Chlorophyll biomass in the global oceans: airborne lidar retrieval using fluorescence of both chlorophyll and chromophoric dissolved organic matter

For three decades airborne laser-induced fluorescence has demonstrated value for chlorophyll biomass retrieval in wide-area oceanic field experiments, satellite validation, and algorithm development. A new chlorophyll biomass retrieval theory is developed using laser-induced and water Raman normalized fluorescence of both (a) chlorophyll and (b) chromophoric dissolved organic matter (CDOM). This airborne lidar retrieval theory is then independently confirmed by chlorophyll biomass obtained from concurrent (1) ship-cruise retrievals, (2) satellite inherent optical property (IOP) biomass retrievals, and (3) satellite standard band-ratio chlorophyll biomass retrievals. The new airborne lidar chlorophyll and CDOM fluorescence-based chlorophyll biomass retrieval is found to be more robust than prior lidar methods that used chlorophyll fluorescence only. Future research is recommended to further explain the underlying influence of CDOM on chlorophyll production.     

Oceanic inherent optical properties: proposed single laser lidar and retrieval theory

It is suggested that an economical airborne lidar having a single laser can retrieve the three principal inherent optical properties of the ocean. Only three time-resolved backscattering receiver channels are required: (i) elastic (on-wavelength), (ii) inelastic (water Raman), and (iii) inelastic [chromophoric dissolved organic matter (CDOM) fluorescence channel to remove the CDOM fluorescence interference from the Raman channel].     

Validation of satellite-retrieved oceanic inherent optical properties: proposed two-color elastic backscatter lidar and retrieval theory

Recent radiative transfer models show that: (1) regardless of elastic lidar receiver field of view (FOV), at vanishing lidar depth the lidar-derived attenuation coefficient klidar --> a, where a is the total absorption coefficient per meter of depth; and (2) for a wide FOV as the lidar sensing depth approaches some large value (depending on water type), klidar --> Kd, where Kd is the diffuse attenuation for downwelling irradiance. As a result, it is shown that a time-resolved, dual-wavelength-laser, elastic-backscattering lidar can retrieve the three principal oceanic optical properties: (1) the absorption coefficient of phytoplankton aph, (2) the absorption coefficient of chromophoric dissolved organic matter (CDOM) aCDOM, and (3) the nonwater total constituent backscattering coefficient bbt. The lidar-retrieved aph, aCDOM, and bbt inherent optical properties can be used to validate corresponding satellite-derived products such as those from terra moderate-resolution imaging spectroradiometer (MODIS), Aqua MODIS, Sea-viewing Wide Field-of-view Sensor, (SeaWiFS), and other ocean color sensors.     

Spectral parameters of inherent optical property models: method for satellite retrieval by matrix inversion of an oceanic radiance model

Inherent optical property (IOP) spectral models for the phytoplankton absorption coefficient, chromophoric dissolved organic matter (CDOM) absorption coefficient, and total constituent backscattering (TCB) coefficient are linear in the reference wavelength IOP and nonlinear in the spectral parameters. For example, the CDOM absorption coefficient IOP a(CDOM)(lambda(i)) = a(CDOM)(lambda(ref))exp[-S(lambda(i)- lambda(ref))] is linear in a(CDOM)(lambda(ref)) and nonlinear in S. Upon linearization by Taylor's series expansion, it is shown that spectral model parameters, such as S, can be concurrently accommodated within the same conventional linear matrix formalism used to retrieve the reference wavelength IOP's. Iteration is used to adjust for errors caused by truncation of the Taylor's series expansion. Employing an iterative linear matrix inversion of a water-leaving radiance model, computer simulations using synthetic data suggest that (a) no instabilities or singularities are introduced by the linearization and subsequent matrix inversion procedures, (b) convergence to the correct value can be expected only if starting values for a model parameter are within certain specific ranges, (c) accurate retrievals of the CDOM slope S (or the phytoplankton Gaussian width g) are generally reached in 3-20 iterations, (d) iterative retrieval of the exponent n of the TCB wavelength ratio spectral model is not recommended because the starting values must be within approximately +/-5% of the correct value to achieve accurate convergence, and (e) concurrent retrieval of S and g (simultaneously with the phytoplankton, CDOM, and TCB coefficient IOP's) can be accomplished in a 5 x 5 iterative matrix inversion if the starting values for S and g are carefully chosen to be slightly higher than the expected final retrieved values.     

