论文标题
使用多光谱图像的多空间，多节奏的半分析模型，水浊度和底部成分
A Multi-Spatial, Multi-Temporal, Semi-Analytical Model for Bathymetry, Water Turbidity and Bottom Composition using Multispectral Imagery
论文作者
论文摘要
在本文中，我们引入了一种半分析模型，用于水浊度和底部成分。这主要基于Lee等人的基于物理的模型。与最初设计用于使用高光谱图像的Lee模型不同，我们的模型是专门设计用于使用多光谱卫星图像的。特别是，我们通过在深度和水浊度上引入时间和空间假设来适应光谱分辨率的大大降低。我们通过在西澳大利亚州穆里恩群岛（Murion Islands）地区进行的260 km2案例研究来验证Lee等人模型的扩展，在那里我们将大气校正的Landsat-8衍生的测深量法与西澳大利亚运输运输公司进行的2011年单束声纳调查进行了比较。该模型对单光束声纳调查进行了很好的验证，R^2 = 0.85，平均绝对误差为1.17 m，平均相对误差为7.52％。这表明该模型可以广泛适用于Landsat-8图像。
In this paper we introduce a semi-analytical model for bathymetry, water turbidity and bottom composition; which is primarily based on the physics-based model, HOPE, of Lee et al. Unlike the model of Lee, which was originally designed to use hyperspectral imagery, our model is specifically designed to use multispectral satellite imagery. In particular, we adapt to the greatly decreased spectral resolution by introducing temporal and spatial assumptions on the depth and water turbidity. We validate the extensions to the Lee et al model with a 260 km2 case study in the area of the Murion Islands off Western Australia, where we compare the atmospherically-corrected LANDSAT-8 derived bathymetry against a 2011 single-beam sonar survey by Transport Western Australia. The model validates well against the single-beam sonar survey, with R^2 = 0.85, a mean absolute error of 1.17 m and a mean relative error of 7.52%. This indicates the model could be widely applicable to LANDSAT-8 imagery.
