Alexander Gilerson

Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands.

Remote sensing algorithms that use red and NIR bands for the estimation of chlorophyll-a concentration [Chl] can be more effective in inland and coastal waters than algorithms that use blue and green bands. We tested such two-band and three-band red-NIR algorithms using comprehensive synthetic data sets of reflectance spectra and inherent optical properties related to various water parameters and a very consistent in situ data set from several lakes in Nebraska, USA. The two-band algorithms tested with MERIS bands were Rrs(708)/Rrs(665) and Rrs(753)/Rrs(665). The three-band algorithm with MERIS bands was in the form R3=[Rrs(-1)(665)-Rrs(-1)(708)]×Rrs(753). It is shown that the relationships of both Rrs(708)/Rrs(665) and R3 with [Chl] do not depend much on the absorption by CDOM and non-algal particles, or the backscattering properties of water constituents, and can be defined in terms of water absorption coefficients at the respective bands as well as the phytoplankton specific absorption coefficient at 665 nm. The relationship of the latter with [Chl] was established for [Chl]>1 mg/m3 and then further used to develop algorithms which showed a very good match with field data and should not require regional tuning.

Fluorescence component in the reflectance spectra from coastal waters. Dependence on water composition

Based on HYDROLIGHT simulations of more than 2000 reflectance spectra from datasets typical of coastal waters with highly variable optically active constituents as well as on intercomparisons with field measurements, the magnitude of chlorophyll fluorescence was analyzed and parameterized as a function of phytoplankton, CDOM, and suspended inorganic matter concentrations. Using the parameterizations developed, we show that variations in the fluorescence component of water leaving radiance in coastal waters are due more to the variability of attenuation in the water than to the variability of the fluorescence quantum yield, which we estimate to be relatively stable at around 1%. Finally, the ranges of water conditions where fluorescence plays a significant role in the reflectance NIR peak and where it is effectively undetectable are also determined.

Polarized light in coastal waters: hyperspectral and multiangular analysis.

Measurements of the underwater polarized light field were performed at different stations, atmospheric conditions and water compositions using a newly developed hyperspectral and multiangular polarimeter during a recent cruise in the coastal areas of New York Harbor - Sandy Hook, NJ region (USA). Results are presented for waters with chlorophyll concentrations 1.3-4.8 microg/l and minerals concentrations 2.0- 3.9 mg/l. Angular and spectral variations of the degree of polarization are found to be consistent with theory. Maximum values of the degree of polarization do not exceed 0.4 and the position of the maximum is close to 100 masculine scattering angle. Normalized radiances and degrees of polarization are compared with simulated ones obtained with a Monte Carlo radiative transfer code for the atmosphere-ocean system and show satisfactory agreement.

Novel optical techniques for detecting and classifying toxic dinoflagellate Karenia brevis blooms using satellite imagery

Karenia brevis (K. brevis) blooms are of great interest and have been commonly reported throughout the Gulf of Mexico. In this study we propose a detection technique for blooms with low backscatter characteristics, which we name the Red Band Difference (RBD) technique, coupled with a selective K. brevis bloom classification technique, which we name the K. brevis Bloom Index (KBBI). These techniques take advantage of the relatively high solar induced chlorophyll fluorescence and low backscattering of K. brevis blooms. The techniques are applied to the detection and classification of K. brevis blooms from Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color measurements off the Gulf of Mexico. To assess the efficacy of the techniques for detection and classification, simulations, including chlorophyll fluorescence (assuming 0.75% quantum yield) based on K. brevis blooms and non-K. brevis blooms conditions were performed. These show that effective bloom detection from satellite measurements requires a threshold of RBD>0.15W/m(2)/microm/sr, corresponding to about 5mg/m(3) of chlorophyll. Blooms can be detected at lower concentration by lowering the RBD threshold but false positives may increase. The classification technique is found most effective for thresholds of RBD>0.15W/m(2)/microm/sr and KBBI>0.3*RBD. The techniques were applied and shown to be effective for well documented blooms of K. brevis in the Gulf of Mexico and compared to other detection techniques, including FLH approaches. Impacts of different atmospheric corrections on results were also examined.

