Specific Inherent Optical Properties Research Articles

Inherent optical properties of suspended particulate matter in the southern Baltic Sea in relation to the concentration, composition and characteristics of the particle size distribution; new forms of multicomponent parameterizations of optical properties

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.

Classification of Australian Waterbodies across a Wide Range of Optical Water Types

Baseline determination and operational continental scale monitoring of water quality are required for reporting on marine and inland water progress to Sustainable Development Goals (SDG). This study aims to improve our knowledge of the optical complexity of Australian waters. A workflow was developed to cluster the modelled spectral response of a range of in situ bio-optical observations collected in Australian coastal and continental waters into distinct optical water types (OWTs). Following clustering and merging, most of the modelled spectra and modelled specific inherent optical properties (SIOP) sets were clustered in 11 OWTs, ranging from clear blue coastal waters to very turbid inland lakes. The resulting OWTs were used to classify Sentinel-2 MSI surface reflectance observations extracted over relatively permanent water bodies in three drainage regions in Eastern Australia. The satellite data classification demonstrated clear limnological and seasonal differences in water types within and between the drainage divisions congruent with general limnological, topographical, and climatological factors. Locations of unclassified observations can be used to inform where in situ bio-optical data acquisition may be targeted to capture a more comprehensive characterization of all Australian waters. This can contribute to global initiatives like the SDGs and increases the diversity of natural water in global databases.

Modelling Water Colour Characteristics in an Optically Complex Nearshore Environment in the Baltic Sea; Quantitative Interpretation of the Forel-Ule Scale and Algorithms for the Remote Estimation of Seawater Composition

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.

Inherent Optical Properties of the Baltic Sea in Comparison to Other Seas and Oceans

In order to retrieve geophysical satellite products in coastal waters with high coloured dissolved organic matter (CDOM), models and processors require parameterization with regional specific inherent optical properties (sIOPs). The sIOPs of the Baltic Sea were evaluated and compared to a global NOMAD/COLORS Reference Data Set (RDS), covering a wide range of optical provinces. Ternary plots of relative absorption at 442 nm showed CDOM dominance over phytoplankton and non-algal particle absorption (NAP). At 670 nm, the distribution of Baltic measurements was not different from case 1 waters and the retrieval of Chl a was shown to be improved by red-ratio algorithms. For correct retrieval of CDOM from Medium Resolution Imaging Spectrometer (MERIS) data, a different CDOM slope over the Baltic region is required. The CDOM absorption slope, SCDOM, was significantly higher in the northwestern Baltic Sea: 0.018 (±0.002) compared to 0.016 (±0.005) for the RDS. Chl a-specific absorption and ad [SPM]*(442) and its spectral slope did not differ significantly. The comparison to the MERIS Reference Model Document (RMD) showed that the SNAP slope was generally much higher (0.011 ± 0.003) than in the RMD (0.0072 ± 0.00108), and that the SPM scattering slope was also higher (0.547 ± 0.188) vs. 0.4. The SPM-specific scattering was much higher (1.016 ± 0.326 m2 g−1) vs. 0.578 m2 g−1 in RMD. SPM retrieval could be improved by applying the local specific scattering. A novel method was implemented to derive the phase function (PF) from AC9 and VSF-3 data. b ˜ was calculated fitting a Fournier–Forand PF to the normalized VSF data. b ˜ was similar to Petzold, but the PF differed in the backwards direction. Some of the sIOPs showed a bimodal distribution, indicating different water types—e.g., coastal vs. open sea. This seems to be partially caused by the distribution of inorganic particles that fall out relatively close to the coast. In order to improve remote sensing retrieval from Baltic Sea data, one should apply different parameterization to these distinct water types, i.e., inner coastal waters that are more influenced by scattering of inorganic particles vs. open sea waters that are optically dominated by CDOM absorption.

