... We used the set of 10 calculations to estimate the residual statistical noise in the calculations. The pure water optical properties were taken from Pope and Fry [17] and Morel [18]. Figure 2 shows the optical properties of the water constituents assumed in the base model. ...
... LwX represents one of three water leaving radiance products that are produced with the 3 upwelling radiance measurements. Pure water values (a w and b w ) were from [17,18]. is given by: ...
... The important required IOP's were absorption and scattering (a, b respectively), absorption and scattering of pure water (a w , b w respectively), and the phase function of the water and particles. The water a w , b w , and water phase function are relatively well known [17,18]. Our model runs used a single Chl value to determine a and b through the Morel and Maritorena model [21]. ...
A 3-D instrument self-shading correction has been developed for the MOBY upwelling radiance measurements. This correction was tested using the 23 year time series of MOBY measurements, at the Lanai, Hawaii site. The correction is small (less than 2%) except when the sun and collectors are aligned within 20° azimuth on opposite sides of the main MOBY structure. Estimates of the correction uncertainty were made with a Monte-Carlo method and the variation of the model input parameters at this site. The correction uncertainty was generally less than 1%, but increased to 30% of the correction in the strongest shadow region.
... The sigma correction relating to the incomplete recovery of backscattered light in highly attenuating waters was made in accordance with the User's Manual [31], with additional data necessary for this correction being obtained from laboratory measurements of the attenuation coefficient, described below, using a Viper (TriOS) device. To obtain the backscattering coefficient due only to suspended particles b bp (λ), theoretical values of this coefficient for pure water b bw (λ) were subtracted in accordance with Reference [32]. ...
... In our calculations, we used a compilation of values according to [40][41][42], as well as those from [32] (corrected for the water salinity (ca. 7) typical of the region studied); -It was assumed that for both the organic and inorganic fractions of suspended particles (POM and PIM), typical/average values of the mass-specific optical coefficients could be taken into account, i.e., the coefficients respectively denoted by ap* POM , ap* PIM , bbp* POM or bbp* PIM (definitions are given later). ...
... -Literature values of absorption and backscattering coefficients by pure seawater, a w (λ) and b bw (λ). In our calculations, we used a compilation of values according to [40][41][42], as well as those from [32] (corrected for the water salinity (ca. 7) typical of the region studied); -It was assumed that for both the organic and inorganic fractions of suspended particles (POM and PIM), typical/average values of the mass-specific optical coefficients could be taken into account, i.e., the coefficients respectively denoted by a p * POM , a p * PIM , b bp * POM or b bp * PIM (definitions are given later). ...
The paper presents the modelling results of selected characteristics of water-leaving light in an optically complex nearshore marine environment. The modelled quantities include the spectra of the remote-sensing reflectance Rrs(λ) and the hue angle α, which quantitatively describes the colour of water visible to the unaided human eye. Based on the latter value, it is also possible to match water-leaving light spectra to classes on the traditional Forel-Ule water colour scale. We applied a simple model that assumes that seawater is made up of chemically pure water and three types of additional optically significant components: particulate organic matter (POM) (which includes living phytoplankton), particulate inorganic matter (PIM), and chromophoric dissolved organic matter (CDOM). We also utilised the specific inherent optical properties (SIOPs) of these components, determined from measurements made at a nearshore location on the Gulf of Gdańsk. To a first approximation, the simple model assumes that the Rrs spectrum can be described by a simple function of the ratio of the light backscattering coefficient to the sum of the light absorption and backscattering coefficients (u = bb/(a + bb)). The model calculations illustrate the complexity of possible relationships between the seawater composition and the optical characteristics of an environment in which the concentrations of individual optically significant components may be mutually uncorrelated. The calculations permit a quantitative interpretation of the Forel-Ule scale. The following parameters were determined for the several classes on this scale: typical spectral shapes of the u ratio, possible ranges of the total light absorption coefficient in the blue band (a(440)), as well as upper limits for concentrations of total and organic and inorganic fractions of suspended particles (SPM, POM and PIM concentrations). The paper gives examples of practical algorithms that, based on a given Rrs spectrum or some of its features, and using lookup tables containing the modelling results, enable to estimate the approximate composition of seawater.
... where a, b and c are absorption coefficient, scattering coefficient and beam attenuation coefficient respectively, a w is the absorption coefficient of pure seawater [34], A is the normalized spectral absorption values of phytoplankton pigments [34], a y is the absorption coefficient of yellow substance [35], b w is the scattering coefficient of pure water [36]; b p is the particulate scattering ( , ) ...
... Existing models [31,[34][35][36] were utilized to establish separate relationships between β f and Chl, as well as between c mf and Chl. By considering Chl as the pivot, the relationship between ...
Laser-induced fluorescence (LIF) technology has been widely applied in remote sensing of aquatic phytoplankton. However, due to the weak fluorescence signal induced by laser excitation and the significant attenuation of laser in water, profiling detection becomes challenging. Moreover, it remains difficult to simultaneously retrieve the attenuation coefficient ( K l i d a r m f ) and the fluorescence volume scattering function at 180° ( β f ) through a single fluorescence lidar. To address these issues, a novel all-fiber fluorescence oceanic lidar is proposed, characterized by: 1) obtaining subsurface fluorescence profiles using single-photon detection technology, and 2) introducing the Klett inversion method for fluorescence lidar to simultaneously retrieve K l i d a r m f and β f . According to theoretical analysis, the maximum relative error of β f for the chlorophyll concentration ranging from 0.01 mg/m ³ to 10 mg/m ³ within a water depth of 10 m is less than 20%, while the maximum relative error of K l i d a r m f is less than 10%. Finally, the shipborne single-photon fluorescence lidar was deployed on the experimental vessel for continuous experiments of over 9 hours at fixed stations in the offshore area, validating its profiling detection capability. These results demonstrate the potential of lidar in profiling detection of aquatic phytoplankton, providing support for studying the dynamic changes and environmental responses of subsurface phytoplankton.
... where bbw(λ) is the backscattering of seawater molecules according to Morel [42]. Next, we obtained (f/Q)i values for the four tested wavelengths, λi = 420, 488, 555 and 620 nm. ...
... Just as the absorption capacity, the backscattering properties of seawater also depend on SPM and SPMinorg. These relationships can be presented in the form of hyperbolic expressions (see Equations (39)- (42)). The statistical errors in the case of bbp as a function of two independent variables range from about 30% to about 50%, and they depend on the wavelength (see Tables 1 and 2). ...
Coastal waters are the richest parts of ocean ecosystems characterised by dynamic changes in water biology, physical and chemical features. Establishing local relationships between water constituents and optical properties in these areas will help to develop successful ocean colour algorithms allowing a thorough understanding of complex coastal waters and improving water quality monitoring. In this paper, the authors present the use of optical and biogeochemical measurements in complex aquatic environments and aim to create a semi-empirical model of remote-sensing reflectance (Rrs(λi)) for four wavelengths (λi= 420 nm, 488 nm, 555 nm, and 620 nm) based on multiparameter algorithms of absorption (a(λi)) and backscattering (bb(λi)) coefficients. The bio-optical properties of water were determined based on empirical data gathered from aboard the r/v Oceania from April 2007 to March 2010 in chosen areas of the southern Baltic (Polish coast). The analyses reveal that Rrs(λi) in the studied area can be described with satisfactory accuracy using a five-parameter model. Positive results with a statistical error magnitude of Rrs(λi) of less than 50% were achieved for all four applied wavelengths. Bio-optical algorithms proposed by the authors enable evaluating biogeochemical characteristics of coastal areas in a broader context of ecosystem assessment and contribute significantly to the development of Earth and environmental sciences.
... where the phase function is given by Morel et al. [29] as follows: ...
... The absorption coefficients of water were referred from Pope et al. [31], the density fluctuation scattering coefficients of water and its phase function were adopted from Morel [29] and Morel et al. [3] and the depolarization ratio of water was employed from Zhang et al. [32] as δ1 = 0.039. ...
The blue coloration model of a closed pond, Ao-ike Pond, Aomori Prefecture, Japan, was formulated in terms of radiance by applying a theory of observation devices proposed by Szirmay-Kalos (2008) and Hanaishi’s reverse ray tracing method. In this model, three potential contributions to the coloration were considered; irregular reflection at the Lambertian pond bottom, density fluctuation scattering by water, and Mie scattering by suspended solids. By utilizing model formulas for these mechanisms, some parameters were determined in order to duplicate the images of the pond surface without solar shading by tree leaves above the pond surface, in addition to the images with sunbeam trajectories by solar radiations passing through tree leaves, which are emitted from the water and visible on the surface. Simulating the pictures of the pond surface and the sun-beam-image analyses revealed that the blue colorations of Ao-ike Pond are mainly produced (1) by the density fluctuation scattering of water itself and the white Mie scattering by suspended solids and (2) by the red-light absorption by water in the optical paths before and after the two scatterings. Then, the density fluctuation scattering of water and the Mie scattering by suspended solids ex-hibited contributions of almost equal magnitude. The contribution of irregular reflections at the pond bottom was judged to be relatively small.
