An inherent-optical-property-centered approach to correct the angular effects in water-leaving radiance

Remote-sensing reflectance (R(rs)), which is defined as the ratio of water-leaving radiance (L(w)) to downwelling irradiance just above the surface (E(d)(0?)), varies with both water constituents (including bottom properties of optically-shallow waters) and angular geometry. L(w) is commonly measured in the field or by satellite sensors at convenient angles, while E(d)(0?) can be measured in the field or estimated based on atmospheric properties. To isolate the variations of R(rs) (or L(w)) resulting from a change of water constituents, the angular effects of R(rs) (or L(w)) need to be removed. This is also a necessity for the calibration and validation of satellite ocean color measurements. To reach this objective, for optically-deep waters where bottom contribution is negligible, we present a system centered on water's inherent optical properties (IOPs). It can be used to derive IOPs from angular R_rs and offers an alternative to the system centered on the concentration of chlorophyll. This system is applicable to oceanic and coastal waters as well as to multiband and hyperspectral sensors. This IOP-centered system is applied to both numerically simulated data and in situ measurements to test and evaluate its performance. The good results obtained suggest that the system can be applied to angular R(rs) to retrieve IOPs and to remove the angular variation of R(rs).     

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.     

Adaptive semianalytical inversion of ocean color radiometry in optically complex waters

To address the challenges of the parameterization of ocean color inversion algorithms in optically complex waters, we present an adaptive implementation of the linear matrix inversion method (LMI) [J. Geophys. Res.101, 16631 (1996)], which iterates over a limited number of model parameter sets to account for naturally occurring spatial or temporal variability in inherent optical properties (IOPs) and concentration specific IOPs (SIOPs). LMI was applied to a simulated reflectance dataset for spectral bands representing measured water properties of a macrotidal embayment characterized by a large variability in the shape and amplitude factors controlling the IOP spectra. We compare the inversion results for the single-model parameter implementation to the adaptive parameterization of LMI for the retrieval of bulk IOPs, the IOPs apportioned to the optically active constituents, and the concentrations of the optically active constituents. We found that ocean color inversion with LMI is significantly sensitive to the a priori selection of the empirical parameters g0 and g1 of the equations relating the above-surface remote-sensing reflectance to the IOPs in the water column [J. Geophys. Res.93, 10909 (1988)]. When assuming the values proposed for open-ocean applications for g0 and g1 [J. Geophys. Res.93, 10909 (1988)], the accuracy of the retrieved IOPs, and concentrations was substantially lower than that retrieved with the parameterization developed for coastal waters [Appl. Opt.38, 3831 (1999)] because the optically complex waters analyzed in this study were dominated by particulate and dissolved matter. The adaptive parameterization of LMI yielded consistently more accurate inversion results than the single fixed SIOP model parameterizations of LMI. The adaptive implementation of LMI led to an improvement in the accuracy of apportioned IOPs and concentrations, particularly for the phytoplankton-related quantities. The adaptive parameterization encompassing wider IOP ranges were more accurate for the retrieval of bulk IOPs, apportioned IOPs, and concentration of optically active constituents.     

Uniqueness in remote sensing of the inherent optical properties of ocean water

We examine the problem of uniqueness in the relationship between the remote-sensing reflectance (Rrs) and the inherent optical properties (IOPs) of ocean water. The results point to the fact that diffuse reflectance of plane irradiance from ocean water is inherently ambiguous. Furthermore, in the 400 < lambda < 750 nm region of the spectrum, Rrs(lambda) also suffers from ambiguity caused by the similarity in wavelength dependence of the coefficients of absorption by particulate matter and of absorption by colored dissolved organic matter. The absorption coefficients have overlapping exponential responses, which lead to the fact that more than one combination of IOPs can produce nearly the same Rrs spectrum. This ambiguity in absorption parameters demands that we identify the regions of the Rrs spectrum where we can isolate the effects that are due only to scattering by particulates and to absorption by pure water. The results indicate that the spectral shape of the absorption coefficient of phytoplankton, a(ph)(lambda), cannot be derived from a multiparameter fit to Rrs(lambda). However, the magnitude and the spectral dependence of the absorption coefficient can be estimated from the difference between the measured Rrs(lambda) and the best fit to Rrs(lambda) in terms of IOPs that exclude a(ph)(lambda).     

Effect of atmospheric interference and sensor noise in retrieval of optically active materials in the ocean by hyperspectral remote sensing

We present a method to construct the best linear estimate of optically active material concentration from ocean radiance spectra measured through an arbitrary atmosphere layer by a hyperspectral sensor. The algorithm accounts for sensor noise. Optical models of seawater and maritime atmosphere were used to obtain the joint distribution of spectra and concentrations required for the algorithm. The accuracy of phytoplankton retrieval is shown to be substantially lower than that of sediment and dissolved matter. In all cases, the sensor noise noticeably reduces the retrieval accuracy. Additional errors due to atmospheric interference are analyzed, and possible ways to increase the accuracy of retrieval are suggested, such as changing sensor parameters and including a priori information about observation conditions.     

