Remote-sensing reflectance (Rrs ratio of the water- leaving radiance to the downwelling irradiance above the surface) with and without a vertical polarizer in front of the sensor were derived for measurements made at 90 degrees to the solar plane and in a direction 30 degrees to nadir. These measurements were carried out to see if a vertical polarizer mounted in front of a sensor would improve the Rrs results. For 28 pairs of measurements with chlorophyll- a concentrations ranging from 0.07 to 38 mg/m3, solar zenith angles from 18 degrees to 66 degrees, clear to cloudy skies, and for optically shallow and deep waters, there was no significant variation between the polarized and unpolarized Rrs values. Statistical comparisons of polarized to unpolarized results provided R2 values of 0.987, 0.987, 0.994, and 0.999 with slopes 1.007, 1.005, 0.983 and 0.998 for wavelengths at 410, 440, 550 and 630 nm, respectively. These results suggest that although the underwater light field is partially polarized, a vertical polarizer in front of a sensor will provide close results to unpolarized sensor, if the measurements were made in a direction 90 degrees to the solar plane and 30 degrees to the nadir.
Remote-sensing reflectance and inherent optical properties of oceanic properties of oceanic waters are important parameters for ocean optics. Due to surface reflectance, Rrs or water-leaving radiance is difficult to measure from above the surface. It usually is derived by correcting for the reflected skylight in the measured above-water upwelling radiance using a theoretical Fresnel reflectance value. As it is difficult to determine the reflected skylight, there are errors in the Q and E derived Rrs, and the errors may get bigger for high chl_a coastal waters. For better correction of the reflected skylight,w e propose the following derivation procedure: partition the skylight into Rayleigh and aerosol contributions, remove the Rayleigh contribution using the Fresnel reflectance, and correct the aerosol contribution using an optimization algorithm. During the process, Rrs and in-water inherent optical properties are derived at the same time. For measurements of 45 sites made in the Gulf of Mexico and Arabian Sea with chl_a concentrations ranging from 0.07 to 49 mg/m3, the derived Rrs and inherent optical property values were compared with those from in-water measurements. These results indicate that for the waters studied, the proposed algorithm performs quite well in deriving Rrs and in- water inherent optical properties from above-surface measurements for clear and turbid waters.
In many coastal oceans of the world, the flora and fauna are under stress. In some areas, seagrasses, coral reefs, fish stocks, and marine mammals are disappearing at a rate great enough to capture the attention of, and in some cases, provoke action by local, national, and international governing bodies. The governmental concern and consequent action is most generally rooted in the economic consequences of the collapse of coastal ecosystems. In the United States, for example, some experts believe that the rapid decline of coral reef communities within coastal waters is irreversible. If correct, the economic impact on the local fisheries and tourism industries would be significant. Most scientists and government policy makers agree that remedial action is in order. The ability to make effective management decisions is hampered, however, by the convolution of the potential causes of the decline and by the lack of historical or even contemporary data quantifying the standing stock of the natural resource of concern. Without resource assessment, neither policy decisions intended to respond to ecological crises nor those intended to provide long-term management of coastal resources can be prudently made. This contribution presents a methodology designed to assess the standing stock of immobile coastal resources (eg. seagrasses and corals) at high spatial resolution utilizing a suite of optical instrumentation operating from unmanned underwater vehicles (UUVs) which exploits the multi-spectral albedo and fluorescence signatures of the flora and fauna.
Remote sensing reflectance is easier to interpret for the open ocean than for coastal regions since bottom reflectance and fluorescence from colored dissolved organic matter (CDOM) need not be considered. For estuarine or coastal waters, the reflectance is less easy to interpret because of the variable terrigenous CDOM, suspended sediments, and bottom reflectance, since these factors do not covary with the pigment concentration. To estimate the pigment concentration, the water-leaving radiance signal must be corrected for the effects of these non- covarying factors. A two-parameter model is presented to model remote sensing reflectance of the water-column, to which contributions due to CDOM fluorescence, water Raman scattering, and bottom reflectance have been added. The purpose of this research is to try to understand the separate contributions of the water-column, CDOM fluorescence, water Raman, and bottom reflectance for stations on the West Florida Shelf and Lake Tahoe. This model requires data with spectral resolution of 10 nm or better, consistent with that provided by AVIRIS and expected from HIRIS.
The modeling of oceanic remote sensing reflectance typically
employs absorption and scattering parameters for the various
constituents present in marine waters. Trans-spectral light sources
such as fluorescence and Raman scattering are not generally
parameterized in these models. Bioluminescence is not considered to be
a significant contributor to water-leaving radiance measurements
obtained mid-day, and has not been included in the models either. In
this paper we present evidence of effects due to these three phenomena
by comparing model results to remote sensing reflectances measured at
several stations during the 1988 California Coastal Transition Zone
(CTZ) Experiment. Differences between modeled and measured Rrs(A)
values are discussed from the perspective of in-situ light source
contributions.
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