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Hyperspectral reflectance signature protocol for predicting subsurface bottom reflectance in water: in-situ and analytical methods

机译:用于预测水中地下底部反射率的高光谱反射鉴定方案:原位和分析方法

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In-situ measurement of bottom reflectance signatures & bottom features in water are used to test an analytical based irradiance model protocol. Comparisons between predicted and measured bottom reflectance signatures are obtained using measured hyperspectral remote sensing reflectance signatures, water depth and water column constituent concentrations. Analytical solutions and algorithms are used to generate synthetic signatures of different bottom types. The analytical methodology used to simulated bottom reflectance contains offset and bias that can be corrected using spectral window based corrections. Example results are demonstrated for application to coral species, submerged aquatic vegetation and a sand bottom type. Spectral windows are identified for predicting the above bottom types. Sensitivity analysis of predicted bottom reflectance signatures is conducted by varying water depth, chlorophyll, dissolved organic matter and total suspended mater concentrations. The protocol can be applied to shallow subsurface geospatial mapping using sensor based water surface reflectance based upon an analytical model solution derived from primitive radiative transfer theory.
机译:原位测量水中的底部反射率和底部特征用于测试基于分析的辐照模型协议。使用测量的高光谱遥感反射率,水深和水柱构成浓度获得预测和测量的底部反射距离之间的比较。分析解决方案和算法用于生成不同底部类型的合成签名。用于模拟底部反射率的分析方法包括可以使用基于频谱窗口的校正来校正的偏移和偏置。对珊瑚物种,淹没的水生植被和沙底型施用来证明实施例结果。识别光谱窗口以预测上述底部类型。通过不同的水深,叶绿素,溶解的有机物和总悬浮母体浓度进行预测底部反射率鉴定的灵敏度分析。基于原始辐射转移理论的分析模型解决方案,可以应用于基于传感器的水表面反射率的浅地下空间映射。

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