Paper
14 September 2009 Modeling the influence of water waves upon remote sensing imagery: the underwater radiance distribution and shape factors
Author Affiliations +
Abstract
This paper describes the results of modeling the water wave surface and underwater light field as influenced by water waves using a Monte Carlo model (MCHSIM). Model and sensor data related to water column properties and benthic properties that influence the light upwelled from below the water - as observed from a sensor looking from below or above the water surface is presented. Synthetic image results using Monte Carlo techniques show the influence of water waves upon subsurface shape factors and these factors can be used in shallow water remote sensing algorithms that are based on underlying analytical models. The upwelling angular distribution of light is calculated from the model and results shown for 490 nm. The upwelling and downwelling shape factors are shown from model runs which compare the results with solar zenith angle for nadir viewing geometry, and for realistic water surface wave facets. It is clearly shown that shape factors are strongly dependent upon not only viewing geometry and zenith angle of the sun, but also upon water waves that can focus and defocus radiance entering a wind roughened water column and influence the shape factors due to the scattering lobe effect. This paper presents results quantifying the magnitude of water effects upon the upwelling and downwelling shape factors in a systematic and quantifiable manner at 490 nm and demonstrates the utility of the model to assess the influence of water waves in a full 3-D Monte Carlo hyperspectral synthetic image cube model that accounts for adjacency effects.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles R. Bostater, Luce Bassetti, and Lisa Huddleston "Modeling the influence of water waves upon remote sensing imagery: the underwater radiance distribution and shape factors", Proc. SPIE 7473, Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2009, 74730E (14 September 2009); https://doi.org/10.1117/12.834924
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Cited by 1 scholarly publication.
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KEYWORDS
Monte Carlo methods

3D modeling

Photons

Remote sensing

Atmospheric modeling

Shape analysis

3D image processing

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