Potential impacts of nonalgal materials on water-leaving Sun induced chlorophyll fluorescence signals in coastal waters

It has been suggested that Sun induced chlorophyll fluorescence (SICF) signals could be used to estimate phytoplankton chlorophyll concentration and to investigate algal physiology from space. However, water-leaving SICF is also a product of the ambient light field. In coastal waters both algal and nonalgal materials affect the underwater light field. In this study we examine the independent impacts of varying loads of mineral suspended solids (MSS) and colored dissolved organic materials (CDOM) on water-leaving SICF signals using Hydrolight radiative transfer simulations. We show that SICF signals in coastal waters are strongly influenced by nonalgal materials. Increasing concentrations of CDOM and minerals can reduce the water-leaving SICF per unit chlorophyll by over 50% for the concentration ranges explored here (CDOM = 0 to 1 m(-1) at 440 nm, MSS=0 to 10 g m(-3)). The moderate-resolution imaging spectroradiometer (MODIS) fluorescence line height algorithm is shown to be relatively unaffected by increasing CDOM, but performance is significantly degraded by mineral concentrations greater than 5 g m(-3) owing to increased background radiance levels. The combination of these two effects means that caution is required for the interpretation of SICF signals from coastal waters.     

Bio-optical properties and ocean color algorithms for coastal waters influenced by the Mississippi River during a cold front

During the passage of a cold front in March 2002, bio-optical properties examined in coastal waters impacted by the Mississippi River indicated that westward advective flows and increasing river discharge containing high concentrations of nonalgal particles contributed significantly to surface optical variability. A comparison of seasonal data from three cruises indicated spectral models of absorption and scattering to be generally consistent with other coastal environments, while their parameterization in terms of chlorophyll (Chl) alpha concentration showed seasonal variability. The exponential slope of the colored dissolved organic matter (CDOM) averaged 0.0161+/-0.00054 nm(-1) and nonalgal absorption averaged 0.011 nm(-1) with deviations from general trends observed due to anomalous water properties. Although the phytoplankton specific absorption coefficients varied over a wide range [0.02 to 0.1 m2 (mg Chl)(-1) at 443 nm] being higher in offshore surface waters, values of phytoplankton absorption spectra at the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) wave bands were highly correlated to modeled values. Particulate scattering characteristics were similar to observations for other coastal waters, while backscattering ratios were on average lower in phytoplankton-dominated surface waters (0.011+/-0.003) and higher in low Chl near-bottom waters (0.0191+/-0.0045). Average percent differences in remote sensing reflectance Rrs derived from modeled and in-water radiometric measurements were highest in the blue wave bands (52%) and at locations with more stratified water columns. SeaWiFS estimates of Chl and CDOM absorption derived using regional empirical algorithms were highly correlated to in situ data.     

Retrieval of chlorophyll from remote-sensing reflectance in the china seas

The East China Sea is a typical case 2 water environment, where concentrations of phytoplankton pigments, suspended matter, and chromophoric dissolved organic matter (CDOM) are all higher than those in the open oceans, because of the discharge from the Yangtze River and the Yellow River. By using a hyperspectral semianalytical model, we simulated a set of remote-sensing reflectance for a variety of chlorophyll, suspended matter, and CDOM concentrations. From this simulated data set, a new algorithm for the retrieval of chlorophyll concentration from remote-sensing reflectance is proposed. For this method, we took into account the 682-nm spectral channel in addition to the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) channels. When this algorithm was applied to a field data set, the chlorophyll concentrations retrieved through the new algorithm were consistent with field measurements to within a small error of 18%, in contrast with that of 147% between the SeaWiFS ocean chlorophyll 2 algorithm and the in situ observation.     

Evaluation of a reflectance model used in the SeaWiFS ocean color algorithm: implications for chlorophyll concentration retrievals

For the atmospheric correction of ocean-color imagery obtained over Case I waters with the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) instrument the method currently used to relax the black-pixel assumption in the near infrared (NIR) relies on (1) an approximate model for the nadir NIR remote-sensing reflectance and (2) an assumption that the water-leaving radiance is isotropic over the upward hemisphere. Radiance simulations based on a comprehensive radiative-transfer model for the coupled atmosphere-ocean system and measurements of the nadir remote-sensing reflectance at 670 nm compiled in the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) database are used to assess the validity of this method. The results show that (1) it is important to improve the flexibility of the reflectance model to provide more realistic predictions of the nadir NIR water-leaving reflectance for different ocean regions and (2) the isotropic assumption should be avoided in the retrieval of ocean color, if the chlorophyll concentration is larger than approximately 6, 10, and 40 mg m(-3) when the aerosol optical depth is approximately 0.05, 0.1, and 0.3, respectively. Finally, we extend our scope to Case II ocean waters to gain insight and enhance our understanding of the NIR aspects of ocean color. The results show that the isotropic assumption is invalid in a wider range than in Case I waters owing to the enhanced water-leaving reflectance resulting from oceanic sediments in the NIR wavelengths.     

