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Barataria Basin, a deltaic marsh-estuary system in the northern Gulf of Mexico (nGOM), is an important source of dissolved organic matter (DOM) to the coastal ecosystem. To assess DOM dynamics, monthly measurements of dissolved organic carbon (DOC) concentrations and colored DOM (CDOM; an optical proxy for DOC) absorption were obtained over a three-year period (2008–2011) along a transect encompassing the upper, middle and lower regions of the Barataria Basin estuary. While CDOM absorption coefficient at 355 nm (a g 355) generally decreased and spectral slope at 275–295 nm (S 275–295) increased along the transect from the upper to lower basin, deviations were observed associated with hydrologic and meteorological influences. An application of wavelet analysis to the time-series of a g 355 and various freshwater sources revealed a spatiotemporal resonance of a g 355 with freshwater input from the Mississippi River (MR), the controlled freshwater discharge from the Davis Pond freshwater diversion, and rainfall in the lower, middle and upper basins, respectively. Field measurements and Landsat/MODIS data spanning across different seasons between 2008 and 2011 were used to develop optimized a g 355 empirical algorithms for the high river flow, cold front, and normal conditions. Power law models relating a band ratio (green/red) of a satellite sensor to a g 355 showed good performance for the MODIS-Aqua (R2~0.81–0.83, N = 581) and Landsat-5 TM (R2~0.72–0.79, N = 304) imagery. a g 355-DOC relationships (R2~0.77–0.84, N = 306) applied to historical Landsat-5 TM (1985–2011) and MODIS-Aqua imagery (2002−2012) showed strong environmental influences on multi-decadal CDOM and DOC spatiotemporal trends. Satellite-derived DOC agreed reasonably well with in-situ measured DOC (averaged R2 = 0.71; RMSE = 2.13). While the time-series DOC showed seasonality and decreasing gradients from the upper to lower basin, an overall increase in DOC was observed in the upper and middle basins from 1985 to 2012. However, in the lower basin, DOC increased from 1985 to 2006 but decreased from 2007 to 2012, likely due to the impact of two major hurricanes in 2005. Furthermore, relationships between satellite-derived DOC and land cover variations (1985–2011) along the wetland-estuary interfaces derived from Landsat-5 TM supervised classification showed an increase in DOC with corresponding increase in developed area in the upper basin, while in the lower basin, DOC increased by 41% (R2 = 0.54) between 1985 and 2006 corresponding to a 17% decrease in salt marsh area, suggesting strong land use/land loss impact on the long-term DOC trends in Barataria Basin. • Landsat/MODIS-based CDOM empirical algorithm is presented for Barataria Basin. • Distributions of a g 355 and DOC were examined in conjunction with forcing factors. • Environmental influences on multi-decadal CDOM and DOC spatiotemporal trends. • Strong land use/land loss impact on long-term DOC trends in Barataria Basin. [ABSTRACT FROM AUTHOR]