... where b bW is the backscattering due to seawater [65] and b bP is the backscattering due to particulate matter suspended in the water column. We measured light backscattering in the water column using a WET Labs ECO BB-9 instrument at wavelengths 412, 440, 488, 510, 532, 595,650, 676 and 715 nm. ...
... The corrected volume scattering coefficients comprise contributions from particles and water in the backward direction (θ = 117 • ). Particulate volume scattering (β P ) was obtained by subtracting the volume scattering of water [65]. Particulate backscattering coefficients, b bP (λ) with units of m −1 , were then determined as: ...
Coastal water quality degradation is a global challenge. Marine pollution due to suspended sediments and dissolved matter impacts water colour, biogeochemistry, benthic habitats and eventually human populations that depend on marine resources. In Sarawak (Malaysian Borneo), peatland-draining river discharges containing suspended sediments and dissolved organic carbon influence coastal water quality at multiple locations along the coast. Optical remote sensing is an effective tool to monitor coastal waters over large areas and across remote geographic locations. However, the lack of regional optical measurements and inversion models limits the use of remote sensing observations for water quality monitoring in Sarawak. To overcome this limitation, we have (1) compiled a regional spectral optical library for Sarawak coastal waters, (2) developed a new semi-analytical remote sensing model to estimate suspended sediment and dissolved organic carbon in coastal waters, and (3) demonstrated the application of our remote sensing inversion model on satellite data over Sarawak. Bio-optical data analysis revealed that there is a clear spatial variability in the inherent optical properties of particulate and dissolved matter in Sarawak. Our optical inversion model coupled with the Sarawak spectral optical library performed well in retrieving suspended sediment (bias = 3% and MAE = 5%) and dissolved organic carbon (bias = 3% and MAE = 8%) concentrations. Demonstration products using MODIS Aqua data clearly showed the influence of large rivers such as the Rajang and Lupar in discharging suspended sediments and dissolved organic carbon into coastal waters. The bio-optical parameterisation, optical model, and remote sensing inversion approach detailed here can now help improve monitoring and management of coastal water quality in Sarawak.
... The absorption [71,72] and backscattering [73] coefficients of pure water are given by a w (λ) and b b,w (λ), respectively. Colored dissolved organic matter (CDOM), phytoplankton (phy), and non-algal particles (NAPs) are optically active constituents and their absorption and backscattering properties are considered in Equations (4) and (5). ...
... The absorption [71,72] and backscattering [73] coefficients of pure water are given by ( ) and , ( ), respectively. Colored dissolved organic matter (CDOM), phytoplankton (phy), and non-algal particles (NAPs) are optically active constituents and their absorption and backscattering properties are considered in Eqs. 4 and 5. ...
A new era of spaceborne hyperspectral imaging has just begun with the recent availability of data from PRISMA (PRecursore IperSpettrale della Missione Applicativa) launched by the Italian space agency (ASI). There has been pre-launch optimism that the wealth of spectral information offered by PRISMA can contribute to a variety of aquatic science and management applications. Here, we examine the potential of PRISMA level 2D images in retrieving standard water quality parameters, including total suspended matter (TSM), chlorophyll-a (Chl-a), and colored dissolved organic matter (CDOM) in a turbid lake (Lake Trasimeno, Italy). We perform consistency analyses among the aquatic products (remote sensing reflectance (R rs) and constituents) derived from PRISMA and those from Sentinel-2. The consistency analyses are expanded to synthesized Sentinel-2 data as well. By spectral downsampling of the PRISMA images, we better isolate the impact of spectral resolution in retrieving the constituents. The retrieval of constituents from both PRISMA and Sentinel-2 images is built upon inverting the radiative transfer model implemented in the Water Color Simulator (WASI) processor. The inversion involves a parameter (g dd) to compensate for atmospheric and sun-glint artifacts. A strong agreement is indicated for the cross-sensor comparison of R rs products at different wavelengths (average R ≈ 0.87). However, the R rs of PRISMA at shorter wavelengths (<500 nm) is slightly overestimated with respect to Sentinel-2. This is in line with the estimates of g dd through the inversion that suggests an underestimated atmospheric path radiance of PRISMA level 2D products compared to the atmospherically corrected Sentinel-2 data. The results indicate the high potential of PRISMA level 2D imagery in mapping water quality parameters in Lake Trasimeno. The PRISMA-based retrievals agree well with those of Sentinel-2, particularly for TSM.
... Total bb (λ) (m −1 ) is computed as the sum of each constituent's scattering multiplied by constant and λindependent backscattering-to-scattering ratios (bbr W , bbr R , and bbr (i) PH ) that were 0.5 for water (Morel, 1974), 0.005 for detritus (Gallegos et al., 2011), 0.002 for P (DIATOM) (Dutkiewicz et al., 2015), 0.0071 for P (NANO) (Gregg and Rousseaux, 2017), 0.0039 for P (PICO) (Gregg and Rousseaux, 2017;Dutkiewicz et al., 2015), and 0.003 for P (DINO) (Dutkiewicz et al., 2015) (Table 1): ...
Chromophoric dissolved organic matter (CDOM) significantly contributes to the non-water absorption budget in the Mediterranean Sea. The absorption coefficient of CDOM, aCDOM(λ), is measurable in situ and can be retrieved remotely, although ocean-colour algorithms do not distinguish it from the absorption of detritus. These observations can be used as indicators for the concentration of other relevant biogeochemical variables in the ocean, e.g. dissolved organic carbon. However, our ability to model the biogeochemical processes that determine CDOM concentrations is still limited. Here we propose a novel parameterization of the CDOM cycle that accounts for the interplay between the light- and nutrient-dependent dynamics of local CDOM production and degradation, as well as its vertical transport. The parameterization is included in a one-dimensional (1D) configuration of the Biogeochemical Flux Model (BFM), which is here coupled to the General Ocean Turbulence Model (GOTM) through the Framework for Aquatic Biogeochemical Models (FABM). Here the BFM is augmented with a bio-optical component that resolves spectrally the underwater light transmission. We run this new GOTM-(FABM)-BFM configuration to simulate the seasonal aCDOM(λ) cycle at the deep-water site of the Bouée pour l'acquisition de Séries Optiques à Long Terme (BOUSSOLE) project in the northwestern Mediterranean Sea. Our results show that accounting for both nutrient and light dependence of CDOM production improves the simulation of the seasonal and vertical dynamics of aCDOM(λ), including a subsurface maximum that forms in spring and progressively intensifies in summer. Furthermore, the model consistently reproduces the higher-than-average concentrations of CDOM per unit chlorophyll concentration observed at BOUSSOLE. The configuration, outputs, and sensitivity analyses from this 1D model application will be instrumental for future applications of BFM to the entire Mediterranean Sea in a three-dimensional configuration.
... where b bp (λ i ) is the backscattering coefficient of particles and b bw (λ i ) is the backscattering coefficient of water molecules given by Morel [35]. The absorption coefficient a(λ i ) was calculated as the sum of the following [5]: ...
The Pomeranian lakes in Northern Poland and the nearby coastal waters of the Baltic Sea
belong to optically complex water bodies characterised by high eutrophication levels. These water
types require a local approach when developing bio-optical algorithms that combine the inherent
and the apparent properties of seawater. Well-established local algorithms are of great value for
understanding and addressing rapid changes in water quality related mostly to human activities
in coastal and near-shore zones, as well as in optically similar lakes. Our research analyses the
possibility of using the multi-parameter algorithms of absorption a(l), backscattering bb(l) and
remote sensing reflectance Rrs(l), originally developed for the coastal waters of the Southern Baltic
Sea, for three selected Pomeranian lakes. Our multi-parameter algorithms are based on the input
concentrations of the biogeochemical components measured in the lake waters, i.e., chlorophyll
a (Chl a), suspended particulate matter (SPM), inorganic suspended particulate matter (SPMinorg),
the sum of the surface concentrations of accessory pigments (SC) and coloured dissolved organic
matter with a wavelength of 400 nm (aCDOM(400)). Rrs(l) and a(l) output values were compared
with independent measurements of these parameters conducted in the lake waters at 20 sampling
stations. Our algorithm output values of bb(l) were compared to the values obtained based on the
algorithm provided by Ficek, previously developed and validated for Pomeranian lakes, at the same
stations. The statistical analyses conducted afterwards showed that the multi-parameter algorithms
of Rrs(l) and a(l) for the Southern Baltic Sea are sufficient to be used for the stations investigated in
the aforementioned three lakes. Specifically, the correlations between the bb(l) values obtained based
on the Ficek algorithm and the bb(l) values obtained using our multi-parameter algorithm reveal a
statistical error rate of less than 20%.