Effect of spectral band numbers on the retrieval of water column and bottom properties from ocean color data

Using an optimization technique, we derived subsurface properties of coastal and oceanic waters from measured remote-sensing reflectance spectra. These data included both optically deep and shallow environments. The measured reflectance covered a spectral range from 400 to 800 nm. The inversions used data from each 5-, 10-, and 20-nm contiguous bands, including Sea-viewing Wide Field-of-view Sensor (SeaWiFS), moderate-resolution imaging spectrometer (MODIS), and a self-defined medium-resolution imaging spectrometer (MERIS) channels, respectively. This study is designed to evaluate the influence of spectral resolution and channel placement on the accuracy of remote-sensing retrievals and to provide guidance for future sensor design. From the results of this study, we found the following: (1) use of 10-nm-wide contiguous channels provides almost identical results as found for 5-nm contiguous channels; (2) use of 20-nm contiguous channels and MERIS provides comparable results with those with 5-nm contiguous channels for deep waters, but use of contiguous 20-nm channels perform better than MERIS for optically shallow waters; and (3) SeaWiFS or MODIS channels work fine for deep, clearer waters (total absorption coefficient at 440 nm < 0.3 m(-1)), but introduce more errors in bathymetry retrievals for optically shallow waters. The inclusion of the 645-nm MODIS land band in its channel set improves inversion returns for both deep and shallow waters.     

Hyperspectral remote sensing for shallow waters. I. A semianalytical model

For analytical or semianalytical retrieval of shallow-water bathymetry and/or optical properties of the water column from remote sensing, the contribution to the remotely sensed signal from the water column has to be separated from that of the bottom. The mathematical separation involves three diffuse attenuation coefficients: one for the downwelling irradiance (K(d)), one for the upwelling radiance of the water column (K(u)(C)), and one for the upwelling radiance from bottom reflection (K(u)(B)). Because of the differences in photon origination and path lengths, these three coefficients in general are not equal, although their equality has been assumed in many previous studies. By use of the Hydrolight radiative-transfer numerical model with a particle phase function typical of coastal waters, the remote-sensing reflectance above (R(rs)) and below (r(rs)) the surface is calculated for various combinations of optical properties, bottom albedos, bottom depths, and solar zenith angles. A semianalytical (SA) model for r(rs) of shallow waters is then developed, in which the diffuse attenuation coefficients are explicitly expressed as functions of in-water absorption (a) and backscattering (b(b)). For remote-sensing inversion, parameters connecting R(rs) and r(rs) are also derived. It is found that r(rs) values determined by the SA model agree well with the exact values computed by Hydrolight (~3% error), even for Hydrolight r(rs) values calculated with different particle phase functions. The Hydrolight calculations included b(b)/a values as high as 1.5 to simulate high-turbidity situations that are occasionally found in coastal regions.     

Optical remote sensing of chlorophyll a in case 2 waters by use of an adaptive two-band algorithm with optimal error properties

Two-band algorithms that use the ratio of reflectances at 672 and 704 nm have already proved successful for chlorophyll a retrieval in a range of coastal and inland waters. An analysis of the effect of reflectance measurement errors on such algorithms is made. It provides important indications of the range of validity of these algorithms and motivates the development of an entirely new type of adaptive two-band algorithm for hyperspectral data, whereby the higher wavelength is chosen for each input spectrum individually. When one selects the wavelength at which reflectance is equal to the reflectance at the red chlorophyll a absorption peak, chlorophyll a retrieval becomes entirely insensitive to spectrally flat reflectance errors, which are typical of imperfect atmospheric correction, and is totally uncoupled from the retrieval or an estimation of backscatter. This new algorithm has been tested for Dutch inland and Belgian coastal waters.     