Estimation of Chlorophyll-a Concentration from Optimizing a Semi-Analytical Algorithm in Productive Inland Waters

The high nutrient concentrations coming from non-point and point pollution have been linked to algae blooms, especially in hydroelectric plant reservoirs, due to higher residence time compared to rivers. The monitoring of algae is important to prevent risk of contamination by toxins in reservoirs used for drinking water supply. In this context, a physical model-based approach was adopted to retrieve chlorophyll-a (chl a) concentration, a photosynthetic pigment found in all phytoplankton species. We assumed that a semi-analytical algorithm parameterized to a eutrophic reservoir could also be applied to other eutrophic reservoirs, at least the specific inherent optical properties (SIOPs) are not similar. The parameterization was carried out based on Ocean and Land Color Instrument (OLCI) bands aboard Sentinel-3 spacecraft. In our study, the semi-analytical approach showed good performance in retrieving chl a content, with a normalized root mean square error (NRMSE) of 18.7%. The findings encourage the use of a unique semi-analytical algorithm in a reservoir cascade, where the impoundments present similar bio-optical status. The good performance of the algorithm indicates that this approach is rather useful in predicting trophic status in reservoirs.

Optical response associated with changing summer biogeochemical conditions in a turbid lake

Water quality degradation in inland water bodies during summer periods due to phytoplankton growth is a global problem. Lake Burley Griffin (LBG) in Canberra, Australia is an artificial, turbid, urban lake which is prone to water quality degradation in summer due to phytoplankton blooms. In Australia only limited (spatial, spectral and temporal) datasets are available that detail the full bio-optical condition of the water body during summer transformation processes. In this study, we conducted field campaigns in LBG to measure biogeochemical as well as inherent optical properties (IOP) during summer 2010 to understand the variability in the optical response. Optically active biogeochemical components such as total suspended solids (TSS), Chlorophyll- a (Chl- a ) and coloured dissolved organic matter (CDOM) varied over a wide range in response to changing environmental conditions during summer. The underwater optical environment was dominated by light scattering properties and the light absorption budget varied in response to changing CDOM and phytoplankton distributions. Specific inherent optical properties and spectral slopes of IOP observed here were different to other regional datasets, thus indicated the limitation in the extrapolation of optical models from other regions. Optical response as described by the scattering to absorption ratio and backscattering albedo showed that absorption due to CDOM and non-algal particulate matter (NAP) masked phytoplankton absorption features limiting the application of standard optical algorithms. A through description of bio-optical properties, relationships and their variability in response to changing summer biogeochemical conditions in a turbid optically complex lake is presented here.

Testing the performance of empirical remote sensing algorithms in the Baltic Sea waters with modelled and in situ reflectance data

Summary Remote sensing studies published up to now show that the performance of empirical (band-ratio type) algorithms in different parts of the Baltic Sea is highly variable. Best performing algorithms are different in the different regions of the Baltic Sea. Moreover, there is indication that the algorithms have to be seasonal as the optical properties of phytoplankton assemblages dominating in spring and summer are different. We modelled 15,600 reflectance spectra using HydroLight radiative transfer model to test 58 previously published empirical algorithms. 7200 of the spectra were modelled using specific inherent optical properties (SIOPs) of the open parts of the Baltic Sea in summer and 8400 with SIOPs of spring season. Concentration range of chlorophyll-a, coloured dissolved organic matter (CDOM) and suspended matter used in the model simulations were based on the actually measured values available in literature. For each optically active constituent we added one concentration below actually measured minimum and one concentration above the actually measured maximum value in order to test the performance of the algorithms in wider range. 77 in situ reflectance spectra from rocky (Sweden) and sandy (Estonia, Latvia) coastal areas were used to evaluate the performance of the algorithms also in coastal waters. Seasonal differences in the algorithm performance were confirmed but we found also algorithms that can be used in both spring and summer conditions. The algorithms that use bands available on OLCI, launched in February 2016, are highlighted as this sensor will be available for Baltic Sea monitoring for coming decades.

Spatial and temporal variations of the inherent optical properties in a tropical cascading reservoir system

In order to verify the effect of a cascade system in the water quality of two tropical reservoirs in Brazil, this work proposed to make use of the inherent optical properties (IOPs) as well as the specific inherent optical properties (SIOPs). From upstream to downstream, Barra Bonita (BB) is the first in a set of six reservoirs along Tiete River and Nova Avanhandava (Nav) is the fifth reservoir. BB is eutrophic whilst Nav is an oligotrophic environment. According to the IOP and SIOP analysis, it was possible to attest that BB was organic matter dominated and Nav was inorganic matter. These differences are noticeable in bio-optical modeling, must be considered different approaches to retrieve water quality parameters in both sites, once, the models take into account the specific information about the IOP and their relation with the optically active components (OACs) concentration. In addition, the results of this paper can provide comparable data to other water systems and improve the comprehension about the optical properties of complex water bodies.