... Afterwards, no additional in-depth quantitative research was carried out. Relevant studies have investigated the optical difference between pure fresh water and seawater (Morel 1974;Smith and Baker 1981). However, such studies, especially those with detailed discussions of the optical characteristics of water bodies with different salinity, were rarely published in the following decades. ...
Salinity is an essential factor of lake water environments and aquatic systems. It is also sensitive to climatic changes and human activities based on concentration variations of solved minerals. However, there are few consecutively temporal studies on lake salinity variations on the Tibetan Plateau because the harsh environmental conditions make it difficult to carry out in-situ observations for several lakes. In this study, we constructed a remote sensing retrieval model for lake salinity based on 87 in-situ lake investigations; moreover, interannual lake salinity and associated variations from 152 lakes larger than 50 km² were analyzed on the Tibetan Plateau. A significant decreasing trend in lake salinity was observed between 2000 and 2019 (p < 0.01). The spatial variation of lake salinity was negatively correlated with lake area changes, and the optical characteristics of salt mineral solutions were generally positively correlated with mineral concentration based on the absorption coefficients of ionic solutions. The decreasing trend of lake salinity was not directly affected by the precipitation, but was potentially dominated by the expanding lake water volume. This study improves the understanding of regional water environmental changes and management efficacy of water resources.
... where the subscript "p" in Eq. (A4 denotes particles, including phytoplankton and detritus. Literature values of a w (λ) [35,36] and b bw (λ) [37] are used. As in Lee et al. [38], a ph (λ) is expressed as a nonlinear function of a ph (440) a ph (λ) = [a 0 (λ) + a 1 (λ) · ln(a ph (440))] · a ph (440) ...
The effective sea-surface skylight reflectance (ρ) is an important parameter for removing the contribution of surface-reflected radiance when measuring water-leaving radiance (Lw) using the above-water approach (AWA). Radiative simulations and field measurements show that ρ varies spectrally. To improve the determination of Lw (and then remote sensing reflectance, Rrs) from the AWA, we further developed a wavelength-dependent model for ρ to remove surface-reflected radiance, which is applied with a spectral optimization approach for the determination of Rrs. Excellent agreement was achieved between the AWA-derived and skylight-blocked approach (SBA)-obtained Rrs (coefficient of determination > 0.92, mean absolute percentage deviation < ∼ 11% for Rrs > 0.0005 sr⁻¹), even during high wave conditions. We found that the optimization approach with the new ρ model worked very well for a wide range of water types and observation geometries. For developing remote sensing algorithms and evaluating satellite products, it would be beneficial to apply this approach to current and historical above-water in situ measurements of Rrs to improve the quality of these data. In addition, this approach could also increase the number of useable spectra where previously rendered unusable when processed with a traditional scheme.
... Chlorophyll concentrations were generated logarithmically, i.e., the concentration was produced as the exponential of values generated in a uniformly distributed fashion between the natural logarithm of 0.005 and 1.5 mg m −3 , inducing a skew towards lower concentrations. Part of the data was generated from tabulated sources, specifically the water theoretical scattering (Morel, 1974) and absorption (Pope and Fry, 1997) coefficients and the numerical coefficients for generating the spectral absorption of phytoplankton (Bricaud et al., 1998). The tabulated values for water scattering were in turn used in our VRT Frontiers in Remote Sensing frontiersin.org ...
Introduction : In preparation for the upcoming PACE mission, we explore the feasibility of a neural network-based approach for the conversion of measurements of the degree of linear polarization at the top of the atmosphere as carried out by the HARP2 instrument into estimations of the ratio of attenuation to absorption in the surface layer of the ocean. Polarization has been shown to contain information on the in-water inherent optical properties including the total attenuation coefficient, in contrast with approaches solely based on remote sensing reflectance that are limited to the backscattered fraction of the scattering. In turn, these properties may be further combined with inversion algorithms to retrieve projected values for the optical and physical properties of marine particulates.
Methodology : Using bio-optical models to produce synthetic data in quantities sufficient for network training purposes, and with associated polarization values derived from vector radiative transfer modeling, we produce a two-step algorithm that retrieves surface-level polarization first and attenuation-to-absorption ratios second, with each step handled by a separate neural network. The networks use multispectral inputs in terms of the degree of linear polarization from the polarimeter and the remote sensing reflectance from the Ocean Color Instrument that are anticipated to be fully available within the PACE data environment.
Result and Discussion : Produce results that compare favorably with expected values, suggesting that a neural network-mediated conversion of remotely sensed polarization into in-water IOPs is viable. A simulation of the PACE orbit and of the HARP2 field of view further shows these results to be robust even over the limited number of data points expected to be available for any given point on Earth’s surface over a single PACE transit.
... The inherent optical properties (IOPs) of pure seawater have known quantities (Morel, 1974;Pope and Fry, 1997), and the IOPs can be derived by the quasi-analytical algorithm (QAA) (Lee et al., 2011;Chen and Zhang, 2015). The series of QAA algorithms input the above-surface remote sensing reflectance and output IOPs of the absorption and backscattering coefficients. ...
When a precise quantitative analysis of satellite measurements over bodies of water is required, the bidirectional effects of water-leaving radiance must be considered. The bidirectional reflectance distribution function (BRDF) is used to estimate the directional dependency of the radiance. Previous research on BRDF has focused on oceanic waters; few studies on turbid inland waters have been conducted. In this article, using multi-angle MISR measurements, five semi-empirical BRDF models (MAG2002, Lee2004, Park-Ruddick 2005, Woerd-Pasterkamp2008, and Lee2011) were quantitatively compared, and an adaptive algorithm was proposed over a typical turbid inland lake, Taihu Lake, China. Our results reveal the following: 1) the Woerd-Pasterkamp2008 and Lee2011 models provide the best fits with correlation coefficients greater than 0.8; 2) when prior modeling parameters were used, the Lee2011 model was still the most accurate with RMSEs less than 1.1%, while the accuracy of the Woerd-Pasterkamp2008 model varied; and 3) the use of an adaptive algorithm including an empirical rule based on the ratio of b b / a improved the accuracy. The results provide a theoretical basis for BRDF models and BRDF effects over inland Case II waters. They also provide a priori knowledge for future studies on water constituents and the quantitative inversion of atmospheric parameters.
... Subsequently, the absorption at 665 nm is analytically retrieved by inverting the Gordon reflectance model and attributed to Chla and water. The algorithm is specified as follows: Here, b bw (λ) is the backscattering coefficient of pure water obtained from Morel (1974) assuming zero salinity. In turn, u(λ) is the ratio of backscattering to the sum of backscattering and absorption, which according to the work by Gordon et al. (1988) can be obtained from below-surface remote-sensing reflectance rrs(λ) as: ...
Satellite product uncertainty estimates are critical for the further development and evaluation of remote sensing algorithms, as well as for the user community (e.g., modelers, climate scientists, and decision-makers). Optical remote sensing of water quality is affected by significant uncertainties stemming from correction for atmospheric effects as well as a lack of algorithms that can be universally applied to waterbodies spanning several orders of magnitude in non-covarying substance concentrations. We developed a method to produce estimates of Chlorophyll-a (Chla) satellite product uncertainty on a pixel-by-pixel basis within an Optical Water Type (OWT) classification scheme. This scheme helps to dynamically select the most appropriate algorithms for each satellite pixel, whereas the associated uncertainty informs downstream use of the data (e.g., for trend detection or modeling) as well as the future direction of algorithm research. Observations of Chla were related to 13 previously established OWT classes based on their corresponding water-leaving reflectance (Rw), each class corresponding to specific bio-optical characteristics. Uncertainty models corresponding to specific algorithm - OWT combinations for Chla were then expressed as a function of OWT class membership score. Embedding these uncertainty models into a fuzzy OWT classification approach for satellite imagery allows Chla and associated product uncertainty to be estimated without a priori knowledge of the biogeochemical characteristics of a water body. Following blending of Chla algorithm results according to per-pixel fuzzy OWT membership, Chla retrieval shows a generally robust response over a wide range of class memberships, indicating a wide application range (ranging from 0.01 to 362.5 mg/m³). Low OWT membership scores and high product uncertainty identify conditions where optical water types need further exploration, and where biogeochemical satellite retrieval algorithms require further improvement. The procedure is demonstrated here for the Medium Resolution Imaging Spectrometer (MERIS) but could be repeated for other sensors, atmospheric correction methods and optical water quality variables.