Abstract Bottom reflectance is often the main cause of high uncertainty in Colored Dissolved Organic Matter (CDOM) estimation for optically shallow waters. This study presents a Landsat-8 based Shallow Water Bio-optical Properties (SBOP) algorithm to overcome bottom effects so as to successfully observe spatial and temporal CDOM dynamics in inland waters. We evaluated the algorithm via 58 images and a large set of field measurements collected across seasons of multiple years in the Saginaw Bay, Lake Huron. Results showed that the SBOP algorithm reduced estimation errors by as much as 4 times (RMSE = 0.17 and R 2 = 0.87 in the Saginaw Bay) when compared to the QAA-CDOM algorithm that did not take into account bottom reflectance. These improvements in CDOM estimation are consistent and robust across broad range CDOM absorption. Our analysis revealed: 1) the proposed remote sensing algorithm resulted in significant improvements in tracing spatial-temporal CDOM inputs from terrestrial environments to lakes, 2) CDOM distribution captured with high resolution land-viewing satellite is useful in revealing the impacts of terrestrial ecosystems on the aquatic environment, and 3) Landsat-8 OLI, with its 16 days revisit time, provides valuable time series data for studying CDOM seasonal variations at land-water interface and has the potential to reveal its relationship to adjacent terrestrial biogeography and hydrology. The study presents a shallow water algorithm for studying freshwater or coastal ecology, as well as carbon cycling science. Highlights • A semi-analytical CDOM retrieval algorithm SBOP is presented based on Landsat-8. • SBOP developed for shallow waters allows high resolution mapping of CDOM gradients. • Snowmelt in early spring peaks CDOM export from land to lakes in annual cycle. • Biogeography and hydrology drives lake CDOM spatio-temporal variation. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon, DOC, and the colored component of dissolved organic matter, CDOM, are key indicators of coastal water quality and biogeochemical state. Yet applications of space-based remote sensing to monitoring of CDOM variability across estuarine ecosystems and assessment of DOC exchanges along highly dynamic terrestrial-aquatic interfaces have been scarce, in part due to the coarse spatial resolution of most existing ocean color sensors and the seasonal and regional dependence of most existing algorithms. Here, we used a rich dataset of field observations to develop and validate new CDOM and DOC algorithms that are broadly applicable to different estuarine and coastal regions, over different seasons and a wide range of in-water conditions. Algorithms were applied to satellite imagery from MERIS-Envisat at a spatial resolution (300 m) that can resolve much of the spatial variability that characterizes estuaries and their margins. Multi-spectral remote sensing reflectance ( R rs ) was used to retrieve CDOM absorption at various wavelengths and CDOM absorption spectral slope in the 275–295 nm spectral range ( S 275–295 ). DOC concentrations were obtained from a tight relationship between the DOC-specific CDOM absorption and S 275–295, two optical quantities that depend only on the quality of CDOM and strongly covary across spatial and temporal scales. Algorithm evaluation using MERIS satellite data across different estuarine and coastal environments (i.e., the northern Gulf of Mexico, the Delaware Bay, the Chesapeake Bay estuary, and the Middle Atlantic Bight coastal waters) and across different seasons over multiple years resulted in relative errors (mean absolute percent difference; MAPD) of 29% ( N = 17), 9.5% ( N = 14), and 18% ( N = 32), for a CDOM (300), S 275–295 , and DOC, respectively. These relative errors are comparable to those previously reported for satellite retrievals of CDOM and DOC products in less optically complex offshore waters. Application of these algorithms to multi-year MERIS satellite imagery over the Chesapeake Bay estuary allowed, for the first time, to capture the impact of tidal exchanges on carbon dynamics along wetland-estuary interfaces, and resolved spatial gradients, seasonal variability, and year-to-year changes in estuarine carbon amount and quality associated with marsh carbon export, riverine inputs, and extreme precipitation events. [ABSTRACT FROM AUTHOR]

Light absorption of the colored fraction of dissolved organic matter (CDOM) is a dominant optical component of the Arctic Ocean (AO). Here we show Pan-Arctic characteristics of CDOM light absorption for various Arctic regions covering both coastal and oceanic waters during the Tara Oceans Polar Circle expedition. The Siberian (or eastern) side of the AO is characterized by higher CDOM absorption values compared to the North American (or western) side. This is due to the difference in watersheds between the eastern and western sides of the AO and is consistent with an Arctic absorption database recently built by Matsuoka et al. (2014). A direct comparison between in situ and satellite data demonstrates that CDOM absorption is derived Arctic-wide from satellite ocean color data with an average uncertainty of 12% (root mean square error of 0.3 m − 1 ) using our previously published algorithm. For river-influenced coastal waters, we found a single and highly significant relationship between concentrations of dissolved organic carbon (DOC) and CDOM absorption ( r 2 > 0.94) covering major Arctic river mouths. By applying this in situ relationship to satellite-derived CDOM absorption, DOC concentrations in the surface waters are estimated for river-influenced coastal waters with an average uncertainty of 28%. Implications for the monitoring of DOC concentrations in Arctic coastal waters are discussed. [ABSTRACT FROM AUTHOR]