Remote-sensing reflectance determinations in the coastal ocean environment: impact of instrumental characteristics and environmental variability

Three independent ocean color sampling methodologies are compared to assess the potential impact of instrumental characteristics and environmental variability on shipboard remote-sensing reflectance observations from the Santa Barbara Channel, California. Results indicate that under typical field conditions, simultaneous determinations of incident irradiance can vary by 9-18%, upwelling radiance just above the sea surface by 8-18%, and remote-sensing reflectance by 12-24%. Variations in radiometric determinations can be attributed to a variety of environmental factors such as Sun angle, cloud cover, wind speed, and viewing geometry; however, wind speed is isolated as the major source of uncertainty. The above-water approach to estimating water-leaving radiance and remote-sensing reflectance is highly influenced by environmental factors. A model of the role of wind on the reflected sky radiance measured by an above-water sensor illustrates that, for clear-sky conditions and wind speeds greater than 5 m/s, determinations of water-leaving radiance at 490 nm are undercorrected by as much as 60%. A data merging procedure is presented to provide sky radiance correction parameters for above-water remote-sensing reflectance estimates. The merging results are consistent with statistical and model findings and highlight the importance of multiple field measurements in developing quality coastal oceanographic data sets for satellite ocean color algorithm development and validation.     

Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization

In earlier studies of passive remote sensing of shallow-water bathymetry, bottom depths were usually derived by empirical regression. This approach provides rapid data processing, but it requires knowledge of a few true depths for the regression parameters to be determined, and it cannot reveal in-water constituents. In this study a newly developed hyperspectral, remote-sensing reflectance model for shallow water is applied to data from computer simulations and field measurements. In the process, a remote-sensing reflectance spectrum is modeled by a set of values of absorption, backscattering, bottom albedo, and bottom depth; then it is compared with the spectrum from measurements. The difference between the two spectral curves is minimized by adjusting the model values in a predictor-corrector scheme. No information in addition to the measured reflectance is required. When the difference reaches a minimum, or the set of variables is optimized, absorption coefficients and bottom depths along with other properties are derived simultaneously. For computer-simulated data at a wind speed of 5 m/s the retrieval error was 5.3% for depths ranging from 2.0 to 20.0 m and 7.0% for total absorption coefficients at 440 nm ranging from 0.04 to 0.24 m(-1). At a wind speed of 10 m/s the errors were 5.1% for depth and 6.3% for total absorption at 440 nm. For field data with depths ranging from 0.8 to 25.0 m the difference was 10.9% (R(2) = 0.96, N = 37) between inversion-derived and field-measured depth values and just 8.1% (N = 33) for depths greater than 2.0 m. These results suggest that the model and the method used in this study, which do not require in situ calibration measurements, perform very well in retrieving in-water optical properties and bottom depths from above-surface hyperspectral measurements.     

Method to derive ocean absorption coefficients from remote-sensing reflectance

A method to derive in-water absorption coefficients from total remote-sensing reflectance (ratio of the upwelling radiance to the downwelling irradiance above the surface) analytically is presented. For measurements made in the Gulf of Mexico and Monterey Bay, with concentrations of chlorophyll-a ranging from 0.07 to 50 mg/m(3), comparisons are made for the total absorption coefficients derived with the suggested method and those derived with diffuse attenuation coefficients. For these coastal to open-ocean waters, including regions of upwelling and the Loop Current, the results are as follows: at 440 nm the difference between the two methods is 13.0% (r(2) = 0.96) for total absorption coefficients ranging from 0.02 to 2.0 m(-1); at 488 nm the difference is 14.5% (r(2) = 0.97); and at 550 nm the difference is 13.6% (r(2) = 0.96). The results indicate that the method presented works very well for retrieval of in-water absorption coefficients exclusively from remotely measured signals, and that this method has a wide range of potential applications in oceanic remote sensing.     

Effects of a nonuniform vertical profile of chlorophyll concentration on remote-sensing reflectance of the ocean

Numerical simulations of radiative transfer were used to examine the effects of a nonuniform vertical profile of the inherent optical properties of the water column associated with the vertical profile of chlorophyll concentration, Chl(z), on the spectral remote-sensing reflectance, Rrs(gamma), of the ocean. Using the Gaussian function that describes the Chl(z) profile, we simulated a relatively broad range of open-ocean conditions characterized by the presence of a subsurface Chl maximum at depths greater than or equal to 20 m. The simulations for a vertically nonuniform Chl(z) were compared with reference simulations for a homogeneous ocean whose Chl was identical to the surface Chl of inhomogeneous cases. The range of values for the Gaussian parameters that produce significant differences in Rrs(gamma) (> 5%) was determined. For some vertical structures of Chl(z) considered, the magnitude of Rrs(gamma) and the blue-to-green band ratios of Rrs(gamma) differ significantly from the reference values of homogeneous ocean (> 70% in extreme cases of low surface chlorophyll of 0.02 mg m(-3) and shallow pigment maximum at 20 m). The differences are small or negligible when the nonuniform profiles are characterized by a surface Chl greater than 0.4 mg m(-3) or a depth of Chl maximum greater than 45 m (65 m in extremely clear waters with a surface Chl of 0.02 mg m(-3) or less). The comparison of modeling results with the current algorithm for retrieving the global distribution of chlorophyll from satellite imagery of ocean color suggests that strong effects of the subsurface chlorophyll maximum on reflectance at low surface chlorophyll concentrations can lead to a severalfold overestimation in the algorithm-derived surface chlorophyll. Examples of field data from the Sea of Japan and the north polar Atlantic Ocean are used to illustrate various nonuniform pigment profiles and their effect on the blue-to-green ratio of Rrs(gamma).     