... The in-situ light spectrum 400-700 nm at depth z is estimated as Equation 12 using a typical incident solar spectrum (400-700 nm from Stomp et al., 2007b,a) and the spectrally dependent light attenuation coefficient [k d (λ)]. Following Morel et al. (2007), k d (λ)(Equation 13a and 13b) is equal to attenuation by pure seawater (a w (λ) from Pope and Fry (1997) and 1 2 b w (λ) from Morel (1974)) and attenuation by phytoplankton, non-algal particles and cultured dissolved organic material as k bio calculated as a function of chlorophyll-a using the coefficient χ(λ) and exponent c(λ). The spectral correction factors for σ PSII or the actinic background light are then calculated as Equations 10 and 11, respectively, where E LED (λ), E in−situ (λ), E background (λ), E actinic (λ) and a phy (λ) have been normalized to the maximum value of their respective spectra: ...
The uptake and application of single turnover chlorophyll fluorometers to the study of phytoplankton ecosystem status and microbial functions has grown considerably in the last two decades. However, standardization of measurement protocols, processing of fluorescence transients and quality control of derived photosynthetic parameters is still lacking and makes community goals of large global databases of high-quality data unrealistic. We introduce the Python package Phytoplankton Photophysiology Utilities (PPU), an adaptable and open-source interface between Fast Repetition Rate and Fluorescence Induction and Relaxation instruments and python. The PPU package includes a variety of functions for the loading, processing and quality control of single turnover fluorescence transients from many commercially available instruments. PPU provides the user with greater flexibility in the application of the Kolber-Prasil-Falkowski model; tools for plotting, quality control, correcting instrument biases and high-throughput processing with ease; and a greater appreciation for the uncertainties in derived photosynthetic parameters. Using data from three research cruises across different biogeochemical regimes, we provide example applications of PPU to fit raw active chlorophyll-a fluorescence data from three commercial instruments and demonstrate tools which help to reduce uncertainties in the final fitted parameters.
... One of the baselines was built using the blue and NIR bands, which made it possible to detect increasing algal biomass through the uplift reflectance of the NIR band. The entire spectral reflectance was low for clean water and showed no evident fluctuations in the NIR band [117], which may not be applicable for clean water to obtain good inversion results. Therefore, the classification of lakes will be developed for future studies to improve inversion accuracy. ...
Remote monitoring of trophic state for inland waters is a hotspot of water quality studies worldwide. However, the complex optical properties of inland waters limit the potential of algorithms. This research aims to develop an algorithm to estimate the trophic state in inland waters. First, the turbid water index was applied for the determination of optical water types on each pixel, and water bodies are divided into two categories: algae-dominated water (Type I) and turbid water (Type II). The algal biomass index (ABI) was then established based on water classification to derive the trophic state index (TSI) proposed by Carlson (1977). The results showed a considerable precision in Type I water (R2 = 0.62, N = 282) and Type II water (R2 = 0.57, N = 132). The ABI-derived TSI outperformed several band-ratio algorithms and a machine learning method (RMSE = 4.08, MRE = 5.46%, MAE = 3.14, NSE = 0.64). Such a model was employed to generate the trophic state index of 146 lakes (> 10 km2) in eastern China from 2013 to 2020 using Landsat-8 surface reflectance data. The number of hypertrophic and oligotrophic lakes decreased from 45.89% to 21.92% and 4.11% to 1.37%, respectively, while the number of mesotrophic and eutrophic lakes increased from 12.33% to 23.97% and 37.67% to 52.74%. The annual mean TSI for the lakes in the lower reaches of the Yangtze River basin was higher than that in the middle reaches of the Yangtze River and Huai River basin. The retrieval algorithm illustrated the applicability to other sensors with an overall accuracy of 83.27% for moderate-resolution imaging spectroradiometer (MODIS) and 82.92% for Sentinel-3 OLCI sensor, demonstrating the potential for high-frequency observation and large-scale simulation capability. Our study can provide an effective trophic state assessment and support inland water management.
... This reference shows that, for the concentration and wavelengths of our interest, the complex refractive index of several binary and mixed-salt solutions presents negligible difference with respect to that of deionized water or standard saline solutions. For this reason, we will assume that the refractive index of our solution is the same as that of simple water [see also Morel, 1974;Pegau et al., 1997). ...
This paper presents results on the electromagnetic field computed inside isolated mitochondria when they are exposed to near‐infrared illuminations with reference to photobiomodulation experiments. The accurate calculation of the electromagnetic dose is considered to be important for a better understanding of the mechanism of interaction of light with these organelles and to improve the reliability and repeatability of the experiments. To get such results, we introduce several models. Even though they refer to a well‐defined experimental setup, different models are necessary to take into account the possible different dispositions of the mitochondria, and of the differences in their dimensions and in their constitutive parameters. Different wavelengths and polarizations are considered as well. The effects of all parameters on the electromagnetic field inside mitochondria are discussed.
... Detailed information about the deployment and the data processing of the IOP data can be found in Doxaran et al. (2012a). Figure 6 shows cross-sections of the total absorption and backscattering coefficients at 440 nm (a(440) and b b (440)), derived as b b = b bp + b bw , where b bw is the backscattering coefficient of pure seawater (Morel, 1974). Both a(440) and b b (440) showed the same patterns along the transects 600 and 300. ...
The MALINA oceanographic campaign was conducted during summer 2009 to investigate the carbon stocks and the processes controlling the carbon fluxes in the Mackenzie River estuary and the Beaufort Sea. During the campaign, an extensive suite of physical, chemical and biological variables were measured across seven shelf–basin transects (south–north) to capture the meridional gradient between the estuary and the open ocean. Key variables such as temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured onboard the Canadian research icebreaker CCGS Amundsen and from a barge in shallow coastal areas or for sampling within broken ice fields. Here, we present the results of a joint effort to compile and standardize the collected data sets that will facilitate their reuse in further studies of the changing Arctic Ocean. The data set is available at https://doi.org/10.17882/75345 (Massicotte et al., 2020).
... Lee et al. first proposed the QAA algorithm based on the relationship between Gordon's remote sensing reflectance and inherent optical properties, using remote sensing reflectance data to invert the absorption coefficient and the scattering coefficient [5,6,27,28]. First, the algorithm calculates the total absorption coefficient (a) at the reference wavelength (λ 0 ), and then derives the total absorption coefficient (a) at other wavelengths, thereby obtaining the absorption coefficient of the colored dissolved organic matter. ...
The inherent optical parameters play a very important role in determining the concentration of seawater components. One such inherent parameter, the absorption coefficient (a), is greatly significant when calculating each component’s content in water and simulating the water’s biological, physical and chemical properties. Quasi-analytical algorithm (QAA) is one of current inherent optical parameters inversion algorithms. In this study, we compared three versions of QAA, including QAA_V4, QAA_V5 and more recently QAA_V6, using IOCCG data set. The results showed that QAA_V4 model performs best for the inversion of the absorption coefficient at 443 nm, with MRE, RMSE and R² values of 11.82%, 0.1995 and 0.9099, respectively, while QAA_V6 has the highest accuracy when inverting a at 555 nm and 670 nm wavelengths. Next, we tested the three models using MODIS product data, including data from case I and case II waters. The data is extracted from image, after position matching, then was imported into the three QAA models to calculate their RMSE, MRE and R² values. The QAA model showed a high accuracy and robust applicability for absorption coefficient inversion at shorter wavelengths, such as 443 nm. Future research should include verification with more complicated water bodies, solidifying the foundation for implementing QAA into ocean color remote sensing research.
... Although hyperspectral reflectance can show distinguishable optical properties for different substrates, the features tend to be From Morel, 1974 concealed when the reflectance signals turn into a multispectral image. For application to Sentinel-2A imagery, the in situ spectral reflectance for each target was convolved by the sensor's RSR function of each band of Sentinel-2A: ...
Sentinel-2 mission has been shown to have promising applications in coral reef remote sensing because of its superior properties. It has a 5-day revisit time, spatial resolution of 10 m, free data, etc. In this study, Sentinel-2 imagery was investigated for bleaching detection through simulations and a case study over the Lizard Island, Australia. The spectral and image simulations based on the semianalytical (SA) model and the sensor spectral response function, respectively, confirmed that coral bleaching cannot be detected only using one image, and the change analysis was proposed for detection because there will be a featured change signal for bleached corals. Band 2 of Sentinel-2 is superior to its other bands for the overall consideration of signal attenuation and spatial resolution. However, the detection capability of Sentinel-2 is still limited by the water depth. With rapid signal attenuation due to the water absorption effect, the applicable water depth for bleaching detection was recommended to be less than 10 m. The change analysis was conducted using two methods: one radiometric normalization with pseudo invariant features (PIFs) and the other with multi-temporal depth invariant indices (DII). The former performed better than the latter in terms of classification. The bleached corals maps obtained using the PIFs and DII approaches had an overall accuracy of 88.9 and 57.1%, respectively. Compared with the change analysis based on two dated images, the use of a third image that recorded the spectral signals of recovered corals or corals overgrown by algae after bleaching significantly improved the detection accuracy. All the preliminary results of this article will aid in the future studies on coral bleaching detection based on remote sensing.