Atmospheric correction of SeaWiFS imagery for turbid coastal and inland waters

The standard SeaWiFS atmospheric correction algorithm, designed for open ocean water, has been extended for use over turbid coastal and inland waters. Failure of the standard algorithm over turbid waters can be attributed to invalid assumptions of zero water-leaving radiance for the near-infrared bands at 765 and 865 nm. In the present study these assumptions are replaced by the assumptions of spatial homogeneity of the 765:865-nm ratios for aerosol reflectance and for water-leaving reflectance. These two ratios are imposed as calibration parameters after inspection of the Rayleigh-corrected reflectance scatterplot. The performance of the new algorithm is demonstrated for imagery of Belgian coastal waters and yields physically realistic water-leaving radiance spectra. A preliminary comparison with in situ radiance spectra for the Dutch Lake Markermeer shows significant improvement over the standard atmospheric correction algorithm. An analysis is made of the sensitivity of results to the choice of calibration parameters, and perspectives for application of the method to other sensors are briefly discussed.     

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.     

Optimization of a semianalytical ocean color model for global-scale applications

Semianalytical (SA) ocean color models have advantages over conventional band ratio algorithms in that multiple ocean properties can be retrieved simultaneously from a single water-leaving radiance spectrum. However, the complexity of SA models has stalled their development, and operational implementation as optimal SA parameter values are hard to determine because of limitations in development data sets and the lack of robust tuning procedures. We present a procedure for optimizing SA ocean color models for global applications. The SA model to be optimized retrieves simultaneous estimates for chlorophyll (Chl) concentration, the absorption coefficient for dissolved and detrital materials [a(cdm)(443)], and the particulate backscatter coefficient [b(bp)(443)] from measurements of the normalized water-leaving radiance spectrum. Parameters for the model are tuned by simulated annealing as the global optimization protocol. We first evaluate the robustness of the tuning method using synthetic data sets, and we then apply the tuning procedure to an in situ data set. With the tuned SA parameters, the accuracy of retrievals found with the globally optimized model (the Garver-Siegel-Maritorena model version 1; hereafter GSM01) is excellent and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl. The advantage of the GSM01 model is that simultaneous retrievals of a(cdm)(443) and b(bp)(443) are made that greatly extend the nature of global applications that can be explored. Current limitations and further developments of the model are discussed.     

Assessment of a bidirectional reflectance distribution correction of above-water and satellite water-leaving radiance in coastal waters

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm. This confirms the advantages of the proposed model over the current one, demonstrating the need for a specific case 2 water BRDF correction algorithm as well as the feasibility of enhancing performance of current and future satellite ocean color remote sensing missions for monitoring of typical coastal waters.     

Optical remote sensing of marine constituents in coastal waters: a feasibility study

Optical remote sensing of ocean color is a well-established technique for inferring ocean properties. However, most retrieval algorithms are based on the assumption that the radiance received by satellite instruments is affected only by the phytoplankton pigment concentration and correlated substances. This assumption works well for open ocean water but becomes questionable for coastal waters. To reduce uncertainties associated with this assumption, we developed a new algorithm for the retrieval of marine constituents in a coastal environment. We assumed that ocean color can be adequately described by a three-component model made up of chlorophyll a, suspended matter, and yellow substance. The simultaneous retrieval of these three marine constituents and of the atmospheric aerosol content was accomplished through an inverse-modeling scheme in which the difference between simulated radiances exiting the atmosphere and radiances measured with a satellite sensor was minimized. Simulated radiances were generated with a comprehensive radiative transfer model that is applicable to the coupled atmosphere-ocean system. The method of simulated annealing was used to minimize the difference between measured and simulated radiances. To evaluate the retrieval algorithm, we used simulated (instead of measured) satellite-received radiances that were generated for specified concentrations of aerosols and marine constituents, and we tested the ability of the algorithm to retrieve assumed concentrations. Our results require experimental validation but show that the retrieval of marine constituents in coastal waters is possible.     

Reflectance recovery for airborne sensor images of 3D scenes

An airborne sensor measures the radiance spectrum, which is dependent on the spectral reflectance of the ground material, the orientation of the material surface, and the atmospheric and illumination conditions. We present an algorithm to estimate the surface spectral reflectance, given the sensor radiance spectrum corresponding to a single pixel. The algorithm uses a nonlinear physics-based image formation model. A low-dimensional linear subspace model is used for the reflectance spectra. The solar radiance, sky radiance, and path-scattered radiance are dependent on the environmental conditions and viewing geometry, and this interdependence is considered by using a coupled-subspace model for these spectra. The algorithm uses the Levenberg-Marquardt method to estimate the subspace model parameters. We have applied the algorithm to a large set of synthetic and real data.     