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.     

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).     

Uncertainties associated to measurements of inherent optical properties in natural waters

Monte Carlo simulations are used to explain and quantify the errors in inherent optical properties (IOPs) (absorption and attenuation coefficients) measured using the WET Labs AC-9 submarine spectrophotometer, and to assess correction algorithms. Simulated samples with a wide range of IOPs encountered in natural waters are examined. The relative errors on the measured absorption coefficient are in general lower than 25%, but reach up to 100% in highly scattering waters. Relative errors on attenuation and scattering coefficients are more stable, with an underestimation mainly driven by the volume scattering function. The errors in attenuation and scattering spectral shapes are small.     

Estimating aerosol optical properties over the oceans with the multiangle imaging spectroadiometer: some preliminary studies

The multiangle imaging spectroradiometer (MISR) scheduled to be flown on the first platform of the Earth Observing System in 1998 provides an opportunity to enhance considerably the accuracy with which aerosol properties over the ocean can be retrieved through passive sensing from Earth orbit. As opposed to most radiometers in space that scan the earth in a plane normal to the subsatellite path, the MISR will scan the earth simultaneously in nine planes and thus provide the radiance exiting the atmosphere over a given pixel in nine different directions and at four wavelengths. We examine the problem of extracting the aerosol optical thickness (τ(a)) over the oceans from MISR data, and we produce two algorithms, a single-band algorithm and a spectral or two-band algorithm, for deriving τ(a). The algorithms are based on the use of realistic aerosol models as candidates on which to base an estimation of the aerosol optical properties. They take into account all orders of multiple scattering. Simulations suggest that for nonabsorbing or mildly absorbing aerosol (single-scattering albedo ω(a) > 0.90) the error in the recovered τ(a) is ? 10%, as long as the candidate models adequately cover the size refractive index distribution range of the expected aerosols. In the special case of a strongly absorbing aerosol (ω(a) ? 0.75), the error in τ(a) becomes large; however, the combination ω(a)τ(a) (the scattering optical thickness) can still be recovered with an error of ? 20%, although it is always underestimated. The reason for this decrease in accuracy is that multiple-scattering effects are a strong function of ω(a). A simple extension of the two-band algorithm permits the retrieval of the aerosol scattering phase function with surprising accuracy.     

Multiparameter retrieval of water optical properties from above-water remote-sensing reflectance using the simulated annealing algorithm

Water-leaving radiance, measured just above the ocean surface, contains important information about near-surface or subsurface processes that occur on or below the deep ocean and coastal water. As such, retrieving seawater inherent optical properties (IOPs) is an important step to determining water type, subsurface light field, turbidity, pigment concentration, and sediment loading. However, the retrieval (or inversion) of seawater IOPs from just above water radiance measurements is a multiparameter nonlinear problem that is difficult to solve by conventional optimization methods. The applicability of the simulated annealing algorithm (SA) is explored as a nonlinear global optimizer to solve this multiparameter retrieval problem. The SA algorithm is combined with widely known semianalytical relations for seawater's IOPs to parameter invert these properties from simulated and measured water-leaving reflectance spectra. Furthermore, given the versatility of the SA algorithm, the scheme is extended to retrieve water depth from input reflectance data. Extensive tests and comparisons with in situ and simulated data sets compiled by the International Ocean-Color Coordinating Group are presented. Field data include reflectance spectra acquired with a handheld GER 1500 spectroradiometer and absorption measurements, performed with the AC-9 instrument on waters around Singapore's nearby islands.     