... The visible portion of the spectrun extends from about 430 to 770 THz. Pure water is relatively transparant in visible light; however, according to the Einstein-Smoluchowski theory, the random motion of water molecules, which in a sufficiently small local volume causes fluctuations of density, changes the local dielectric constant, causing scattering of light (Morel 1974;Reghunath et al. 1991). According to this theory (Reghunath et al. 1991), the isotropic part of the Rayleigh ratio is given by: ...
Developing a mathematical model for the dielectric properties of water over a wide range of frequencies helps design, develop, model and optimize processes involving the interaction of electromagnetic waves with water containing materials. Based on large data sets (1744 published dielectric measurements) from literature and significant extensions to mathematical models, which have also been presented in literature, a comprehensive mathematical model for the most important dipolar responses and molecular resonances of water, from radio wave to the ultraviolet frequencies has been developed. This model provides a good approximation to published dielectric properties of pure water. Where possible, it also accounts for the influence of salinity and temperature.
... From β(θc), the volume scattering of particles (βp) was calculated by subtracting the volume scattering of water (βw) which is a function of temperature and salinity (Zhang et al. 2009;Morel 1974). The particulate backscattering coefficients (bbp; m -1 ) from βp and total backscattering coefficients (bb; m -1 ) was then calculated from βp according to Boss and Pegau (2001): ...
The Central Red Sea (CRS) has been characterized by significant eddy activity throughout the year. Weakened wintertime stratification contributes to enhanced vertical exchange. In winter 2014–2015, an extended glider time series in the CRS captured this variability. Surface cooling and stronger winds resulted in deepening of the mixed layer (ML) to nearly 90 m. The vertical distributions of density and oxygen suggest that the ML did not penetrate the nutricline. However, mixing events dispersed phytoplankton from the deep CHL maximum (DCM) throughout the ML, increasing near‐surface chlorophyll. Following the mixing events, a mesoscale cyclonic eddy (CE) grew and intensified, weakening stratification and decreasing the ML depth within the eddy. Where the CE interfaced with an adjacent anticyclonic eddy (AE), the CE DCM subducted beneath the shallower AE DCM leading to a local integrated chlorophyll maximum. Low salinity water containing relatively high chlorophyll and CDOM concentrations, originating from the Gulf of Aden, appeared in late winter. Mesoscale eddy activity resulted in a 160 m upward displacement of the nutricline to ∼60 m, well within the euphotic layer. Remote sensing imagery indicates that these eddies contribute to horizontal dispersion, including exchange between the open sea and coastal coral reefs. When the phytoplankton is distributed through the ML, clear diel variability was evident in the temporal CHL distribution. Because not all of the biogeochemical responses were apparent at the surface, sustained glider observations were essential to understand the temporal and spatial scales and their impact on these processes.
... The absorption and backscattering coefficients for pure water come from the literature [52,53]. The coefficients for other components can be simulated using the empirical models as follows [54][55][56][57]: ...
Chlorophyll-a (Chl-a) is an objective biological indicator, which reflects the nutritional status of coastal waters. However, the turbid coastal waters pose challenges to the application of existing Chl-a remote sensing models of case II waters. Based on the bio-optical models, we analyzed the suppression of coastal total suspended matter (TSM) on the Chl-a optical characteristics and developed an improved model using the imagery from a hyper-spectrometer mounted on an unmanned aerial vehicle (UAV). The new model was applied to estimate the spatiotemporal distribution of Chl-a concentration in coastal waters of Qingdao on 17 December 2018, 22 March 2019, and 20 July 2019. Compared with the previous models, the correlation coefficients (R2) of Chl-a concentrations retrieved by the new model and in situ measurements were greatly improved, proving that the new model shows a better performance in retrieving coastal Chl-a concentration. On this basis, the spatiotemporal variations of Chl-a in Qingdao coastal waters were analyzed, showing that the spatial variation is mainly related to the TSM concentration, wind waves, and aquaculture, and the temporal variation is mainly influenced by the sea surface temperature (SST), sea surface salinity (SSS), and human activities.
... Detailed information about the deployment and the data processing of the IOP data can be found in Doxaran et al. (2012). (440)) derived as b b = b bp +b bw , where b bw is the backscattering coefficient of pure seawater (Morel, 1974). Both a(440) and b b (440) showed the same patterns along the transects 600 and 300. ...
The MALINA oceanographic campaign was conducted during summer 2009 to investigate the carbon stocks and the processes controlling the carbon Fluxes in the Mackenzie River estuary and the Beaufort Sea. During the campaign, an extensive suite of physical, chemical and biological variables was measured across seven shelf–basin transects (south-north) to capture the meridional gradient between the estuary and the open ocean. Key variables such as temperature, absolute salinity, radiance, irradiance, nutrient concentrations, chlorophyll-a concentration, bacteria, phytoplankton and zooplankton abundance and taxonomy, and carbon stocks and fluxes were routinely measured onboard the Canadian research icebreaker CCGS Amundsen and from a barge in shallow coastal areas or for sampling within broken ice fields. Here, we present the results of a joint effort to tidy and standardize the collected data sets that will facilitate their reuse in further studies of the changing Arctic Ocean.
... The phase function for atmospheric molecules is approximated by Rayleigh scattering, which can be given by [38] β ...
Spaceborne lidar (light detection and ranging) is a very promising tool for the optical properties of global atmosphere and ocean detection. Although some studies have shown spaceborne lidar’s potential in ocean application, there is no spaceborne lidar specifically designed for ocean studies at present. In order to investigate the detection mechanism of the spaceborne lidar and analyze its detection performance, a spaceborne oceanic lidar simulator is established based on the semianalytic Monte Carlo (MC) method. The basic principle, the main framework, and the preliminary results of the simulator are presented. The whole process of the laser emitting, transmitting, and receiving is executed by the simulator with specific atmosphere–ocean optical properties and lidar system parameters. It is the first spaceborne oceanic lidar simulator for both atmosphere and ocean. The abilities of this simulator to characterize the effect of multiple scattering on the lidar signals of different aerosols, clouds, and seawaters with different scattering phase functions are presented. Some of the results of this simulator are verified by the lidar equation. It is confirmed that the simulator is beneficial to study the principle of spaceborne oceanic lidar and it can help develop a high-precision retrieval algorithm for the inherent optical properties (IOPs) of seawater.
In order to verify the blue coloration model for Ao-ike Pond, Aomori Prefecture, Japan, the authors refined the formulas previously reported for the light intensities in the coloration model. Then, the authors utilized a homography transformation technique to obtain the coordinates on the pond water surface from the digital camera image. Moreover, they experimentally determined the sensitivity factor and white balance factor of a digital camera used. Assuming potential coloration mechanisms including irregular reflection at the pond bottom, molecular scattering by water and Mie scattering by suspended solids, two types of images were analyzed so as to determine model parameters; images taken in early spring when the shading by tree leaves does not exist above the pond surface, and images photographed in early summer containing incident light trajectories brought by the sunbeam’s passage through the leaves above the pond surface. Analytical results obtained by both of the images revealed that the main coloration mechanism is molecular scattering by water but with no contribution of Mie scattering. Thus, the blue color of Ao-ike Pond was judged to be attributed to the nature of water itself.
We propose a semi-analytical (SA) model for relating seafloor reflectance to measured radiance in deep-water hyperspectral imaging in artificially illuminated scenes. Using accurate sensor-seafloor geometry from photogrammetry and the principle of two-viewpoint observation, we estimate the inherent optical properties (IOPs) of the water column. We demonstrate the SA model and estimation of IOPs for hyperspectral imaging of a deep-water coral reef from a remotely operated vehicle. For the calibrated SA model, evaluation of across-viewpoint similarity demonstrates the model’s ability to compensate for water column and light source effects.
