an interference factor of shallow water depth multispectral remote sensing, and it contains waterdepth information. Therefore, how to separate the sun glitter information and water radiation information, andimprove the inversion ability of water depth using the two parts of information, is a scientific and practicalresearch topic.In this study, the Lingshui Bay of Hainan Island was selected as the main study area, and the sun glitter separationmethod of high resolution multispectral remote sensing images and the semi-empirical water depth inversionmodels are evaluated and analyzed. And a multi-spectral remote sensing inversion method for water depthwithout the support of measured water depth data was developed. The following research results are obtained:The semi-empirical water depth inversion models were used for inversion and evaluation analysis of the waterradiation information obtained by different sun glitter separation methods. Results showed that the logarithmicratio depth model with blue and green bands is the best in the shallow area of 10 m. When the solar radiation ofremote sensing image is weak, the best water depth inversion results can be obtained using Martin algorithm, theR2 is 0.94, the RMSE is 1.27m. When the solar radiation of remote sensing image is strong, the best water depthinversion results can be obtained using Hedley algorithm, the R2 is 0.89, the RMSE is 0.94m.A multispectral remote sensing water depth inversion algorithm without the support of measured water depthdata was developed based on sun glitter information and water radiation information. The evaluation resultsshowed that RMSE is 0.92m in shallow waters with depth less than 6m. Therefore, this algorithm has a certainapplication potential in shallow sea area without measured data.
机译:水深是一个重要的海洋元素,以及海洋测量和海洋测量的主要内容之一映射。与传统的单梁和多光束声纳测量方法相比,遥感方法已成为船不能的区域的碱基数据的重要补充方法直接达到,由于其大规模和低成本的优点。太阳闪光是浅水深度多光谱遥感的干扰系数,它含有水深度信息。因此,如何分离太阳闪光信息和水辐射信息,以及使用两部分信息提高水深的反转能力,是一种科学和实践研究主题。在这项研究中,选择海南岛的Lingshui湾被选为主要研究区,而阳光闪光分离高分辨率多光谱遥感图像的方法及半经验水深反转评估和分析模型。和水深的多光谱遥感反演方法没有开发测量的水深数据的支持。获得以下研究结果:半经验水深反转模型用于水的反转和评估分析通过不同的阳光闪光分离方法获得的辐射信息。结果表明对数与蓝色和绿色带的比率深度模型是10米的浅面积中最好的。当太阳辐射时遥感图像较弱,可以使用Martin算法获得最佳的水深反演结果,R2为0.94,RMSE为1.27米。当遥感图像的太阳辐射很强,最好的水深可以使用Hedley算法获得反演结果,R2为0.89,RMSE为0.94米。没有测量水深的载体的多光谱遥感水深反演算法数据是基于Sun闪光信息和水辐射信息开发的。评估结果显示RMSE在浅水区中为0.92米,深度小于6米。因此,该算法具有一定的算法浅海域的应用势,没有测量数据。

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