Physical oceanographic processes influence bio-optical properties in the Tasman Sea

Remote sensing observations show optical signatures to conform to the physical oceanographic patterns in the Tasman Sea. To test the link between physical oceanographic processes and bio-optical properties we investigated an in situ bio-optical dataset collected in the Tasman Sea. Analysis of in situ observations showed the presence of four different water masses in the Tasman Sea, formed by the relatively warm and saline East Australia Current (EAC) water, a mesoscale cold core eddy on the continental slope, cooler Tasman Sea water on the shelf and river plume water. The distribution of suspended substances and their inherent optical properties in these water masses were distinctly different. Light absorption and attenuation budgets indicate varying optical complexity between the water masses. Specific inherent optical properties of suspended particulate and dissolved substances in each group were different as they were influenced by physical and biogeochemical processes specific to that water mass. Remote sensing reflectance signature varied in response to changing bio-optical properties between the water masses; thus providing the link between physical oceanographic processes, bio-optical properties and the optical signature. Findings presented here extend our knowledge of the Tasman Sea, its optical environment and the role of physical oceanographic processes in influencing the inherent optical properties and remote sensing signature in this complex oceanographic region.

Relation between inherent optical properties and land use and land cover across Gulf Coast estuaries

AbstractLand use and land cover (LULC) can affect the watershed exports of optically active constituents such as suspended particulate matter and colored dissolved organic matter, and in turn affect estuarine optical properties. We collected optical data from six estuaries in the northeastern Gulf of Mexico with different watershed LULC characteristics and investigated how estuarine optical properties varied across these systems. Differences in LULC corresponded with significant differences in the estuarine inherent optical properties and specific inherent optical properties (SIOPs), which are known surrogates for phytoplankton cell size, organic particle concentration, and the amount of terrigenous dissolved organic carbon. The results indicated that increasing proportions of developed land use (urban + agriculture) in the watersheds resulted in a linear increase in light attenuation in the estuaries primarily through increased absorption by phytoplankton. Estuarine SIOPs were also linearly related to the proportion of developed land. These findings were used to demonstrate how improved knowledge of the factors regulating estuarine SIOPs may be used to increase the accuracy of semianalytical ocean color remote sensing algorithms in optically complex estuaries.

Applying Spectral Unmixing to Determine Surface Water Parameters in a Mining Environment

Compared to natural waters, mine waters represent an extreme water type that is frequently heavily polluted. Although they have been traditionally monitored by in situ measurements of point samples taken at regular intervals, the emergence of a new generation of multispectral and hyperspectral (HS) sensors means that image spectroscopy has the potential to become a modern method for monitoring polluted surface waters. This paper describes an approach employing linear Spectral Unmixing (LSU) for analysis of hyperspectral image data to map the relative abundances of mine water components (dissolved Fe—Fediss, dissolved organic carbon—DOC, undissolved particles). The ground truth data (8 monitored ponds) were used to validate the results of spectral mapping. The same approach applied to HS data was tested using the image data resampled to WorldView2 (WV2) spectral resolution. A key aspect of the image data processing was to define the proper pure image end members for the fundamental water types. The highest correlations detected between the studied water parameters and the fractional images using the HyMap and the resampled WV2 data, respectively, were: dissolved Fe (R2 = 0.74 and R2vw2 = 0.6), undissolved particles (R2 = 0.57 and R2vw2 = 0.49) and DOC (R2 = 0.42 and R2vw2 < 0.40). These fractional images were further classified to create semi-quantitative maps. In conclusion, the classification still benefited from the higher spectral resolution of the HyMap data; however the WV2 reflectance data can be suitable for mapping specific inherent optical properties (SIOPs), which significantly differ from one another from an optical point of view (e.g., mineral suspension, dissolved Fe and phytoplankton), but it seems difficult to differentiate among diverse suspension particles, especially when the waters have more complex properties (e.g., mineral particles, DOC together with tripton or other particles, etc.).