Radiative transfer (RT) simulations have long been used to study the relationships between the inherent optical properties (IOPs) of seawater and light fields within and leaving the ocean, from which ocean apparent optical properties (AOPs) can be calculated. For example, inverse models used to estimate IOPs from ocean color radiometric measurements have been developed and validated using the results of RT simulations. Here we describe the development of a new synthetic optical database based on hyperspectral RT simulations across the spectral range of near-ultraviolet to near-infrared performed with the HydroLight radiative transfer code. The key component of this development is the generation of a synthetic dataset of seawater IOPs that serves as input to RT simulations. Compared to similar developments of optical databases in the past, the present dataset of IOPs is characterized by the probability distributions of IOPs that are consistent with global distributions representative of vast areas of open-ocean pelagic environments and coastal regions, covering a broad range of optical water types. The generation of synthetic data of IOPs associated with particulate and dissolved constituents of seawater was driven largely by an extensive set of field measurements of the phytoplankton absorption coefficient collected in diverse oceanic environments. Overall, the synthetic IOP dataset consists of 3320 combinations of IOPs. Additionally, the pure seawater IOPs were assumed following recent recommendations. The RT simulations were performed using 3320 combinations of input IOPs, assuming vertical homogeneity within an infinitely deep ocean. These input IOPs were used in three simulation scenarios associated with assumptions about inelastic radiative processes in the water column (not considered in previous synthetically generated optical databases) and three simulation scenarios associated with the sun zenith angle. Specifically, the simulations were made assuming no inelastic processes, the presence of Raman scattering by water molecules, and the presence of both Raman scattering and fluorescence of chlorophyll a pigment. Fluorescence of colored dissolved organic matter was omitted from all simulations. For each of these three simulation scenarios, the simulations were made for three sun zenith angles of 0, 30, and 60 • assuming clear skies, standard atmosphere, and a wind speed of 5 m s −1. Thus, overall 29 880 RT simulations were performed. The output results of these simulations include radiance distributions, plane and scalar irradiances, and a whole set of AOPs, including remote-sensing reflectance, vertical diffuse attenuation coefficients, and mean cosines, where all optical variables are reported in the spectral range of 350 to 750 nm at 5 nm intervals for different depths between the sea surface and 50 m. The consistency of this new synthetic database has been assessed through comparisons with in situ data and previously developed empirical relationships involving IOPs and AOPs. The database is available at the Dryad open-access repository of research data (https://doi.org/10.
A traditional bathymetric light detection and ranging (B-LiDAR) has disadvantages such as large volume, heavy weight, necessity for airport and runway, and high cost for operation. For these reasons, this article presents an off-axis four-reflection optical structure for single-band (532 nm) B-LiDAR carried on unmanned aerial vehicle (UAV). This optical system fully considers characteristics of the laser echo energy under different water conditions, which relate to the optical system parameters, such as peak power of laser emission, field of view (FOV), and receiver aperture area. The proposed optical system designs the objective lens, which is composed of one avalanche photodiode (APD) detector and two photomultipliers (PMTs) detectors, the primary mirror, the second mirror, the plane mirror, and the third mirror, two split field mirrors that separate the echo signals from shallow water, medium water, and deep water, respectively. This proposed optical system was verified in a laboratory tank, swimming pool, Lijiang river, lake, and the Qiaogang Sea Bay. It is found that the maximum water depth measured can reach 25.0 m with an error of less than 0.1 m on average. The dimension and weight of this LiDAR reach
$90\times 160\times90$
mm and 10.25 kg, respectively, which is the lightest and smallest B-LiDAR worldwide.
The ECO BB9, an instrument designed for characterizing the particulate backscattering coefficient (bbp) of waters in situ, saturates frequently in water with high concentrations of particles. These water types are of increasing interest in water optics research due to the complexity of their contents and gaps in the knowledge of their interactions with the light field. Through serial dilutions, the concentrations of particles can be brought into the instrument range and linear extrapolation can be used to yield a prediction of bbp for the original undiluted solution. The efficacy of this simple approach is explored here using natural and synthetic waters in a controlled laboratory setting. bbp is a key inherent optical property used in validating and calibrating water quality parameters commonly estimated by remote sensing inversion algorithms. For this reason, the synthetic waters were constructed to test the method across water types characteristic of colored dissolved organic matter, non‐algal particulates, and phytoplankton. The dilution method was evaluated by assessment of dilution series accuracy, precision, and constancy of the backscattering spectral slope. It was found to be effective with all water types in this paper.
In recent years, oceanic lidar has seen a wide range of oceanic applications, such as optical profiling and detecting bathymetry. Furthermore, spaceborne lidars, CALIOP and ICESat-2, designed for atmospheric and ice science applications, have been used for ocean backscattering retrievals, but, until now, there has been no spaceborne lidar specifically designed for ocean detection. There is a demand for an effective lidar simulator to study the detection potential capability of spaceborne oceanic lidar. In this study, an open-source spaceborne oceanic lidar simulator named SOLS was developed, which is available freely. Moreover, the maximum detectable depth and corresponding optimal wavelength for spaceborne lidar were analyzed at a global scale by using SOLS. The factors controlling detection limits of a spaceborne ocean profiling lidar in different cases were discussed. Then, the maximum detectable depths with different relative measurement errors and the influence of solar background radiance were estimated. Subsequently, the effects of laser and detector parameters on maximum detectable depths were studied. The relationship between the lidar detectable depth and the ocean mixed layer depth was also discussed. Preliminary results show that the maximum detectable depth could reach deeper than 120 m in the oligotrophic sea at low latitudes. We found that 490 nm is the optimal wavelength for most of the open seawater. For coastal water, 532 nm is a more suitable choice considering both the technical maturity and geophysical parameters. If possible, a lidar equipped with 440 nm could achieve the greatest depth in oligotrophic seawater in subtropical gyres north and south of the equator. The upper mixed layer vertical structure in most of the global open ocean is within the lidar maximum detectable depth. These results show that SOLS can help the design of future spaceborne oceanic lidar systems a lot.
Satellite sensors are used to monitor water on a large scale. One of the key variables defining the water-leaving signal is suspended particulate matter (SPM) and thus it is important to understand its properties to improve remote sensing algorithms. However, only a few studies investigating the variability of SPM properties (concentration, nature and size) under different seasonal, weather and geographical conditions have been carried out in the Baltic Sea. We focused on relatively shallow areas (maximum depth of 10 m) where there is strong sediment transport by rivers and resuspension of the particles by wave action and advection by currents. Eleven field campaigns were conducted using a set of instruments measuring inherent optical properties, auxiliary data, and, in Pärnu Bay, also particle size distributions. The results showed that the (SPM) concentrations, particulate absorption, mass-specific particulate scattering, and backscattering varied temporally and spatially from 5.5–19.6 g m⁻³, 0–5.62 m⁻¹, 0.08–1.45 m² g⁻¹, and 0.0009–0.25 m² g⁻¹, respectively. The spectral backscattering ratio, which in general is considered to be constant in bio-optical remote sensing algorithms, was actually wavelength-independent and varied between 0.005 and 0.09 depending on the origin of the particles (organic or mineral matter), particle size distribution, weather conditions, and location. In situ particle size measurements in coastal waters of Pärnu Bay also showed that resuspended fine clay particles agglomerated into flocs of >30 µm in the brackish waters of the Baltic Sea having random shapes and different sizes.
Using in situ measurements of radiometric quantities and of the optical backscattering coefficient of particulate matter ( ${{{b}}_{\textit{bp}}}$ b bp ) at an oceanic site, we show that diel cycles of ${{{b}}_{\textit{bp}}}$ b bp are large enough to generate measurable diel variability of the ocean reflectance. This means that biogeochemical quantities such as net phytoplankton primary production, which are derivable from the diel ${{{b}}_{\textit{bp}}}$ b bp signal, can be potentially derived also from the diel variability of ocean color radiometry (OCR). This is a promising avenue for basin-scale quantification of such quantities because OCR is now performed from geostationary platforms that enable quantification of diel changes in the ocean reflectance over large ocean expanses. To assess the feasibility of this inversion, we applied three numerical inversion algorithms to derive ${{{b}}_{\textit{bp}}}$ b bp from measured reflectance data. The uncertainty in deriving ${{{b}}_{\textit{bp}}}$ b bp transfers to the retrieval of its diel cycle, making the performance of the inversion better in the green part of the spectrum (555 nm), with correlation coefficients ${\gt}{0.75}$ > 0.75 and a variability of 40% between the observed and derived ${{{b}}_{\textit{bp}}}$ b bp diel changes. While the results are encouraging, they also emphasize the inherent limitation of current inversion algorithms in deriving diel changes of ${{{b}}_{\textit{bp}}}$ b bp , which essentially stems from the empirical parameterizations that such algorithms include.