Fluorescence component in the reflectance spectra from coastal waters. II. Performance of retrieval algorithms.

Retrieval of chlorophyll fluorescence magnitude using Fluorescence Height algorithms in coastal waters is more complicated than in the open ocean because of the strong deviations of elastic reflectance within the fluorescence band from the derived fluorescence baseline. We use results of our recently established relationship between fluorescence magnitude and concentrations of water constituents together with extensive HYDROLIGHT simulations, field and satellite data to analyze the performance and retrieval limitations of MODIS and MERIS FLH algorithms in the variety of coastal waters and to examine improvements for spectral band selection suitable for future sensors.

Measurements and simulations of polarization states of underwater light in clear oceanic waters.

Polarization states of the underwater light field were measured by a hyperspectral and multiangular polarimeter and a video polarimeter under various atmospheric, surface, and water conditions, as well as solar and viewing geometries, in clear oceanic waters near Port Aransas, Texas. Some of the first comprehensive comparisons were made between the measured polarized light, including the degree and angle of linear polarization and linear Stokes parameters (Q and U), and those from Monte Carlo simulations that used concurrently measured water inherent optical properties and particle volume scattering functions as input. For selected wavelengths in the visible spectrum, measured and model-simulated polarization characteristics were found to be consistent in most cases. Measured degree and angle of linear polarization are found to be largely determined by an in-water single-scattering model. Model simulations suggest that the degree of linear polarization (DoLP) at horizontal viewing directions is highly dependent on the viewing azimuth angle for a low solar elevation. This implies that animals can use the DoLP signal for orientation.

Neural network approach to retrieve the inherent optical properties of the ocean from observations of MODIS

Retrieving the inherent optical properties of water from remote sensing multispectral reflectance measurements is difficult due to both the complex nature of the forward modeling and the inherent nonlinearity of the inverse problem. In such cases, neural network (NN) techniques have a long history in inverting complex nonlinear systems. The process we adopt utilizes two NNs in parallel. The first NN is used to relate the remote sensing reflectance at available MODIS-visible wavelengths (except the 678 nm fluorescence channel) to the absorption and backscatter coefficients at 442 nm (peak of chlorophyll absorption). The second NN separates algal and nonalgal absorption components, outputting the ratio of algal-to-nonalgal absorption. The resulting synthetically trained algorithm is tested using both the NASA Bio-Optical Marine Algorithm Data Set (NOMAD), as well as our own field datasets from the Chesapeake Bay and Long Island Sound, New York. Very good agreement is obtained, with R² values of 93.75%, 90.67%, and 86.43% for the total, algal, and nonalgal absorption, respectively, for the NOMAD. For our field data, which cover absorbing waters up to about 6 m⁻¹, R² is 91.87% for the total measured absorption.

Polarization impacts on the water-leaving radiance retrieval from above-water radiometric measurements

Above-water measurements of water-leaving radiance are widely used for water-quality monitoring and ocean-color satellite data validation. Reflected skylight in above-water radiometry needs to be accurately estimated prior to derivation of water-leaving radiance. Up-to-date methods to estimate reflection of diffuse skylight on rough sea surfaces are based on radiative transfer simulations and sky radiance measurements. But these methods neglect the polarization state of the incident skylight, which is generally highly polarized. In this paper, the effects of polarization on the sea surface reflectance and the subsequent water-leaving radiance estimation are investigated. We show that knowledge of the polarization field of the diffuse skylight significantly improves above-water radiometry estimates, in particular in the blue part of the spectrum where the reflected skylight is dominant. A newly developed algorithm based on radiative transfer simulations including polarization is described. Its application to the standard Aerosol Robotic Network-Ocean Color and hyperspectral radiometric measurements of the 1.5-year dataset acquired at the Long Island Sound site demonstrates the noticeable importance of considering polarization for water-leaving radiance estimation. In particular it is shown, based on time series of collocated data acquired in coastal waters, that the azimuth range of measurements leading to good-quality data is significantly increased, and that these estimates are improved by more than 12% at 413 nm. Full consideration of polarization effects is expected to significantly improve the quality of the field data utilized for satellite data validation or potential vicarious calibration purposes.

