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The importance of atmospheric correction for airborne hyperspectral remote sensing of shallow waters: application?to?depth?estimation

机译:大气校正对浅水机载高光谱遥感的重要性:在深度估计中的应用

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Accurate determination of water depth is indispensable in multiple aspects of civil engineering (dock construction, dikes, submarines outfalls, trench control, etc.). To determine the type of atmospheric correction most appropriate for the depth estimation, different accuracies are required. Accuracy in bathymetric information is highly dependent on the atmospheric correction made to the imagery. The reduction of effects such as glint and cross-track illumination in homogeneous shallow-water areas improves the results of the depth estimations. The aim of this work is to assess the best atmospheric correction method for the estimation of depth in shallow waters, considering that reflectance values cannot be greater than 1.5?% because otherwise the background would not be seen. This paper addresses the use of hyperspectral imagery to quantitative bathymetric mapping and explores one of the most common problems when attempting to extract depth information in conditions of variable water types and bottom reflectances. The current work assesses the accuracy of some classical bathymetric algorithms (Polcyn–Lyzenga, Philpot, Benny–Dawson, Hamilton, principal component analysis) when four different atmospheric correction methods are applied and water depth is derived. No atmospheric correction is valid for all type of coastal waters, but in heterogeneous shallow water the model of atmospheric correction 6S offers good results.
机译:在土木工程的多个方面(码头建设,堤防,潜艇排污口,战trench控制等),准确确定水深是必不可少的。为了确定最适合深度估计的大气校正类型,需要不同的精度。测深信息的准确性高度依赖于对图像进行的大气校正。在均匀的浅水区域中减少诸如闪烁和交叉轨迹照明之类的影响,可以改善深度估计的结果。这项工作的目的是评估用于估计浅水深度的最佳大气校正方法,考虑到反射率值不能大于1.5?%,因为否则将看不到背景。本文探讨了高光谱图像在定量测深图中的应用,并探讨了在可变水类型和底部反射率条件下尝试提取深度信息时最常见的问题之一。当应用四种不同的大气校正方法并得出水深时,当前工作评估了一些经典测深算法(Polcyn–Lyzenga,Philpot,Benny–Dawson,Hamilton,主成分分析)的准确性。对于所有类型的沿海水域,均不能进行大气校正,但是在非均质浅水中,大气校正6S模型可以提供良好的结果。

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