Impact of an extreme flood event on optical and biogeochemical properties in a subtropical coastal periurban embayment (Eastern Australia)

AbstractMajor floods impacted the city of Brisbane, eastern Australia, in January 2011, delivering large amounts of dissolved and particulate materials and nutrients into the adjacent coastal embayment, Moreton Bay. The resulting spatially resolved changes in biogeochemical and optical properties in Moreton Bay were examined 1, 2, 6, 19, and 49 weeks after the main freshwater discharge. One week postflood, total suspended matter (TSM) and chlorophyll a (TChla) concentrations varied over 1 order of magnitude throughout Moreton Bay, the particle scattering coefficient at 555 nm varied by a factor of 20, and the total absorption coefficient and colored dissolved organic matter (CDOM) absorption coefficient at 440 nm varied by a factor of 5. The largest changes in biogeochemical and optical properties observed during our study were from 1 to 2 weeks after the floods: near the Brisbane River mouth, TSM decreased by a factor of 3, CDOM by a factor of 2, while TChla increased by a factor of 3. Within a year, optical and biogeochemical properties recovered to levels similar to nonflood conditions. The strong changes in the characteristics of the particulate and dissolved material following the flood event and subsequent biological and photochemical processes led to a large spatial and temporal variability in the relative contribution of different constituents to the total absorption coefficient at 440 nm, the particle single scattering albedo, and the specific inherent optical properties. This work has significant implications for the accuracy of standard ocean color remote sensing algorithms in coastal waters during flood events.

A Spectral-Unmixing Approach to Estimate Water–Mass Concentrations in Case 2 Waters

In this work, we study the estimation of water-quality parameters from the water-leaving reflectance by means of spectral unmixing. Our starting point is the provision of an analytic model relating the reflectance of water to its masses/bodies or constituents, as specified by their specific inherent optical properties (SIOP) and concentrations. The main objective is to reformulate the estimation of these concentrations as a spectral unmixing problem. We perform this by employing the linear mixing model (LMM), while suitably defining the endmembers (EMs) as representations of different water types dominated by one or more constituents. Each EM is then calculated by substituting the in situ-measured SIOP and combinations of utmost concentrations of each constituent into the water-reflectance model. Such use of unmixing practically enables to maintain an implicitly nonlinear relation between the water reflectance and constituents' concentrations, without resorting to the use of nonlinear mixing models. Furthermore, we present a method to automatically extract the EMs from the reflectance image. We validate the entire unmixing-based take using the state-of-the-art method as reference that inverts the water reflectance via comparisons (curve matching) with spectra from a lookup table. This validation is done using simulated data derived from the water-reflectance model and real hyperspectral data acquired over coastal waters of a shallow sea.

Specific inherent optical properties of highly turbid productive water for retrieval of water quality after optical classification

Assessments of specific inherent optical properties (SIOPs) and their variability in highly turbid and productive inland waters are essential for the accurate estimation of water quality. A new optical classification method including two classification criteria [i.e., normalized remote sensing reflectance slope (NS), and normalized remote sensing reflectance depth (ND)] was developed to divide remote sensing reflectance into four classes, i.e., class 1 (NS 0.21) is low turbid and high productive water; class 3 (NS > −0.0017 and ND −0.0017 and ND > 0.009) is high turbid and high productive water. The relationships between phytoplankton absorption at 440 nm [a ph(440)] and chlorophyll-a concentration [C chla] as well as between particle backscattering coefficient at 440 nm [b bp(440)] and total suspended matter concentration (C TSM) after classification were obtained from a large number of in situ data in Lake Taihu. The measured specific phytoplankton absorption $$[ {a_{\text{ph}}^{*} \left( \lambda \right)} ]$$ and particle backscattering coefficient $$[ {b_{\text{bp}}^{*} \left( \lambda \right)} ]$$ show significant variations even within the same class. The mean values of $$a_{\text{ph}}^{*} \left( \lambda \right)$$ at 440 nm $$[ {a_{\text{ph}}^{*} \left( {440} \right)} ]$$ for each class are 0.048 ± 0.013, 0.060 ± 0.012, 0.083 ± 0.021, and 0.056 ± 0.017 m2/mg, respectively. The mean values of $$b_{\text{bp}}^{*} \left( \lambda \right)$$ at 440 nm $$[ {b_{\text{bp}}^{*} \left( {440} \right)} ]$$ for each class are 0.035 ± 0.01, 0.024 ± 0.004, 0.041 ± 0.009, and 0.038 ± 0.009 m2/g, respectively. The power functions of SIOPs and water constituents’ concentration indicate that $$a_{\text{ph}}^{*} \left( {440} \right)$$ and $$b_{\text{bp}}^{*} \left( {440} \right)$$ vary with C chla and C TSM. The validation results show that our proposed values for $$a_{\text{ph}}^{*} \left( {440} \right)$$ and $$b_{\text{bp}}^{*} \left( {440} \right)$$ cover a very wide range of water optical properties, which are characterized from clear water to highly turbid productive water. The validation results also suggest that the retrieval accuracy of C chla and C TSM bio-optical model was improved after classification. The root mean square error (RMSE) of C chla was improved from 14.18 to 7.43 μg/L (mean value of all classes) and RMSE of C TSM was improved from 32.98 to 26.10 mg/L (mean value of all classes). Thus, the temporal and spatial variation of $$a_{\text{ph}}^{*} \left( {440} \right)$$ and $$b_{\text{bp}}^{*} \left( {440} \right)$$ should be considered in the bio-optical retrieval model of water quality. In complex optical properties of inland water, retrieving the water constituents with high accuracy needs to classify the water optical properties from the remote sensing spectrum by optical classification method. The figure shows the water color examples of each class .