The traditional way to detect the vertical structure of seawater optical properties and chlorophyll-a is mainly through shipboard discrete observations or biogeochemical-argo profiling floats, which requires considerable time to cover a limited area. In this study, the vertical distribution of seawater optical properties and chlorophyll-a concentration across two different optically contrasted sea areas from the East China Sea (ESC) to the South China Sea (SCS) were obtained for the first time using a shipboard integrated Mie–Raman–fluorescence Light Detection and Ranging (LiDAR) for large-scale observations, with a total observation distance of over 3700 km. More than 74000 LiDAR profiles were obtained from September 5 to September 15, 2020. In general, the LiDAR-estimated inherent optical properties (IOPs) and chlorophyll-a values decreased from turbid water in the ECS to clear water in the SCS. Subsurface scattering layers were often observed at depths ranging from 10 to 20 m along the SCS coast. Subsequently, the LiDAR-derived results were compared against in situ measurements. In addition, the diurnal hourly variation in IOPs and chlorophyll-a by LiDAR at a fixed coastal station was monitored for the first time, which was relatively lower in the early morning and midday yet was higher in the evening, while the relative tide height showed the reverse change trend, which revealed that the tide possibly impacted the diurnal variation in IOPs and chlorophyll-a on the SCS coast. Overall, our results indicate that the LiDAR remote sensing technique is effective and feasible to monitor large-scale and long-term subsurface phytoplankton structure over different optically contrasted sea regions, and integration of multiple detection mechanisms will enhance the monitoring capacity.
This paper reports on detailed studies of the relationship between the inherent optical properties (IOPs) of suspended particulate matter populations occurring in southern Baltic Sea waters, and the basic biogeochemical and morphological quantities enabling these populations to be generally characterized. Specifically, these IOPs are the spectral absorption coefficients by all particulate matter, phytoplankton pigments and detritus, the spectral scattering and backscattering coefficients by particles, and the backscattering ratio. The biogeochemical properties of suspended matter populations are characterized by measuring concentrations of suspended particulate matter (SPM), particulate organic matter (POM) and particulate inorganic matter (PIM), as well as concentrations of various phytoplankton pigments, including chlorophyll a (Chla). We also take particle size distributions (PSDs) into account. This diverse empirical material is used to describe how the typical relationships between the IOPs of suspended matter and the concentrations of the main water constituents (SPM or Chla) can be influenced by differences in the general composition and size distributions of the suspended matter. We statistically describe the possible impact on these relationships of the variability of composition ratios, such as POM/SPM and Chla/SPM, as well as the impact of the variability of certain characteristics calculated on the basis of PSDs: the average particle diameter weighted by the particle's projected area (DA), the average apparent density of particles (ρa), the average intracellular concentration of chlorophyll a (ci), and the corresponding products of these quantities. We also demonstrate the significant variability of the specific IOPs (SIOPs) by attempting to determine them in the classical way for our southern Baltic data, and we give a possible interpretation of this variability. On the basis of these analyses, we derive new, multicomponent IOP parameterizations that are functions of several variables. These new parameterizations enable the IOPs of suspended matter to be characterized and predicted with better accuracy than with the often-used standard one-component relationships.
In this study, six algorithms (both empirical and semi-analytical) developed for the estimation of Kd in the ultraviolet (UV) domain (specifically 360, 380, and 400 nm) were evaluated from a dataset of 316 stations covering oligotrophic ocean and coastal waters. In particular, the semi-analytical algorithm (Lee et al. 2013) used remote sensing reflectance in these near-blue UV bands estimated from a recently developed deep learning system as the input. For Kd(380) in a range of 0.018 - 2.34 m⁻¹, it is found that the semi-analytical algorithm has the best performance, where the mean absolute relative difference (MARD) is 0.19, and the coefficient of determination (R²) is 0.94. For the empirical algorithms, the MARD values are 0.23–0.90, with R² as 0.70–0.92, for this evaluation dataset. For a VIIRS and in situ matchup dataset (N = 62), the MARD of Kd(380) is 0.21 (R² as 0.94) by the semi-analytical algorithm. These results indicate that a combination of deep learning system and semi-analytical algorithms can provide reliable Kd(UV) for past and present satellite ocean color missions that have no spectral bands in the UV, where global Kd(UV) products are required for comprehensive studies of UV radiation on marine primary productivity and biogeochemical processes in the ocean.
Global ocean color measurements from satellites provide critical information about ocean ecology and biogeochemistry, this advances our knowledge of the carbon cycle and its impact on climate disturbances. The repeated synoptic observations of spectral leaving reflectance can be used to estimate marine inherent optical properties. The spatial, angular, and spectral distributions of underwater light field depend upon the absorption and scattering characteristics, the inherent optical properties (IOPs), of oceanic particles or hydrosols. The remote sensing algorithms or inverse methods typically rely on forward models to relate the satellite observed quantity, remote sensing reflectance, with the corresponding IOPs. The viewing angle dependence, spectral, and polarization states of reflected light contain rich information on the retrieval IOP parameters. The inverse methods depend on a reliable atmospheric correction algorithm. However, due to the presence of absorbing aerosols and complex optical properties of coastal waters, it is difficult to achieve successful atmospheric correction over coastal waters or when absorbing aerosols are involved. To overcome the limitations of atmospheric correction in coastal and inland waters involving absorbing aerosols, the use of multi-angle, multi-wavelength, polarized measurements to characterize aerosol and hydrosol properties would be beneficial. The polarized signal is measured by several multi-angular polarimeters like POLDER, the Research Scanning Polarimeter (RSP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Spectropolarimeter for Planetary EXploration (SPEX) and the HyperAngular Rainbow Polarimeter (HARP). Notably, NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission plans to carry SPEXone and HARP2 as well as the Ocean Color Instrument (OCI), which will acquire an abundance of unprecedented co-located datasets of polarimeter and ocean color measurements. To handle the huge volume of data it is critical to use a fast ocean reflectance model that can be used in the retrieval algorithms to achieve operational retrieval of aerosol and ocean color information. The retrieval algorithms need to call radiative transfer models iteratively in order to minimize the difference between measurements and model prediction, which is computationally expensive. In this chapter, available fast retrieval algorithms based on machine learning techniques used by the community are reviewed. Their scopes and limitations is discussed. Particularly this chapter summarizes various machine learning and optimization algorithms used in ocean optics studies.KeywordsOcean opticsRadiative transferMachine learning techniquesRemote sensing
Many countries share an effort to understand the impact of growing urban areas on the environment. Spatial, spectral, and temporal resolutions of remote sensing images offer unique access to this information. Nevertheless, their use is limited because urban surface materials exhibit a great diversity of types and are not well spatially and spectrally distinguishable. This work aims to quantify the effect of these spatial and spectral characteristics of urban surface materials on their retrieval from images. To avoid other sources of error, synthetic images of the historical center of Venice were analyzed. A hyperspectral library, which characterizes the main materials of Venice city and knowledge of the city, allowed to create a starting image at a spatial resolution of 30 cm and spectral resolution of 3 nm and with a spectral range of 365–2500 nm, which was spatially and spectrally resampled to match the characteristics of most remote sensing sensors. Linear spectral mixture analysis was applied to every resampled image to evaluate and compare their capabilities to distinguish urban surface materials. In short, the capability depends mainly on spatial resolution, secondarily on spectral range and mixed pixel percentage, and lastly on spectral resolution; impervious surfaces are more distinguishable than pervious surfaces. This analysis of capability behavior is very important to select more suitable remote sensing images and/or to decide the complementarity use of different data.
The topic of underwater (UW) image colour correction and restoration has gained significant scientific interest in the last couple of decades. There are a vast number of disciplines, from marine biology to archaeology, that can and need to utilise the true information of the UW environment. Based on that, a significant number of scientists have contributed to the topic of UW image colour correction and restoration. In this paper, we try to make an unbiased and extensive review of some of the most significant contributions from the last 15 years. After considering the optical properties of water, as well as light propagation and haze that is caused by it, the focus is on the different methods that exist in the literature. The criteria for which most of them were designed, as well as the quality evaluation used to measure their effectiveness, are underlined.
Climatic changes have decreased the stability of the Gulf Stream (GS), increasing the frequency at which its meanders interact with the Mid‐Atlantic Bight (MAB) continental shelf and slope region. These intrusions are thought to suppress biological productivity by transporting low‐nutrient water to the otherwise productive shelf edge region. Here we present evidence of widespread, anomalously intense subsurface diatom hotspots in the MAB slope sea that likely resulted from a GS intrusion in July 2019. The hotspots (at ∼50 m) were associated with water mass properties characteristic of GS water (∼100 m); it is probable that the hotspots resulted from the upwelling of GS water during its transport into the slope sea, likely by a GS meander directly intruding onto the continental slope east of where the hotspots were observed. Further work is required to unravel how increasingly frequent direct GS intrusions could influence MAB marine ecosystems.