Atmospheric correction of satellite ocean color imagery: the black pixel assumption

The assumption that values of water-leaving radiance in the near-infrared (NIR) are negligible enable aerosol radiative properties to be easily determined in the correction of satellite ocean color imagery. This is referred to as the black pixel assumption. We examine the implications of the black pixel assumption using a simple bio-optical model for the NIR water-leaving reflectance [rho(w)(lambda(NIR))](N). In productive waters [chlorophyll (Chl) concentration >2 mg m(-3)], estimates of [rho(w)(lambda(NIR))](N) are several orders of magnitude larger than those expected for pure seawater. These large values of [rho(w)(lambda(NIR))](N) result in an overcorrection of atmospheric effects for retrievals of water-leaving reflectance that are most pronounced in the violet and blue spectral region. The overcorrection increases dramatically with Chl, reducing the true water-leaving radiance by roughly 75% when Chl is equal to 5 mg m(-3). Relaxing the black pixel assumption in the correction of Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) satellite ocean color imagery provides significant improvements in Chl and water-leaving reflectance retrievals when Chl values are greater than 2 mg m(-3). Improvements in the present modeling of [rho(w)(lambda(NIR))](N) are considered, particularly for turbid coastal waters. However, this research shows that the effects of nonzero NIR reflectance must be included in the correction of satellite ocean color imagery.     

Band-ratio or spectral-curvature algorithms for satellite remote sensing?

For the retrieval of chlorophyll concentrations or the total absorption coefficients of oceanic waters based on water color, there are algorithms that use either band ratios or spectral curvatures of remote-sensing reflectance or water leaving radiance. We show that band-ratio algorithms have the potential to be applied to a wider dynamic range of oceanic waters, whereas spectral-curvature algorithms show stable performance as long as the data set falls within the appropriate range.     

Remote-sensing reflectance in the Beaufort and Chukchi seas: observations and models

Two semianalytical remote-sensing reflectance models were evaluated and validated by use of bio-optical data collected in the Beaufort and Chukchi seas. Both models were efficient at retrieving chlorophyll concentration, phytoplankton absorption coefficients,and particulate backscattering coefficients. In contrast, they were not accurate in predicting an absorption coefficient for colored dissolved organic matter plus nonpigmented particulates. The poor model performance is attributed to the high variability in the concentrations of these colored materials. A chlorophyll-dependent reflectance model was also assessed, and it proved to be highly successful in reproducing measured reflectance spetra. A four-component, case 2 model with mean absorption spectra for phytoplankton, soluble materials, and nonpigmented particulates was employed in Hydrolight radiative-transfer model simulations. The remote sensing reflectance spectra simulated inthe radiative-transfer model were in excellent agreement with field data. The similarity between the model and the measurement confirms the accuracy of the underlying bio-optical relationships and underscores the utility of modeling for better understanding of the variability of ocean color observations. The latest SeaWiFS algorithm (OC4V4) overestimated chlorophyll by approximately 1.5 fold across most of the observed range of biomass (0.07-9 mg chlorophyll m(-3)). Regionally tuned algorithms explained > 93% of the variability in the surface chlorophyll concentration.     

Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function

The bidirectionality of the upward radiance field in oceanic case 1 waters has been reinvestigated by incorporation of revised parameterizations of inherent optical properties as a function of the chlorophyll concentration (Chl), considering Raman scattering and making the particle phase function shape (beta(rho)) continuously varying along with the Chl. Internal consistency is thus reached, as the decrease in backscattering probability (for increasing Chl) translates into a correlative change in beta(rho). The single particle phase function (previously used) precluded a realistic assessment of bidirectionality for waters with Chl > 1 mg m(-3). This limitation is now removed. For low Chl, Raman emissions significantly affect the radiance field. For moderate Chl (0.1-1 mg m(-3)), new and previous bidirectional parameters remain close. The ocean reflectance anisotropy has implications in ocean color remote-sensing problems, in derivation of coherent water-leaving radiances, in associated calibration-validation activities, and in the merging of data obtained under various geometrical configurations.     