Retrieving total suspended matter in Lake Taihu from HJ-CCD near-infrared band data

Among water quality parameters, total suspended matter is important for the evaluation of inland waters. A recently launched satellite sensor, HJ-CCD, by China possesses high temporal resolution, medium spatial resolution, and wide swath, so it is convenient for monitoring this parameter in large inland waters. However, no operational method currently exists for retrieving the total suspended matter concentration of turbid inland waters from HJ-CCD data. Using Lake Taihu in Eastern China as a study area, we obtained and analyzed optical properties of the lake during all seasons, and found that the absorption coefficient of suspended matter, chlorophyll, and colored dissolved organic matter of the near-infrared band may approximate zero. Based on this analysis, we found that a single band method of retrieving concentration using the near-infrared band was suitable using HJ-CCD data. We parameterized the single band method with specific inherent optical properties of Lake Taihu, and validated it using the results retrieved from a HJ-CCD image taken on 14 March 2009, as well as water-surface quasi-synchronous measured data. The concentration retrieved from the image is precise and stable; the single band method uses the established specific optical property database in the study area for input parameters, and does not need support from synchronous data. With this method, HJ-CCD may be applied to retrieve total suspended matter of other highly turbid inland waters.

Remote sensing of particulate absorption coefficients and their biogeochemical interpretation: A case study in the Irish Sea

We propose a method for (i) obtaining particulate absorption coefficients from optical remote sensing reflectance signals and (ii) partitioning these coefficients into separate components for phytoplankton cells and mineral particles. This method makes the initial assumption that absorption by coloured dissolved organic matter (CDOM) in the region of interest is either constant, or so low that its variability can be neglected. It uses a slightly modified version of the Quasi-Analytical Algorithm (Lee et al., 2009) to recover the non-water absorption (anw) and particulate backscattering (bbp) coefficients, and then obtains an estimate of absorption by CDOM, and the backscattering to absorption ratios for minerals and phytoplankton, by fitting upper and lower boundaries to the resulting data cluster. These ratios are employed in linear un-mixing equations to resolve the contributions of phytoplankton and minerals to the particulate absorption coefficient. The performance of the method was evaluated using reflectance spectra generated by an optical model of the Irish Sea which incorporated realistic specific inherent optical properties and distributions of constituent concentrations. It was then used to recover absorption coefficients for phytoplankton and suspended minerals in the 488nm waveband from MODIS remote sensing data for the central Irish Sea for the period May 2005–November 2012. The partitioned coefficients showed strong seasonality, with suspended mineral absorption peaking in winter and phytoplankton absorption becoming dominant in spring and summer. By employing locally determined specific inherent optical properties, it was possible to estimate the average annual cycles in the concentrations of the two constituents. These cycles proved to be consistent with previously published models of particle dynamics in the region in which mineral concentrations are elevated by winter mixing and increasing water column stability in spring is followed by a period of phytoplankton growth. We conclude that it is possible to resolve the separate contributions of phytoplankton and minerals to particulate absorption in waters where these constituents are the dominant determinants of optical variability, and that the partitioned absorption coefficients can provide valuable insights into the dynamics of biogenic and minerogenic particles in shelf sea ecosystems.

