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).     

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.     

Estimation of the inherent optical properties of natural waters from the irradiance attenuation coefficient and reflectance in the presence of Raman scattering

By means of radiative transfer simulations we developed a model for estimating the absorption a, the scattering b, and the backscattering b(b) coefficients in the upper ocean from irradiance reflectance just beneath the sea surface, R(0-), and the average attenuation coefficient for downwelling irradiance, 1, between the surface and the first attenuation depth. The model accounts for Raman scattering by water, and it does not require any assumption about the spectral shapes of a, b, and b(b). The best estimations are obtained for a and b(b) in the blue and green spectral regions, where errors of a few percent to <10% are expected over a broad range of chlorophyll concentration in water. The model is useful for satellite ocean color applications because the model input, R(0-) and 1, can be retrieved from remote sensing and the model output, a and b(b), is the major determinant of remote-sensing reflectance.     

Toward closure of upwelling radiance in coastal waters

We present three methods for deriving water-leaving radiance L(w)(lambda) and remote-sensing reflectance using a hyperspectral tethered spectral radiometer buoy (HyperTSRB), profiled spectroradiometers, and Hydrolight simulations. Average agreement for 53 comparisons between HyperTSRB and spectroradiometric determinations of L(w)(lambda) was 26%, 13%, and 17% at blue, green, and red wavelengths, respectively. Comparisons of HyperTSRB (and spectroradiometric) L(w)(lambda) with Hydrolight simulations yielded percent differences of 17% (18%), 17% (18%), and 13% (20%) for blue, green, and red wavelengths, respectively. The differences can be accounted for by uncertainties in model assumptions and model input data (chlorophyll fluorescence quantum efficiency and the spectral chlorophyll-specific absorption coefficient for the red wavelengths, and scattering corrections for input ac-9 absorption data and volume scattering function measurements for blue wavelengths) as well as radiance measurement inaccuracies [largely differences in the depth of the L(u)(lambda, z) sensor on the HyperTSRB].     

Effect of suspended particulate and dissolved organic matter on remote sensing of coastal and riverine waters

We use remote sensing reflectance (RSR) together with the inherent optical properties of suspended particulates to determine the backscattering ratio b(b)/b for coastal waters. We examine the wavelength dependence of b(b)(lambda) and f(lambda)/Q(lambda) and establish the conditions when C(lambda) in RSR(lambda) approximately or = C(lambda)b(b)(lambda)/a(lambda) can be treated as a constant. We found that for case 2 waters, RSR was insensitive to the natural fluctuations in particle-size distributions. The cross-sectional area of the suspended particulate per unit volume, x(g), showed an excellent correlation with the volume scattering coefficient.     

Estimation of the remote-sensing reflectance from above-surface measurements

The remote-sensing reflectance R(rs) is not directly measurable, and various methodologies have been employed in its estimation. I review the radiative transfer foundations of several commonly used methods for estimating R(rs), and errors associated with estimating R(rs) by removal of surface-reflected sky radiance are evaluated using the Hydrolight radiative transfer numerical model. The dependence of the sea surface reflectance factor rho, which is not an inherent optical property of the surface, on sky conditions, wind speed, solar zenith angle, and viewing geometry is examined. If rho is not estimated accurately, significant errors can occur in the estimated R(rs) for near-zenith Sun positions and for high wind speeds, both of which can give considerable Sun glitter effects. The numerical simulations suggest that a viewing direction of 40 deg from the nadir and 135 deg from the Sun is a reasonable compromise among conflicting requirements. For this viewing direction, a value of rho approximately 0.028 is acceptable only for wind speeds less than 5 m s(-1). For higher wind speeds, curves are presented for the determination of rho as a function of solar zenith angle and wind speed. If the sky is overcast, a value of rho approximately 0.028 is used at all wind speeds.     

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.     

Measured and modeled radiometric quantities in coastal waters: toward a closure

Accurate radiative transfer modeling in the coupled atmosphere-sea system is increasing in importance for the development of advanced remote-sensing applications. Aiming to quantify the uncertainties in the modeling of coastal water radiometric quantities, we performed a closure experiment to intercompare theoretical and experimental data as a function of wavelength lambda and water depth z. Specifically, the study focused on above-water downward irradiance E(d)(lambda, 0+) and in-water spectral profiles of upward nadir radiance L(u)(lambda, z), upward irradiance E(u)(lambda, z), downward irradiance E(d)(lambda, z), the E(u)(lambda, z)/L(u)(lambda, z) ratio (the nadir Q factor), and the E(u)(lambda, z)/E(d)(lambda, z) ratio (the irradiance reflectance). The theoretical data were produced with the finite-element method radiative transfer code ingesting in situ atmospheric and marine inherent optical properties. The experimental data were taken from a comprehensive coastal shallow-water data set collected in the northern Adriatic Sea. Under various measurement conditions, differences between theoretical and experimental data for the above-water E(d)(lambda, 0+) and subsurface E(d)(lambda, 0-) as well as for the in-water profiles of the nadir Q factor were generally less than 15%. In contrast, the in-water profiles of L(u)(lambda, z), E(d)(lambda, z), E(u)(lambda, z) and of the irradiance reflectance exhibited larger differences [to approximately 60% for L(u)(lambda, z) and E(u)(lambda, z), 30% for E(d)(lambda, z), and 50% for the irradiance reflectance]. These differences showed a high sensitivity to experimental uncertainties in a few input quantities used for the simulations: the seawater absorption coefficient; the hydrosol phase function backscattering probability; and, mainly for clear water, the bottom reflectance.     