Remote sensing has mainly relied on measurements of scalar radiance and its spectral and angular features to retrieve micro- and macro-physical properties of aerosols/hydrosols. However, it is recognized that measurements that include the polarimetric characteristics of light provide more intrinsic information about particulate scattering. To take advantage of this, we used vector radiative transfer (VRT) simulations and developed an analytical relationship to retrieve the macro and micro-physical properties of the oceanic hydrosols. Specifically, we investigated the relationship between the observed degree of linear polarization (DoLP) and the ratio of attenuation-to-absorption coefficients ( c / a ) in water, from which the scattering coefficient can be readily computed ( b = c − a ), after retrieving a . This relationship was parameterized for various scattering geometries, including sensor zenith/azimuth angles relative to the Sun's principal plane, and for varying Sun zenith angles. An inversion method was also developed for the retrieval of the microphysical properties of hydrosols, such as the bulk refractive index and the particle size distribution. The DoLP vs c / a relationship was tested and validated against in-situ measurements of underwater light polarization obtained by a custom-built polarimeter and measurements of the coefficients a and c , obtained using an in-water WET Labs ac-s instrument package. These measurements confirmed the validity of the approach, with retrievals of attenuation coefficients showing a high coefficient of determination depending on the wavelength. We also performed a sensitivity analysis of the DoLP at the Top of Atmosphere (TOA) over coastal waters showing the possibility of polarimetric remote sensing application for ocean color. [ABSTRACT FROM AUTHOR]

Issues like monitoring lake water quality, studying the role of lakes in the global carbon cycle or the response of lakes to global change require data more frequently and/or over much larger areas than the in situ water quality monitoring networks can provide. The aim of our study was to investigate whether it is feasible to estimate different lake carbon fractions (CDOM, DOC, TOC, DIC, TIC and pCO 2 ) from space using sensors like OLCI on future Sentinel 3. In situ measurements were carried out in eight measuring stations in two Swedish lakes within 2 days of MERIS overpass. The results suggest that the MERIS CDOM product was not suitable for estimating CDOM in lakes Mälaren and Tämnaren and was not a good proxy for mapping lake DOC and TOC from space. However, a simple green to red band ratio and some other MERIS products like the total absorption coefficient, turbidity index, suspended matter and chlorophyll-a were correlated with different carbon fractions and could potentially be used as proxies to map these lake carbon fractions (CDOM, DOC, TOC, DIC, TIC and pCO 2 ) from space. [ABSTRACT FROM AUTHOR]