Operational multi-sensor monitoring of turbidity for the entire Mekong Delta

An operational satellite-based approach was implemented to monitor turbidity and organic absorption in the Mekong river system. Using physics-based algorithms linked together in a fully automated processing chain, more than 300 Landsat Enhanced Thematic Mapper (ETM) scenes and 1000 MODIS scenes, representing five years of data, were used to produce standardized, quantitative time series of turbidity and organic absorption across Vietnam, Thailand, Cambodia, Laos, and China. To set up this system, the specific inherent optical properties (SIOPs) of the Mekong river system were determined through three separate field campaigns, laboratory analysis, and subsequent optical closure calculations. Following this, a range of satellite data types was tested using the derived Mekong-specific inherent optical properties, including Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m data, Landsat ETM, Medium Resolution Imaging Spectrometer (MERIS), Satellite Pour l’Observation de la Terre (SPOT) 5, RapidEye, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and QuickBird. The satellite-based turbidity estimates were coincident with available field data, and comparisons showed them to be in good agreement. Overall, the derived SIOPs were suitable for water-quality monitoring of the Mekong, and the MODIS, MERIS, Landsat, and RapidEye sensors were found to be the most radiometrically stable and thereby suitable for ongoing operational processing. The implemented system delivers consistent results across the different satellite sensors and over time, but is limited to where the spatial resolution of the sensor is still able to resolve the river width. The system is currently applicable for the entire Mekong river system, both for near-real-time monitoring and for analysis of historical data archive.

Remote sensing of shelf sea optical properties: Evaluation of a quasi-analytical approach for the Irish Sea

A quasi-analytical approach to deriving the coefficients of absorption, a(λ), backscattering, bb(λ), and the attenuation of planar irradiance, Kd(λ), from sub-surface remote sensing reflectance, rrs(λ), was investigated for the optically complex (Case 2) waters of the Irish Sea. The algorithms of Lee et al. (2005b, Journal of Geophysical Research Oceans, 110, C02017) were tuned for this region using radiative transfer calculations which incorporated locally determined specific inherent optical properties and constituent concentrations. The optimised algorithms were then applied to rrs spectra derived from profiling radiometry for 145 stations in the Irish Sea and adjacent waters, and their outputs compared with inherent optical property measurements for these stations. For the modelled data, recoveries of, a(λ), bb(λ) and Kd(λ) in six wavebands between 412nm and 667nm had mean percentage errors below 3% and standard deviations of around 6%. For in situ data, the algorithms tended to over-estimate a(λ) and under estimate bb(λ) relative to measured values, but a contributing factor could be the difficulty of measuring optical properties accurately in turbid waters. Retrieved values of Kd(λ) were highly correlated with those measured in situ, with regression slopes in the best-performing bands of 1.05 at 442nm (r2=0.91) and 0.92 at 488nm (r2=0.96). Three previously published relationships between satellite-derived optical properties at 490nm and euphotic depth, z1%PAR, produced roughly equivalent results with root mean square percentage errors, relative to in situ measurements, of around 20%. On the logarithmic scales usually employed in remote sensing, values of a(488), bb(488), Kd(488) and z1%PAR recovered using the optimised algorithms bore strong linear relationships to in situ measurements, with least square regression slopes in the range 0.89 to 1.03 and r2 values from 0.87 to 0.94. Application of these algorithms to a MODIS image of the Irish Sea in early summer (25th May 2013) revealed marked spatial variations in optical properties which were well correlated with known patterns of tidal stirring in the region.

Characterizing the Absorption Properties for Remote Sensing of Three Small Optically-Diverse South African Reservoirs

Characterizing the specific inherent optical properties (SIOPs) of water constituents is fundamental to remote sensing applications. Therefore, this paper presents the absorption properties of phytoplankton, gelbstoff and tripton for three small, optically-diverse South African inland waters. The three reservoirs, Hartbeespoort, Loskop and Theewaterskloof, are challenging for remote sensing, due to differences in phytoplankton assemblage and the considerable range of constituent concentrations. Relationships between the absorption properties and biogeophysical parameters, chlorophyll-a (chl-a), TChl (chl-a plus phaeopigments), seston, minerals and tripton, are established. The value determined for the mass-specific tripton absorption coefficient at 442 nm, a∗ (442), ranges from 0.024 to 0.263 m2·g−1. The value of the TChl-specific phytoplankton absorption coefficient (a∗ ) was strongly influenced by phytoplankton species, size, accessory pigmentation and biomass. a∗ (440) ranged from 0.056 to 0.018 m2·mg−1 in oligotrophic to hypertrophic waters. The positive relationship between cell size and trophic state observed in open ocean waters was violated by significant small cyanobacterial populations. The phycocyanin-specific phytoplankton absorption at 620 nm, a∗ (620), was determined as 0.007 m2·g−1 in a M. aeruginosa bloom. Chl-a was a better indicator of phytoplankton biomass than phycocyanin (PC) in surface scums, due to reduced accessory pigment production. Absorption budgets demonstrate that monospecific blooms of M. aeruginosa and C. hirundinella may be treated as “cultures”, removing some complexities for remote sensing applications. These results contribute toward a better understanding of IOPs and remote sensing applications in hypertrophic inland waters. However, the majority of the water is optically complex, requiring the usage of all the SIOPs derived here for remote sensing applications. The SIOPs may be used for developing remote sensing algorithms for the detection of biogeophysical parameters, including chl-a, suspended matter, tripton and gelbstoff, and in advanced remote sensing studies for phytoplankton type detection.