Remote sensing of ocean color: a methodology for dealing with broad spectral bands and significant out-of-band response

A methodology for delineating the influence of finite spectral bandwidths and significant out-of-band response of sensors for remote sensing of ocean color is developed and applied to the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS). The basis of the method is the application of the sensor's spectral-response functions to the individual components of the top-of-the-atmosphere (TOA) radiance rather than the TOA radiance itself. For engineering purposes, this approach allows one to assess easily (and quantitatively) the potential of a particular sensor design for meeting the system-sensor plus algorithms-performance requirements. In the case of the SeaWiFS, two significant conclusions are reached. First, it is found that the out-of-band effects on the water-leaving radiance component of the TOA radiance are of the order of a few percent compared with a sensor with narrow spectral response. This implies that verification that the SeaWiFS system-sensor plus algorithms-meets the goal of providing the water-leaving radiance in the blue in clear ocean water to within 5% will require measurements of the water-leaving radiance over the entire visible spectrum as opposed to just narrow-band (10-20-nm) measurements in the blue. Second, it is found that the atmospheric correction of the SeaWiFS can be degraded by the influence of water-vapor absorption in the shoulders of the atmospheric-correction bands in the near infrared. This absorption causes an apparent spectral variation of the aerosol component between these two bands that will be uncharacteristic of the actual aerosol present, leading to an error in correction. This effect is dependent on the water-vapor content of the atmosphere. At typical water-vapor concentrations the error is larger for aerosols with a weak spectral variation in reflectance than for those that display a strong spectral variation. If the water-vapor content is known, a simple procedure is provided to remove the degradation of the atmospheric correction. Uncertainty in the water-vapor content will limit the accuracy of the SeaWiFS correction algorithm.     

Contribution of Raman scattering to water-leaving radiance: a reexamination

We have reexamined the contribution of Raman scattering to the water-leaving radiance in case 1 waters by carrying out radiative transfer simulations that combine the latest reported measurements of the absorption coefficient of pure water with direct measurements of the spectral variation of the Raman-scattering coefficient. The resulting contribution of Raman scattering is then compared with experimental measurements of the water-leaving radiance, and the fractional contribution of radiance produced by Raman scattering to the total radiance measured at a given wavelength is determined. The results show that (1) the contribution of Raman scattering to the water-leaving radiance in an ocean of pure seawater is as much as 50-100% larger than earlier predictions, and (2) the Raman contribution does not decay as rapidly with increasing concentrations of chlorophyllouslike pigments C as predicted earlier. In fact, the Raman fraction for C 8% at wavelengths of interest in ocean color remote sensing and therefore cannot be ignored in ocean color modeling.     

Remote sensing of ocean color and aerosol properties: resolving the issue of aerosol absorption

Current atmospheric correction and aerosol retrieval algorithms for ocean color sensors use measurements of the top-of-the-atmosphere reflectance in the near infrared, where the contribution from the ocean is known for case 1 waters, to assess the aerosol optical properties. Such measurements are incapable of distinguishing between weakly and strongly absorbing aerosols, and the atmospheric correction and aerosol retrieval algorithms fail if the incorrect absorption properties of the aerosol are assumed. We present an algorithm that appears promising for the retrieval of in-water biophysical properties and aerosol optical properties in atmospheres containing both weakly and strongly absorbing aerosols. By using the entire spectrum available to most ocean color instruments (412-865 nm), we simultaneously recover the ocean's bio-optical properties and a set of aerosol models that best describes the aerosol optical properties. The algorithm is applied to simulated situations that are likely to occur off the U.S. East Coast in summer when the aerosols could be of the locally generated weakly absorbing Maritime type or of the pollution-generated strongly absorbing urban-type transported over the ocean by the winds. The simulations show that the algorithm behaves well in an atmosphere with either weakly or strongly absorbing aerosol. The algorithm successfully identifies absorbing aerosols and provides close values for the aerosol optical thickness. It also provides excellent retrievals of the ocean bio-optical properties. The algorithm uses a bio-optical model of case 1 waters and a set of aerosol models for its operation. The relevant parameters of both the ocean and atmosphere are systematically varied to find the best (in a rms sense) fit to the measured top-of-the-atmosphere spectral reflectance. Examples are provided that show the algorithm's performance in the presence of errors, e.g., error in the contribution from whitecaps and error in radiometric calibration.     

