Modeling the influence of water waves upon remote sensing imagery: the underwater radiance distribution and shape factors

Bostater, Charles R.; Bassetti, Luce; Huddleston, Lisa L.

doi:10.1117/12.834924

Cited by 2 publications

(4 citation statements)

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“…A synthetic water wave surface image is simulated for the surface boundary using a synthetic water surface image model [3,4]. The model utilizes a Weibull probability function approach from Nelson (1982) to simulate the natural water surface conditions based on a calibrated and measured wave gauge using video imagery of the water surface wave field as described by Bostater, et al [2].…”

Section: Methodsmentioning

confidence: 99%

“…This model is used due to its unique ability to calculate upwelling and downwelling irradiances, radiances, reflectance, mean cosines, shape factors, and directional attenuation coefficients in realistic natural waters and can be applied to water columns containing fluid mud lutocline layers. This model has been vigorously tested [1,3,4,5] and compared to selected results of previous Monte Carlo models reported by Gordon [9], Kattawar [15], Morel and Gentilli [19], Stavn [13], Kirk [14], etc. Comparisons of the models repeated in the literature are shown in Table 1.…”

Section: Monte-carlo Model Usedmentioning

confidence: 99%

“…In fact, most sampling of water is based upon instantaneous grab sampling methods. Thus, the role for mathematical modeling to help understand processes in waters with lutoclines 3,4 .…”

Section: Introductionmentioning

confidence: 99%

“…In this research we use sondes (sediment traps) (Bostater and Rotkiske, 2015) to provide spatially and temporally averaged water column particulate properties and the data from the sondes provide input to an optical radiative transfer model using Monte Carlo techniques. The purpose of this paper is to report on an updated Monte-Carlo model 4,5,6,7 and the utilization of information developed by the integration of time and space averaged particulate fluxes (g m -2 s -1 ) within moving fluid mud lutoclines. Methods for measuring depth dependent fluid mud fluxes are discussed by Bostater, Rotkiske, and Oney [8] and others 9,10 .…”

Section: Introductionmentioning

confidence: 99%

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Space coast Florida turbid shallow water Monte-Carlo modeling to support satellite algorithm development for WorldView-3 imagery

Bostater,

Rotkiske

2023

Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2023

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Space Coast Florida waters consist of shallow coastal turbid water along the southeastern United States and Florida’s east coast estuaries and tidal lagoon systems. The waters have become dominated by a bottom boundary sediment layer characterized by moving fluid mud near the bottom. Surface winds and their resulting water surface gravity waves result in the resuspension of the mud bottom boundary layer sediments and result in water columns with very low light visibility. The decreased light penetration as a function of depth and wavelength influences marine life that require light to function. The complex physical phenomena and associated underwater light fields can best be understand using Monte-Carlo models. Model results can be tuned to be applicable to specific satellites and channels for development of algorithms which make use of reflectance signatures measured by satellites as well as in-situ sensors. Recent model developments and model simulations are described with reference to WorldVeiw-3 satellite imagery and shape factors.

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Section: Methodsmentioning

confidence: 99%

Section: Monte-carlo Model Usedmentioning

confidence: 99%

“…In fact, most sampling of water is based upon instantaneous grab sampling methods. Thus, the role for mathematical modeling to help understand processes in waters with lutoclines 3,4 .…”

Section: Introductionmentioning

confidence: 99%