A combination of new measurements and analysis of historical data from several geographic regions was used to address four issues that affect the reliability and interpretation of colored dissolved organic matter (CDOM) measured by remote sensing of inland waters. First, high variability of CDOM levels in lakes and rivers was found at seasonal and multi-year time scales and at shorter intervals in some rivers and lakes. Coefficients of variation (CVs) of 30%–50% for absorptivity at 440 nm ( a 440 ) were common in historical and new data sets we examined. CDOM values used to calibrate imagery thus should be measured close to the image acquisition date, preferably within 1–2 months in lakes and a few days in large rivers, unless it can be shown that CDOM levels are temporally stable over longer (or shorter) time periods in a given aquatic system. Second, spectral slopes ( S ) for CDOM in the visible range vary little over time (even over multi-year periods) within sites. Substantial variation was found between sites, however, and most spectra showed a change in slope near 460 nm. Values of S 400–460 for waters with moderate to high CDOM levels generally were within a narrow range (~ 0.014–0.018) and similar to reported S values in the near UV. Values of S 400–460 for waters with low CDOM generally were smaller and more variable, as were values for S 460–650 for all waters. Overall, the variability of spectral slopes in the visible range should not have a large effect on the reliability of a 440 estimates made from remote sensing, which in many models involve reflectance measurements at wavelengths > 500 nm. Third, although a strong correlation (r 2 = 0.925) was found between CDOM levels and DOC concentrations in 34 surface waters sampled in 2013, the standard error of estimate suggests an uncertainty of ~ ± 20% in predicting DOC at a 440 = 5 m − 1 (a moderate CDOM level). Moreover, CDOM–DOC relationships for unpublished data sets we analyzed and those reported in the literature indicate that both the fraction of DOC that is colored and slopes of regressions between CDOM and DOC are highly variable in space and time. Prediction of DOC concentrations in water bodies from CDOM levels (whether measured in the laboratory or by remote sensing) thus is associated with considerable uncertainty. For the present, this implies that field sampling is required to verify DOC concentrations predicted from remotely sensed CDOM measurements until we have a better understanding of variations in DOC–CDOM relationships. Fourth, shapes of reflectance spectra for CDOM-rich waters varied greatly depending on the concentrations of other constituents (suspended solids and chlorophyll) that affect the optical properties of water. Nonetheless, it is not obvious from our results for several predictive models that different remote sensing algorithms are needed to calculate CDOM levels accurately for waters where CDOM is the only variable affecting reflectance versus waters where other constituents also affect the spectra. The best band or band ratio models for simulated Landsat 8, Sentinel-2 and Sentinel-3 bands from field measured reflectance spectra yielded high r 2 values (0.84–0.86) for a 440 . The broader Landsat 8 bands worked nearly as well for a 440 as the narrower Sentinel band sets and hyperspectral bands, probably because CDOM is characterized by a broad exponential increase in absorbance with decreasing wavelength rather than specific peaks or troughs in absorbance or reflectance. [ABSTRACT FROM AUTHOR]

There is a strong need to develop remote sensing methods for mapping lake carbon content on regional to global scales. The use of in situ methods is impractical for monitoring lake water quality over large geographical areas, which is a fundamental requirement to understand the true role of lakes in the global carbon cycle. The coloured component of dissolved organic carbon (DOC), called CDOM, absorbs light strongly in the blue part of the visible spectrum and can be used as a proxy for mapping lake DOC with remote sensing. However, iron associated to organic matter can cause extra browning of waters. Consequently, the remote sensing signal we interpret as DOC may partially be attributed to the presence of iron associated to organic matter, potentially hampering our ability to estimate carbon concentrations. A thorough analysis of biogeochemical parameters was carried out on Lake Mälaren on August 23, 2010, and a MERIS full resolution image was acquired simultaneously. MERIS standard, Case 2 Regional, and Boreal processors were used to calculate remote sensing products, which were compared with different lake water characteristics. The carbon to iron ratio was different from the rest of the lake in one of the basins. MERIS standard and Case 2 Regional processors were sensitive to this difference as the correlation between MERIS CDOM product and DOC was low (R 2 = 0.43) for all sampling stations and increased to 0.92 when the one basin was excluded. The Boreal Lakes processor results were less disturbed by the different carbon–iron ratios found in one basin and produced reasonably good results (R 2 = 0.65). We found MERIS products (e.g. total absorption) that provided good correlation (R 2 = 0.80) with DOC-specific absorbance at 254 nm, called SUVA, which is a metric commonly used to assess drinking water treatability. However, none of the MERIS products were suitable for mapping the total organic carbon in Lake Mälaren. MERIS total suspended matter product was a good (R 2 = 0.73) proxy for particulate iron, meaning that the particulate iron content in Mälaren can be mapped from space. [ABSTRACT FROM AUTHOR]