Remote sensing of the ocean contributions from ultraviolet to near-infrared using the shortwave infrared bands: simulations

In the remote sensing of the ocean near-surface properties, it is essential to derive accurate water-leaving radiance spectra through the process of the atmospheric correction. The atmospheric correction algorithm for Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) uses two near-infrared (NIR) bands at 765 and 865 nm (748 and 869 nm for MODIS) for retrieval of aerosol properties with assumption of the black ocean at the NIR wavelengths. Modifications are implemented to account for some of the NIR ocean contributions for the productive but not very turbid waters. For turbid waters in the coastal regions, however, the ocean could have significant contributions in the NIR, leading to significant errors in the satellite-derived ocean water-leaving radiances. For the shortwave infrared (SWIR) wavelengths (approximately > 1000 nm), water has significantly larger absorption than those for the NIR bands. Thus the black ocean assumption at the SWIR bands is generally valid for turbid waters. In addition, for future sensors, it is also useful to include the UV bands to better quantify the ocean organic and inorganic materials, as well as for help in atmospheric correction. Simulations are carried out to evaluate the performance of atmospheric correction for nonabsorbing and weakly absorbing aerosols using the NIR bands and various combinations of the SWIR bands for deriving the water-leaving radiances at the UV (340 nm) and visible wavelengths. Simulations show that atmospheric correction using the SWIR bands can generally produce results comparable to atmospheric correction using the NIR bands. In particular, the water-leaving radiance at the UV band (340 nm) can also be derived accurately. The results from a sensitivity study for the required sensor noise equivalent reflectance, (NE Delta rho), [or the signal-to-noise ratio (SNR)] for the NIR and SWIR bands are provided and discussed.     

Ocean optics estimation for absorption,backscattering, and phase function parameters

We propose and test an inverse ocean optics procedure with numerically simulated data for the determination of inherent optical properties using in-water radiance measurements. If data are available at only one depth within a deep homogeneous water layer, then the single-scattering albedo and the single parameter that characterizes the Henyey-Greenstein phase function can be estimated. If data are available at two depths, then these two parameters can be determined along with the optical thickness so that the absorption and scattering coefficients, and also the backscattering coefficient, can be estimated. With a knowledge of these parameters, the albedo and Lambertian fraction of reflected radiance of the bottom can be determined if measurements are made close to the bottom. A simplified method for determining the optical properties of the water also is developed for only three irradiance-type measurements if the radiance is approximately in the asymptotic regime.     

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.     

Effects of ocean surface reflectance variation with solar elevation on normalized water-leaving radiance

Effects of the ocean surface reflection for solar irradiance on the normalized water-leaving radiance in the visible wavelengths are evaluated and discussed for various conditions of the atmosphere, solar-zenith angles, and wind speeds. The surface reflection effects on water-leaving radiance are simply due to the fact that the radiance that is backscattered out of the water is directly proportional to the downward solar irradiance just beneath the ocean surface. The larger the solar-zenith angle, the less the downward solar irradiance just beneath the ocean surface (i.e., more photons are reflected by the ocean surface), leading to a reduced value of the radiance that is backscattered out of the ocean. For cases of large solar-zenith angles, the effects of surface irradiance reflection need to be accounted for in both the satellite-derived and in situ measured water-leaving radiances.     

Influence of the angular shape of the volume-scattering function and multiple scattering on remote sensing reflectance

Scattering phase functions derived from measured (volume-scattering meter, VSM) volume-scattering functions (VSFs) from Crimean coastal waters were found to have systematic differences in angular structure from Fournier-Forand (FF) functions with equivalent backscattering ratios. Hydrolight simulations demonstrated that differences in the angular structure of the VSF could result in variations in modeled subsurface radiance reflectances of up to +/-20%. Furthermore, differences between VSM and FF simulated reflectances were found to be nonlinear as a function of scattering and could not be explained with the single-scattering approximation. Additional radiance transfer modeling demonstrated that the contribution of multiple scattering to radiance reflectance increased exponentially from a minimum of 16% for pure water to a maximum of approximately 94% for turbid waters. Monte Carlo simulations demonstrated that multiple forward-scattering events were the dominant contributors to the generation of radiance reflectance signals for turbid waters and that angular structures in the shape of the VSF at forward angles could have a significant influence in determining reflectance signals for turbid waters.     

Atmospheric correction of ocean color sensors: analysis of the effects of residual instrument polarization sensitivity

We provide an analysis of the influence of instrument polarization sensitivity on the radiance measured by spaceborne ocean color sensors. Simulated examples demonstrate the influence of polarization sensitivity on the retrieval of the water-leaving reflectance rho(w). A simple method for partially correcting for polarization sensitivity-replacing the linear polarization properties of the top-of-atmosphere reflectance with those from a Rayleigh-scattering atmosphere-is provided and its efficacy is evaluated. It is shown that this scheme improves rho(w) retrievals as long as the polarization sensitivity of the instrument does not vary strongly from band to band. Of course, a complete polarization-sensitivity characterization of the ocean color sensor is required to implement the correction.