Parameterization of the inherent optical properties of Murchison Bay, Lake Victoria

Lake Victoria, Africa's largest freshwater lake, suffers greatly from negative changes in biomass of species of fish and also from severe eutrophication. The continuing deterioration of Lake Victoria's ecological functions has great long-term consequences for the ecosystem benefits it provides to the countries bordering its shores. However, knowledge about temporal and spatial variations of optical properties and how they relate to lake constituents is important for a number of reasons such as remote sensing, modeling of underwater light fields, and long-term monitoring of lake waters. Based on statistical analysis of data from optical measurements taken during half a year of weekly cruises in Murchison Bay, Lake Victoria, we present a three-component model for the absorption and a two-component model for the scattering of light in the UV and the visible regions of the solar spectrum along with tests of their ranges of validity. The three-component input to the model for absorption is the chlorophyll-a (Chl-a), total suspended materials concentrations, and yellow substance absorption, while the two-component input to the model for scattering is the Chl-a concentration and total suspended materials.     

Comparison of the ocean inherent optical properties obtained from measurements and inverse modeling

A model developed recently by Loisel and Stramski [Appl. Opt. 39, 3001-3011 (2000)] for estimating the spectral absorption a(lambda), scattering b(lambda), and backscattering b(b)(lambda) coefficients in the upper ocean from the irradiance reflectance just beneath the sea surface R(lambda, z = 0(-)) and the diffuse attenuation of downwelling irradiance within the surface layer ?K(d)(lambda)?(1) is compared with measurements. Field data for this comparison were collected in different areas including off-shore and near-shore waters off southern California and around Europe. The a(lambda) and b(b)(lambda) values predicted by the model in the blue-green spectral region show generally good agreement with measurements that covered a broad range of conditions from clear oligotrophic waters to turbid coastal waters affected by river discharge. The agreement is still good if the model estimates of a(lambda) and b(b)(lambda) are based on R(lambda, z = 0(-)) used as the only input to the model available from measurements [as opposed to both R(lambda, z = 0(-)) and ?K(d)(lambda)?(1) being measured]. This particular mode of operation of the model is relevant to ocean-color remote-sensing applications. In contrast to a(lambda) and b(b)(lambda) the comparison between the modeled and the measured b(lambda) shows large discrepancies. These discrepancies are most likely attributable to significant variations in the scattering phase function of suspended particulate matter, which were not included in the development of the model.     

Interference-based optical image encryption using three-dimensional phase retrieval

In recent years, optical image encryption has attracted more and more attention in information security due to its unique advantages, such as parallel processing and multiple-parameter characteristics. In this paper, we propose a new method using three-dimensional (3D) processing strategy for interference-based optical image encryption. The plaintext is considered as a series of particles distributed in 3D space, and any one sectional extraction cannot render information about the plaintext during image decryption. In addition, the silhouette problem in the conventional interference-based optical encryption method is effectively suppressed, and the proposed optical cryptosystem can achieve higher security compared with the previous work. A numerical experiment is conducted to demonstrate the feasibility and effectiveness of the proposed method.     

Uncertainties of inherent optical properties obtained from semianalytical inversions of ocean color

We present a method to quantify the uncertainties in the in-water constituent absorption and backscattering coefficients obtained from an inversion of remotely sensed reflectance (rrs). We first find a set of positive inversion solutions within a given uncertainty range around the values of the inverted rrs. The uncertainties of the solutions are then computed based on the statistics of these solutions. We demonstrate the uncertainty calculation algorithm using a specific semianalytic inversion model applied to both a field and a simulated data set. When the associated uncertainties are taken into account, the inverted parameters are generally within the uncertainties of the measured (or simulated) parameters, highlighting the success of the inversion and the method to obtain uncertainties. The specific inversion we use, however, fails to retrieve two spectral parameters within a usable range. The method presented is general and can be applied to all existing semianalytical inversion algorithms.     

