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Influence of Bottom Depths and Bottom Types on Water Surface Reflectance

机译:底部深度和底部类型对水面反射率的影响

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Two flow irradiance model solutions are tested using various bottom depths and hyperspectral in-situ bottom reflectance signatures for Elkhorn Coral, Bleached Reef, Sand, Sand and Seagrass, and Turtle Grass. Bottom reflectance signatures are used to simulate a water surface reflectance signatures from analytical solutions that can account for the effect of a collimated irradiance signal or direct sunlight within the water column. Simulated reflectance signatures are generated as a function of depth and wavelength in an optically clear water column and a turbid estuarine water column containing concentrations of chlorophyll-a, seston, and dissolved organic material. Simulated surface reflectance signatures as a function of water depth are then used to predict bottom reflectance signatures. Comparison of in-situ bottom reflectance signatures to simulated bottom reflectance signatures predicts model depth sensitivity at a 95% confidence level. Spectral window solutions for water column depths are detected for bottom types and estuarine type water column concentrations. Model can be coupled with bathymetry and high resolution water surface sensor derived reflectance signatures to monitor or map bottom variations for surveillance, environmental monitoring, fishing, or dredging applications in coastal waters or very shallow estuarine waters.
机译:两个流辐射模型解决方案是使用各种底部深度和高光谱测试现场的麋角珊瑚,珊瑚礁漂白,沙子,沙子和海草,和草龟底部反射特征。底部反射特征用于从分析的解决方案,可以考虑水柱内的准直辐射信号或阳光直射的影响模拟水表面的反射特征。模拟反射率签名被作为深度和波长的光学透明的水列的函数和含叶绿素a,浮游物的浓度混浊河口水柱,和溶解的有机材料产生的。模拟表面反射率的签名作为水深的函数然后被用来预测底反射特征。原位底部反射特征来模拟底部反射特征的比较预测在95%的置信水平模型深度灵敏度。为底的类型和河口型水柱浓度检测到水柱深度光谱窗口的解决方案。模型可以与水深和高分辨率水面传感器导出的反射特征被耦合到监视或用于监控,环境监测,钓鱼,或在沿海水域疏浚应用或很浅的河口水域底部映射变化。

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