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.     

Model for the interpretation of hyperspectral remote-sensing reflectance

Remote-sensing reflectance is easier to interpret for the open ocean than for coastal regions because the optical signals are highly coupled to the phytoplankton (e.g., chlorophyll) concentrations. For estuarine or coastal waters, variable terrigenous colored dissolved organic matter (CDOM), suspended sediments, and bottom reflectance, all factors that do not covary with the pigment concentration, confound data interpretation. In this research, remote-sensing reflectance models are suggested for coastal waters, to which contributions that are due to bottom reflectance, CDOM fluorescence, and water Raman scattering are included. Through the use of two parameters to model the combination of the backscattering coefficient and the Q factor, excellent agreement was achieved between the measured and modeled remote-sensing reflectance for waters from the West Florida Shelf to the Mississippi River plume. These waters cover a range of chlorophyll of 0.2-40 mg/m(3) and gelbstoff absorption at 440 nm from 0.02-0.4 m(-1). Data with a spectral resolution of 10 nm or better, which is consistent with that provided by the airborne visible and infrared imaging spectrometer (AVIRIS) and spacecraft spectrometers, were used in the model evaluation.     

In situ determination of the remotely sensed reflectance and the absorption coefficient: closure and inversion

We tested closure between in situ radiometric and absorption coefficient measurements by using a nearly backscattering-independent remote-sensing reflectance model that employs the remote-sensing reflectance at three wavelengths. We show that only a small error is introduced into the closure model when the proper functional relationships of f/Q and the backscattering is taken to be a constant when using the sea-viewing wide field-of-view sensor wavelengths 443, 490, and 555 nm. A method of inverting the model to obtain the absorption coefficient by use of simple linear spectral relationships of the absorption coefficient is provided. The results of the model show that the independent measurements of reflectance and absorption obtain closure with a high degree of accuracy.     

Effect of Aging on the Spectral Radiative Properties of Plastic Film-Covered Greenhouse under Arid Conditions

Plastic films are widely used to cover greenhouses in arid regions. Unlike predicting the total radiative properties of films, predicting the deterioration behavior of the spectral radiative properties is quite difficult during the service life of the films. These properties should be of great interest for crop morphogenesis studies. This study was to investigate the degradation behavior of spectral transmittance, \( \tau_{\lambda } \), and reflectance, \( \rho_{\lambda } \) (in the solar spectrum range), of a 200 µm thick, LDPE film-covered greenhouse model that was exposed for 1 year to an arid climate. Every 30 days, \( \tau_{\lambda } \) and \( \rho_{\lambda } \) were measured for six samples taken from the six surfaces of the greenhouse cover and averaged to obtain the cover properties. Based on the collected data, nonlinear correlations (each as a function of the wavelength, λ, and the exposure time, t) were obtained to predict \( \tau_{\lambda } \) and \( \rho_{\lambda } \) at any time during the service life of the cover under such climatic conditions. Results showed that 1 year exposure drastically reduced the spectral and total transmittance of the cover film to global and PAR solar radiation by about 32 % and increased the spectral and total reflectance by about 19 % compared to new film. Degradation of the radiative properties of the film did not affect the light quality or the transmission ratios of light into the greenhouse. The transmitted PAR was reduced from 115 W·m^?2 to 27 W·m^?2 after 1 year exposure.     

Diffuse reflectance spectroscopy of particulate systems: a comparative study of discrete models

A comparative study of statistical particle model theory of diffuse reflectance has been made. Theories have been applied to six particulate samples having different optical characteristics and average particle sizes that vary from 42 to 106 mum. We made an overall assessment of each theoretical model by determining the CIELAB color difference using experimentally measured and theoretically predicted diffuse reflectance spectra in the visible spectral range. We discuss the performance ratings of the models of other researchers and discovered numerous typographical errors in Fresnel reflection coefficient expressions. We provide the correct versions for these expressions.     

Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful alga, Karenia brevis

We applied two numerical methods to in situ hyperspectral measurements of remote sensing reflectance Rrs to assess the feasibility of remote detection and monitoring of the toxic dinoflagellate, Karenia brevis, which has been shown to exhibit unique absorption properties. First, an existing quasi-analytical algorithm was used to invert remote sensing reflectance spectra, Rrs(lambda), to derive phytoplankton absorption spectra, a(phi)Rrs(lambda). Second, the fourth derivatives of the a(phi)Rrs(lambda) spectra were compared to the fourth derivative of a reference K. brevis absorption spectrum by means of a similarity index (SI) analysis. Comparison of reflectance-derived a(phi) with filter pad measured a(phi) found them to agree well (R2=0.891; average percentage difference, 22.8%). A strong correlation (R2=0.743) between surface cell concentration and the SI was observed, showing the potential utility of SI magnitude as an indicator of bloom strength. A sensitivity analysis conducted to investigate the effects of varying levels of cell concentrations and colored dissolved organic matter (CDOM) on the efficacy of the quasi-analytical algorithm and SI found that a(phi)Rrs(lambda) could not be derived for very low cell concentrations and that, although it is possible to derive a(phi)Rrs(lambda) in the presence of high CDOM concentrations, CDOM levels influence the a(phi)Rrs(lambda) amplitude and shape. Results suggest that detection and mapping of K. brevis blooms based on hyperspectral measurements of Rrs are feasible.     

Effects of molecular and particle scatterings on the model parameter for remote-sensing reflectance

For optically deep waters, remote-sensing reflectance (r(rs)) is traditionally expressed as the ratio of the backscattering coefficient (b(b)) to the sum of absorption and backscattering coefficients (a + b(b)) that multiples a model parameter (g, or the so-called f'/Q). Parameter g is further expressed as a function of b(b)/(a + b(b)) (or b(b)/a) to account for its variation that is due to multiple scattering. With such an approach, the same g value will be derived for different a and b(b) values that provide the same ratio. Because g is partially a measure of the angular distribution of upwelling light, and the angular distribution from molecular scattering is quite different from that of particle scattering; g values are expected to vary with different scattering distributions even if the b(b)/a ratios are the same. In this study, after numerically demonstrating the effects of molecular and particle scatterings on the values of g, an innovative r(rs) model is developed. This new model expresses r(rs) in two separate terms: one governed by the phase function of molecular scattering and one governed by the phase function of particle scattering, with a model parameter introduced for each term. In this way the phase function effects from molecular and particle scatterings are explicitly separated and accounted for. This new model provides an analytical tool to understand and quantify the phase-function effects on r(rs), and a platform to calculate r(rs) spectrum quickly and accurately that is required for remote-sensing applications.     

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.     

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).     

Spectral reflectance and responsivity of Ge- and InGaAs-photodiodes in the near-infrared: measurement and model

The spectral reflectance and responsivity of Ge- and InGaAs-photodiodes at (nearly) normal and oblique incidence (45 degrees) were investigated. The derived data allow a calculation of the photodiodes responsivities for any incident angle. The measurements were carried out with s- and p-polarized radiation in the wavelength range from 1260 to 1640 nm. The spectral reflectance of the photodiodes was modeled by using the matrix approach developed for thin-film optical assemblies. The comparison between the calculated and measured reflectance shows a difference of less than 2% for the Ge-photodiode. For the InGaAs-photodiode, the differences between measured and calculated reflectance are larger, i.e., up to 6% for wavelengths between 1380 and 1580 nm. Despite the larger differences between calculated and measured spectral reflectances for the InGaAs-photodiode, the difference between calculated and measured spectral responsivity is even smaller for the InGaAs-photodiode than for the Ge-photodiode, i.e., < or =1.2% for the InGaAs-photodiode compared to < or =2.2% for the Ge-photodiode. This is because the difference in responsivity is strongly correlated to the absolute spectral reflectance level, which is much lower for the InGaAs-photodiode. This observation also shows the importance of having small reflectances, i.e., appropriate antireflection coatings for the photodiodes. The relative standard uncertainty associated with the modeled spectral responsivity is about 2.2% for the Ge-photodiode and about 1.2% for the InGaAs-photodiode for any incident angle over the whole spectral range measured. The data obtained for the photodiodes allow the calculation of the spectral responsivity of Ge- and InGaAs-trap detectors and the comparison with experimental results.     

Modeling the optical properties of mineral particles suspended in seawater and their influence on ocean reflectance and chlorophyll estimation from remote sensing algorithms

The optical properties of mineral particles suspended in seawater were calculated from the Mie scattering theory for different size distributions and complex refractive indices of the particles. The ratio of the spectral backscattering coefficient to the sum of the spectral absorption and backscattering coefficients of seawater, b(b)(lambda)/[a(lambda) + b(b)(lambda)], was analyzed as a proxy for ocean reflectance for varying properties and concentrations of mineral particles. Given the plausible range of variability in the particle size distribution and the refractive index, the general parameterizations of the absorption and scattering properties of mineral particles and their effects on ocean reflectance in terms of particle mass concentration alone are inadequate. The variations in the particle size distribution and the refractive index must be taken into account. The errors in chlorophyll estimation obtained from the remote sensing algorithms that are due to the presence of mineral particles can be very large. For example, when the mineral concentration is 1 g m(-3) and the chlorophyll a concentration is low (0.05 mg m(-3)), current global algorithms based on a blue-to-green reflectance ratio can produce a chlorophyll overestimation ranging from approximately 50% to as much as 20-fold.     

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.