A performance evaluation of ocean color chlorophyll-a algorithms was conducted based on the in situ fluorescence chlorophyll concentration (Fchl) measured by a sensor on the buoy SiMCosta-SC01 in coastal waters of South Brazil. The operational algorithms are used in MODIS and VIIRS sensors to derive satellite chlorophyll concentration (Csat). Fchl values were successfully corrected for nonphotochemical quenching (NPQ) by an interpolation of sunrise and sunset daily measurements. A laboratory-derived calibration coefficient was applied to convert the unquenching Fchl values into chlorophyll concentration (Cflu). Overall, linear regression analysis between Cflu and Csat for both sensors showed good results, with the coefficient of determination (R2) varying between 0.88 and 0.96, slopes between 0.92 and 1.02 and intercepts between -0.17 and 0.13. The MODIS algorithm (R2 = 0.96, slope = 1.02, RMSE = 0.16 mg m-3, BIAS = 0.16 mg m-3, for N = 222 and time interval ±1 h) presented slightly better performance than VIIRS (R2 = 0.92, slope = 0.96, RMSE = 0.25 mg m-3, BIAS = -0.25 mg m-3, for N = 284 and time interval ±1 h). These results represent the most comprehensive satellite data analysis for this region, suggesting that the approach may be applicable to other SiMCosta buoys.
The particulate backscattering coefficient (bbp) provides effective proxies for particulate organic carbon (POC) and phytoplankton carbon (Cphy); however, their bio-optical relationships in the oligotrophic ocean are rarely reported. In this work, based on the in-situ synchronous optical and biogeochemical measurements in the oligotrophic South China Sea (SCS) basin, we refined the regional relationships between POC (and Cphy) and bbp and investigated the impacts of phytoplankton community compositions and size classes on the bbp variability. The observations showed that: 1) POC and Cphy exhibited good linear relationships with bbp; 2) the relationship between Cphy and POC could also be fitted in a linear function with a positive POC intercept, and the POC contributed by phytoplankton-covarying non-algal particles was nearly two-fold of Cphy; and 3) the POC-specific bbp (b*bp) was positively correlated with the fraction of the phytoplankton groups haptophytes (Type 8) and diatoms to total Chla, but negatively correlated with the fraction of pico-phytoplankton to Chla (fpico). These findings suggest that in oligotrophic waters, the variability of b*bp was mainly determined by the variability in the relative contribution of large phytoplankton with complex structures.
for the detection of shallow underwater targets by the hyperspectrum, the information of the target is carried in the water-leaving radiation. However, the differences between the water-leaving radiation of the underwater target and the ocean background radiation are not significant, and the spectrum of the water-leaving radiation is sensitive to the changes of the marine environment. Therefore, taking the spectrum as the feature is not stable for hyperspectral detection of the underwater target. In this paper, we propose a parameter feature extraction method for hyperspectral detection of the shallow underwater target. The presence of an underwater target would change the optical properties of seawater in a local place. Based on that, a quasi-analytical model of the water-leaving radiation is adopted to inverse the properties of the marine environment from the radiated spectrum. Then the inversed water depth and bottom reference reflectance are taken as the features. Simulation results show that the samples which belong to the water-leaving radiation of underwater target have higher inversed depth and reference reflectance than that belong to the ocean background radiation. Furthermore, these two kinds of samples can be separated significantly and stably in a 2-dimension feature space.
The case-1 (optically simple) oceanic environment is described by a smoothly transitioning gradient in optical properties arising from the concentration of the primary algal photopigment, chlorophyll a, plus its covarying and optically relevant constituents. As such, the spectral transition that defines case-1 water types is captured by a single primary spectral mode—the transition in peak wavelength between oligotrophic blue and mesotrophic green waters—which has substantiated blue-green algorithm designs and sensor capabilities for oceanographic observations that primarily focus on retrieving the visible (VIS) spectral domain. For case-2 water types, e.g., optically complex inland and coastal waters interacting with the continent and shelf, a similar unifying mode that captures common spectral changes is not defined. This study evaluates the potential to formulate optical complexity as a progression of discrete or continuous parameters in order to advance radiometry for a global range of water types. Within a gradient of increasing optical complexity, this study uses a comprehensive set of case-2 scenarios to compare spectral changes as a function of increasing water mass complexity, based on simple diagnostic tools and definitions. The spectral comparisons rely on instrument and data processing improvements—developed from an end-member analysis (EMA) perspective—that optimize a spectral domain spanning wavelengths shorter and longer than the primarily case-1 VIS domain, i.e., the ultraviolet (UV) and near-infrared (NIR) domains, and that enable sampling of shallow or non-navigable water bodies. The spectral comparisons in the case-2 scenarios indicate five primary modes capture the dominant spectral changes associated with increasing optical complexity. The primary modes and diagnostic tools presented herein enable the organization of global (i.e., oceanic, coastal, and inland) water bodies along a continuous complexity gradient defined by optical complexity instead of as a binary and discontinuous partition (i.e., case-1 and case-2). The expression and dynamic range of the modes establish the spectral regions most sensitive to water mass transitions in optically complex environments. These spectral expressions provide a basis for evaluating the spectral sensing requirements for next-generation remote sensing missions, which seek to characterize optically complex coastal (i.e., the continental shelf and its environs) and inland water bodies. In particular, three of five spectral modes indicate the spectral response to increasing optical complexity is greatest at the spectral end members. The results presented indicate that both discretized values and a continuum are useful for formulating a hierarchy in optical complexity and suggest next-generation activities should optimize the retrieval of the UV and NIR domains for improving the development of global algorithms.
Ultraviolet (UV) bands have attracted considerable attention in regard to satellite ocean color remote sensing due to their potential application in atmospheric correction, oil spill detection, and water organic matter retrieval. However, the characteristics of the water spectrum in the UV bands are still poorly understood. In this study, by extending the bio-optical model from traditional visible light wavelengths to UV light wavelengths, the water spectrum in UV bands under different water types was simulated by using the HydroLight water radiative transfer model, and influences of ocean color components on the water spectrum in UV bands were investigated. Results showed that remote sensing reflectance (Rrs) in the UV bands decreased rapidly with the increase in chlorophyll concentration (Chl) and colored dissolved organic matter (CDOM). In clean waters, Rrs in the UV bands was relatively large and sensitive to changes in Chl and CDOM, which could be of benefit for satellite retrieval of water organic matter. In eutrophic water, Rrs in the UV bands was quite low, and thence the UV bands could be used as a reference band for atmospheric correction. Compared to the monotonic decreasing effects of Chl and CDOM, concentration of non-algal particles (NAP) had a complex effect on Rrs in the UV bands, i.e., increase and decrease in Rrs in low-moderately and highly turbid waters, respectively. Thus, the traditional model for the relationship between Rrs and inherent optical properties (IOPs) could be applied to the UV bands in clean waters; in highly turbid waters, however, its deviation increases and empirical coefficients in the model should be improved.
The photobleaching of chromophoric dissolved organic matter (CDOM) is considered an important loss process for CDOM absorption in sunlit natural waters, where it can regulate the biota's exposure to sunlight, surface solar heating, and dissolved organic matter dynamics. Despite its importance, this sink remains poorly quantified, primarily because of the difficulty of determining photobleaching apparent quantum yields (AQYs) that capture the dual spectral dependency of this process and are applicable to polychromatic sunlight. Here, we present a simple method to determine a CDOM photobleaching AQY matrix (AQY-M) for natural water samples that does not require any a priori assumptions about the spectral dependency of photobleaching. It combines controlled irradiation experiments, a partial least-square regression, and an optimization procedure to produce AQY-Ms that are spectrally coherent and optimized for modeling accurate photobleaching rates in natural waters. Water temperature and the solar exposure history of CDOM had a major influence on the magnitude and spectral characteristics of the AQY-M. These factors should be considered when determining the AQY-M of samples and provide constraints when modeling photobleaching rates in natural waters. We expect that this effective method will provide future studies with a robust means to characterize and understand the variability of AQY-M in natural waters.
Ocean water column information profiles are essential for ocean research. Currently, water column profiles are typically obtained by ocean lidar instruments, including spaceborne, airborne and shipborne lidar, most of which are equipped with a 532 nm laser; however, blue wavelength penetrates more for open ocean detection. In this paper, we present a novel airborne dual-wavelength ocean lidar (DWOL), equipped with a 532 and 486 nm laser that can operate simultaneously. This instrument was designed to compare the performance of 486 and 532 nm lasers in a single detection area and to provide a reference for future spaceborne oceanic lidar (SBOL) design. Airborne and shipborne experiments were conducted in the South China Sea. Results show that—for a 500-frame accumulation—the 486 nm channel obtained volume profiles from a depth of approximately 100 m. In contrast, the vertical profiles obtained by the 532 nm channel only reached in a depth of 75 m, which was approximately 25% less than that of 486 m channel in the same detection area. Results from the inverse lidar attenuation coefficient α(z) for the DWOL show that the maximum value of α(z) ranged from 40 to 80 m, which was consistent with the chlorophyll-scattering layer (CSL) distribution measured by the shipborne instrument. Additionally, α486(z) decreased for depth beyond 80 m, indicating that the 486 nm laser can potentially penetrate the entire CSL.
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