Specific absorption and backscattering coefficients of the main water constituents in Poyang Lake, China

Obtaining and analyzing the specific inherent optical properties (SIOPs) of water bodies is necessary for bio-optical model development and remote sensing-based water quality retrievals and, further, for related ecological studies of aquatic ecosystems. This study aimed to measure and analyze the specific absorption and backscattering coefficients of the main water constituents in Poyang Lake, China. The specific absorption and/or backscattering coefficients of the main water constituents at 85 sampling sites (47 in 2010 and 38 in 2011) were measured and analyzed as follows: (1) the concentrations of chlorophyll a (C(CHL)), suspended particulate matter (C(SPM)) (including suspended particulate inorganic matter (C(SPIM)) and suspended particulate organic matter (C(SPOM))), and the absorption coefficients of total particulate (a(p)), phytoplankton (a(ph)), and non-pigment particulate (a(d)) were measured in the laboratory; (2) the total backscattering coefficients at six wavelengths of 420, 442, 470, 510, 590, and 700 nm, including the contribution of pure water, were measured in the field with a HydroScat-6 backscattering sensor, and the backscattering coefficients without the contribution of pure water (b(b)) were then derived by subtracting the backscattering coefficients of pure water from the total backscattering coefficients; (3) the specific absorption coefficients of total particulate (a*(p)), phytoplankton (a(ph)*), and non-pigment particulate (a*(d)) were calculated by dividing a(p), a(ph), and ad by C(SPM), C(CHL), and C(SPIM), respectively, while the specific backscattering coefficients of total suspended particulate matter (b*(b)) were calculated by dividing b(b) by CSPM; and (4) the a(ph)*, a*(d), a*(p) and b*(b) of the remaining samples (46 in 2010 and 36 in 2011) were visualized and analyzed, and their relations to CCHL, CSPIM or CSPM were studied, respectively. The main results are summarized as follows: (1) the a(ph)* values at 440 nm were 0.0367-0.7203 m(2) mg(-1) with a mean of 0.1623 ± 0.1426 m(2) mg(-1) in 2010 and 0.0319-0.7735 m(2) mg(-1) with a mean of 0.3145 ± 0.1961 m(2) mg(-1) in 2011; there existed significant, negative, and moderate correlations between a(ph)* and C(CHL) at 400-700 nm in 2010 and 2011 (p<0.05); (2) The a*(d) values at 440 nm were 0.0672-0.2043 m(2) g(-1) with a mean of 0.1022 ± 0.0326 m(2) g-1) in 2010 and 0.0559-0.1347 m(2) g(-1) with a mean of 0.0953 ± 0.0196 m(2) g(-1) in 2011; there existed negative correlations between a*(d) and C(SPIM), while the correlations showed overall decreasing and increasing trends before and after around 575 nm with increasing wavelengths, respectively; (3) The a*(p) values at 440 nm were 0.0690-0.1929 m(2) g(-1) with a mean of 0.1036 ± 0.0298 m(2) g(-1) in 2010 and 0.0571-0.1321 m(2) g(-1) with a mean of 0.1014 ± 0.0191 m(2) g(-1) in 2011, and the negative correlations between a*(p) and C(SPM) were found in both years; (4) The b*(b) at the six wavelengths generally decreased with increasing wavelengths, while the b*(b) values at 420 nm were lower than those at 442 nm for some samples; the correlation between b*(b) and C(SPM) increased with increasing wavelength. Such results can only represent the SIOPs during the sampling time periods, and more measurements and analyses considering different seasons need to be carried out in the future to comprehensively understand the SIOPs of Poyang Lake.