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

Charles R. Bostater Jr.; Tyler Rotkiske; Taylor Oney

doi:10.1117/12.2241547

18 November 2016 Hyperspectral reflectance signature protocol for predicting subsurface bottom reflectance in water: in-situ and analytical methods

Charles R. Bostater Jr., Tyler Rotkiske, Taylor Oney

Author Affiliations +

Proceedings Volume 9999, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2016; 99990N (2016) https://doi.org/10.1117/12.2241547
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom

Abstract

In-situ measurement of bottom reflectance signatures and 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.

Citation Download Citation

Charles R. Bostater Jr., Tyler Rotkiske, and Taylor Oney "Hyperspectral reflectance signature protocol for predicting subsurface bottom reflectance in water: in-situ and analytical methods", Proc. SPIE 9999, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2016, 99990N (18 November 2016); https://doi.org/10.1117/12.2241547

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