Insight into the inherent randomness of concrete properties using the stochastic micromechanics

The concrete properties inherently fluctuate even using the same manufacturing process. A Legendre polynomial based micromechanical framework is proposed to investigate the inherent randomness of the concrete’s elastic behavior. The three-phase composite model is employed to represent the concrete material at microscale level. The volume fractions of different constituents are reached using a simplified analytical approach. Predictions with and without particle interactions for the concrete properties are obtained through the two-level homogenization process. By describing the microstructures with high-dimensional random vector, the stochastic micromechanical framework is obtained based on the presented three-phase model to incorporate the concrete’s inherent randomness. The unbiased probability density functions (PDFs) of the properties are attained using efficient simulation framework consisting of the Legendre polynomial approximations, Monte Carlo simulations and the linear transformations. Numerical examples indicate that the proposed framework is able to describe the probabilistic characters of concrete properties from microscale level and obtain the material’s unbiased PDFs with high efficiency. Finally, the statistical effects of ITZ are discussed on the concrete’ s macroscopic probabilistic behaviors.     

Sensitivity of surface reflectance retrieval to uncertainties in aerosol optical properties

We formulate a procedure to investigate the sensitivity of surface reflectances retrieved from satellite sensor data to uncertainties in aerosol optical properties. Aerosol optical characteristics encompassed in the study include the aerosol optical depth, the Junge parameter (i.e., spectral dependence), and the imaginary part of the refractive index (i.e., aerosol absorption). The study includes both clear and hazy atmospheric conditions, wavelengths of 0.550 and 0.870 μm, three solar zenith angles, and five viewing geometries. Key results are presented graphically in terms of accuracy requirements on the aerosol property under consideration for a 5% uncertainty in predicted surface reflectance.     

Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters

For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.     

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.     

Modeling the inherent optical properties of the ocean based on the detailed composition of the planktonic community

We describe an approach to modeling the ocean's inherent optical properties (IOPs) that permits extensive analyses of IOPs as the detailed composition of suspended particulate matter is varied in a controlled manner. Example simulations of the IOP model, which includes 18 planktonic components covering a size range from submicrometer viruses and heterotrophic bacteria to microplanktonic species of 30-mum cell diameter, are discussed. Input data to the model include the spectral optical cross sections on a per particle basis and the particle-number concentration for each individual component. This approach represents a significant departure from traditional IOP and bio-optical models in which the composition of seawater is described in terms of a few components only or chlorophyll concentration alone. The simulations illustrate how the separation and understanding of the effects of various types of particle present within a water body can be achieved. In an example simulation representing an oligotrophic water body with a chlorophyll a concentration of 0.18 mg m(-3), the planktonic microorganisms altogether are the dominant particulate component in the process of light absorption, but their relative contribution to light scattering is smaller than that of nonliving particles. A series of simulations of water bodies with the same chlorophyll a concentration but dominated by different phytoplankton species shows that composition of the planktonic community is an important source of optical variability in the ocean.     

Semianalytical model for the derivation of ocean color inherent optical properties: description, implementation, and performance assessment

A semianalytical approach to the problem of determining inherent optical properties from satellite and in situ ocean color data is presented. The model uses empirically derived spectral slopes between neighboring wavebands in combination with radiative transfer modeling to determine the spectral absorption (alpha) and backscatter (b(b)); these values are then further decomposed into absorption due to phytoplankton, detrital, and colored dissolved organic matter components. When compared with over 400 in situ data points the model makes good retrievals of the total absorption and backscatter across the entire spectrum, with regression slopes close to unity, little or no bias, high percentage of variance explained, and low rms errors.     

Apparent and inherent optical properties of turbid estuarine waters: measurements, empirical quantification relationships, and modeling

Spectral measurements of remote-sensing reflectance (Rrs) and absorption coefficients carried out in three European estuaries (Gironde and Loire in France, Tamar in the UK) are presented and analyzed. Typical Rrs and absorption spectra are compared with typical values measured in coastal waters. The respective contributions of the water constituents, i.e., suspended sediments, colored dissolved organic matter, and phytoplankton (characterized by chlorophyll-a), are determined. The Rrs spectra are then reproduced with an optical model from the measured absorption coefficients and fitted backscattering coefficients. From Rrs ratios, empirical quantification relationships are established, reproduced, and explained from theoretical calculations. These quantification relationships were established from numerous field measurements and a reflectance model integrating the mean values of the water constituents' inherent optical properties. The model's sensitivity to the biogeochemical constituents and to their nature and composition is assessed.