Long Island Sound Coastal Observatory: Assessment of above-water radiometric measurement uncertainties using collocated multi and hyperspectral systems

The Long Island Sound Coastal Observational platform (LISCO) near Northport, New York, has been recently established to support validation of ocean color radiometry (OCR) satellite data. LISCO is equipped with collocated multispectral, SeaPRISM, and hyperspectral, HyperSAS, above-water systems for OCR measurements. This combination offers the potential for improving validation activities of current and future OCR satellite missions, as well as for satellite intercomparisons and spectral characterization of coastal waters. Results of measurements made by both the multi and hyperspectral instruments, in operation since October 2009, are presented, evaluated and their associated uncertainties quantified based on observations for a period of over a year. Multi- and hyperspectral data processing as well as the data quality analysis are described and their uncertainties evaluated. The quantified intrinsic uncertainties of HyperSAS data exhibit satisfactory values, less than 5% over a large spectral range, from 340 to 740 nm, and over a large range of diurnal daylight conditions, depending on the maximum sun elevation at the solar noon. Intercomparisons between HyperSAS and SeaPRISM data revealed that an overcorrection of the sun glint effect in the current SeaPRISM processing induces errors, which are amplified through the whole data processing, especially at the shorter wavelengths. The spectral-averaged uncertainties can be decomposed as follows: (i) sun glint removal generates 2% uncertainty, (ii) sky glint removal generates strong uncertainties of the order of 15% mainly induced by sun glint overcorrection, (iii) viewing angle dependence corrections improve the data intercomparison by reducing the dispersion by 2%, (iv) normalization of atmospheric effects generates approximately 4% uncertainty. Based on this study, improvements of the sun glint correction are expected to significantly reduce the uncertainty associated with the data processing down to the level of 1%. On the other hand, strong correlations between both datasets (R(2)>0.96) demonstrate the efficacy of the above-water retrieval concept and confirm that the collocated instrumentation constitutes an important aid to above-water data quality analysis, which makes LISCO a key element of the AERONET-OC network.

Open-ocean fish reveal an omnidirectional solution to camouflage in polarized environments.

Disappearing act Unlike coastal regions and reefs, the open ocean is mostly empty. Many fish species, nonetheless, spend most of their lives there. Such emptiness makes camouflage exceedingly difficult, so how does an organism hide in water filled with bouncing and reflected light? Brady et al. show that some families of fish have evolved skin that reflects and polarizes light, allowing them to blend into their mirrorlike conditions more easily. These results help to explain the silvery coloration found in sea-living fish across the worlds oceans. Science, this issue p. 965 Light-reflecting and -polarizing platelets in their skin permit fish to blend into the mirrorlike open ocean. Despite appearing featureless to our eyes, the open ocean is a highly variable environment for polarization-sensitive viewers. Dynamic visual backgrounds coupled with predator encounters from all possible directions make this habitat one of the most challenging for camouflage. We tested open-ocean crypsis in nature by collecting more than 1500 videopolarimetry measurements from live fish from distinct habitats under a variety of viewing conditions. Open-ocean fish species exhibited camouflage that was superior to that of both nearshore fish and mirrorlike surfaces, with significantly higher crypsis at angles associated with predator detection and pursuit. Histological measurements revealed that specific arrangements of reflective guanine platelets in the fish’s skin produce angle-dependent polarization modifications for polarocrypsis in the open ocean, suggesting a mechanism for natural selection to shape reflectance properties in this complex environment.