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Utilizing high-performance computing to improve performance and investigate sensitivity of an inversion model for hyperspectral remote sensing of shallow coral ecosystems.

机译:利用高性能计算来改善性能,并研究用于浅层珊瑚生态系统的高光谱遥感反演模型的敏感性。

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This research presents a sensitivity analysis of a semi-analytical inversion model for hyperspectral remote sensing of shallow coral ecosystems. Using this inversion model, five parameters describing water column bioptical properties, bathymetry and magnitude of bottom reflectance are retrieved. In addition to the parameters of interest, the model contains 12 nuisance parameters that are traditionally assigned a fixed set of values. A sensitivity analysis of estimates retrieved to these nuisance parameters is accomplished using SimLab software to study their impact on model output. The computationally intensive analysis was enabled implementing the inversion model within a parallel processing framework using GENCAN. The sensitivity analysis was used to identify which nuisance parameters are most influential on the parameters of interest. The nuisance parameters found to be most relevant are: S, the spectral slope of the absorption coefficient for gelbstoff, Y, the spectral power coefficient for calculating the backscattering coefficient, and Dop, a constant in the equation for the distribution function for scattered photons from the bottom.
机译:这项研究提出了一种浅层珊瑚生态系统高光谱遥感半解析反演模型的敏感性分析。使用该反演模型,检索了描述水柱生物特征,测深法和底部反射率大小的五个参数。除了感兴趣的参数外,模型还包含12个传统上被分配了固定值的讨厌参数。使用SimLab软件研究对这些讨厌参数的估计值进行敏感性分析,以研究它们对模型输出的影响。能够使用GENCAN在并行处理框架内实施计算密集型分析。灵敏度分析用于确定哪些干扰参数对目标参数的影响最大。已发现最相关的干扰参数为:S,gelbstoff吸收系数的光谱斜率,Y,用于计算反向散射系数的光谱功率系数,以及Dop,其为来自散射光子的分布函数方程中的常数底部。

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