Optical influence of ship wakes

The optical variations observed within ship wakes are largely due to the generation of copious amounts of air bubbles in the upper ocean, a fraction of which accumulate as foam at the surface, where they release scavenged surfactants. Field experiments were conducted to test previous theoretical predictions of the variations in optical properties that result from bubble injection in the surface ocean. Variations in remote-sensing reflectance and size distribution of bubbles within the ship-wake zone were determined in three different optical water types: the clear equatorial Pacific Ocean, moderately turbid coastal waters, and very turbid coastal waters, the latter two of which were offshore of New Jersey. Bubbles introduced by moving vessels increased the backscattering in all cases, which in turn enhanced the reflectance over the entire visible and infrared wave bands. The elevated reflectance had different spectral characteristics in the three locations. The color of ship wakes appears greener in the open ocean, whereas little change in color was observed in near-coastal turbid waters, consistent with predictions. Colorless themselves, bubbles increase the reflected radiance and change the color of the ocean in a way that depends on the spectral backscattering and absorption of the undisturbed background waters. For remote observation from aircraft or satellite, the foam and added surfactants further enhance the reflectance to a degree dependent on the illumination and the viewing geometry.     

Covariance of the absorption of phytoplankton, colored dissolved organic matter, and detritus in case I waters, as deduced from the Coastal Zone Color Scanner bio-optical algorithm

The universal bio-optical algorithm of the Coastal Zone Color Scanner (CZCS) for case I waters implicitly contains an average covariance of the absorption by phytoplankton and colored dissolved organic matter (CDOM) and detritus. We made that covariance explicit by combining the CZCS algorithm with an expression for reflectance. The spectral variation of absorption by CDOM plus detritus for case I waters may be estimated by the expression a(gd(λ)) = 2a(ph)(443)*chl{exp[-0.013(λ - 443)].     

Remote-sensing reflectance of turbid sediment-dominated waters. Reduction of sediment type variations and changing illumination conditions effects by use of reflectance ratios

Variations of sediment type (grain size and refractive index) and changing illumination conditions affect the reflectance signal of coastal waters and limit the accuracy of sediment-concentration estimations from remote-sensing measurements. These effects are analyzed from numerous in situ remote-sensing measurements carried out in the Gironde and Loire Estuaries and then reduced and partly eliminated when reflectance ratios between the near infrared and the visible are considered. These ratios showed high correlation with the sediment concentration. On the basis of the obtained relationships, performing correspondence functions were established that allow an accurate estimation of suspended sediments in the estuaries from Système Probatoire d'Observation de la Terre, Landsat, and Sea-Viewing Wide Field-of-View Sensor data, independently of the date of acquisition.     

Satellite retrieval of inherent optical properties by inversion of an oceanic radiance model: a preliminary algorithm

A previously published radiance model inversion theory has been field tested by using airborne water-leaving radiances to retrieve the chromophoric dissolved organic matter (CDOM) and detritus absorption coefficient, the phytoplankton absorption coefficient, and the total backscattering coefficient. The radiance model inversion theory was tested for potential satellite use by comparing two of the retrieved inherent optical properties with concurrent airborne laser-derived truth data. It was found that (1) matrix inversion of water-leaving radiances is well conditioned even in the presence of instrument-induced noise, (2) retrieved CDOM and detritus and phytoplankton absorption coefficients are both in reasonable agreement with absorption coefficients derived from airborne laser-induced fluorescence spectral emissions, (3) the total backscattering retrieval magnitude and variability are consistent with expected values for the Middle Atlantic Bight, and (4) the algorithm performs reasonably well in Sargasso Sea, Gulf Stream, slope, and shelf waters but is less consistent in coastal waters.     

Factor analysis of multispectral radiances over coastal and open ocean water based on radiative transfer calculations

Factor analysis is applied to multispectral (seventeen wavelengths) radiances simulated by a radiative transfer model (matrix-operator method) in and above coastal and open ocean waters. The calculated radiances were compared with measured radiances before applying factor analysis. They agree well for different sun elevations and even for turbid coastal waters. The factor analysis technique allows us to extract the characteristic signatures of phytoplankton, suspended matter, and yellow substance. The fluorescence of chlorophyll at lambda = 685 nm is found to be a clear signal for phytoplankton, also in the presence of other suspensions and yellow substance. A comparison of different algorithms for the extraction of the fluorescence peak favors the addition of chlorophyll absorption at lambda = 670 nm. The blue-green ratio is found to be useless for chlorophyll detection in coastal waters. Suspended matter and yellow substance can also clearly be seen in the factor loading for all multispectral radiances analyzed. However, suspended matter is reflected more strongly than yellow substance.