Recent and upcoming launches of new satellite sensors will provide the spatial, spectral and radiometric resolution to globally assess freshwater chromophoric dissolved organic matter (CDOM), and thus estimate dissolved organic carbon (DOC) concentration. However, estimating DOC from optical remote sensing requires a robust relationship between CDOM and DOC. This is particularly problematic for reservoirs because they have variable dissolved organic matter composition that complicates the CDOM–DOC relationship. We investigated six manmade reservoirs along a temperate to tropical gradient that represent a range of reservoir types and watershed conditions to determine whether a linear relation between CDOM and DOC could be established. We measured CDOM absorption and DOC concentration during the wet and dry seasons in the six reservoirs. We found the CDOM absorption coefficient and CDOM spectral slope were uncorrelated due to exogenous DOC inputs from multiple sources. Alone, the absorption coefficient of CDOM was a poor predictor of DOC concentration. Including both CDOM absorption coefficient and spectral slope in a multiple regression accounted for both composition and concentration, significantly improving the regression r 2 . By using both CDOM absorption coefficient and spectral slope, we identify a framework for a potential solution to overcome the influence of dissolved organic matter source and transformation history on the CDOM–DOC relationship. We conclude that local variability, seasonality and optical complexity should be considered in remote sensing based approaches for global freshwater DOC estimation. [ABSTRACT FROM AUTHOR]

Abstract: This study evaluated fifteen algorithms representing four major categories of retrieval algorithms for aquatic colored dissolved organic matter (CDOM): empirical, semi-analytical, optimization, and matrix inversion methods. The specific goal here was to evaluate (and understand) the strengths and limits of these algorithms in predicting CDOM dynamics along a gradient of varying water quality in a large, freshwater ecosystem. The data were collected in May and October of 2012 from the estuarine areas of the Kawkawlin and Saginaw Rivers, and Lake Huron. Algorithms were evaluated through comparisons to in-situ CDOM measurements, such that the analysis of these field measurements showed that CDOM levels in these areas displayed a range of CDOM absorption coefficients aCDOM (440) (0.1–8.5m−1). In general, the majority of the algorithms underestimated high CDOM waters (aCDOM (440)>2m−1) and overestimated low CDOM scenarios (<0.5m−1). Six algorithms that performed consistently better compared with the other models (overall RMSE of <0.45) in estimating in-situ CDOM levels were three empirical, two semi-analytical, and one MIM algorithms. Our analysis identified a set of parameters for the matrix inversion methods (MIM) that allow them to work effectively across a broad range of CDOM levels. Analysis of our results indicated that the most effective wavelengths/band locations for estimating CDOM could vary depending on the levels of spectral interference from high concentrations of particulate matter in the water column. In addition, our results suggest that including wavelengths>600nm in the algorithms improves CDOM estimation accuracy significantly, particularly for complex freshwater environments. [Copyright &y& Elsevier]

Abstract: Underwater light characteristics (quality and quantity) are important drivers of many ecological processes in aquatic systems. However, the mechanisms driving the underwater light climate in large rivers are poorly understood due to the complex interactions among color-producing agents (CPAs), which can vary in space and time. A compelling example of such a complex interaction among CPAs concerns the St. Lawrence River, where chromophoric dissolved organic matter and suspended inorganic particulate matter interact to structure the underwater spectral environment. Because such interactions can be complex, the combined net effect of CPAs on water color is not intuitive and remains to be evaluated. To resolve the spatial and temporal dynamics of the spectral profile in the St. Lawrence River, we analyzed a series of 44 Landsat 5 and 7 images, distributed between 1984 and 2009, which cover the main freshwater section of the river. Rather than following linear trends along the longitudinal axis, the spectral profiles on spectral bands (blue, green and red) presented three distinctive spatial patterns. We argue that matter injected by tributaries and discontinuous zones of the river strongly impacts water color by modulating the balance among CPAs. We also clearly demonstrate a marked trend between 1984 and 2009 toward decreasing reflectance values on bands 1, 2 and 3, presumably in response to changes in land use in the surrounding watershed. [Copyright &y& Elsevier]

Abstract: Absorption of ultraviolet radiation (UV, 280–400nm) by chromophoric dissolved organic matter (CDOM) precedes a host of light-sensitized surface ocean processes relevant to global climate. These include photo- and biogeochemical cycling of organic material, release of sulfur and carbon-containing gases to the atmosphere, and the photoprotection of marine microorganisms. Synoptic CDOM absorption data in the UV is highly desired yet difficult to estimate by satellite methods as the atmosphere interferes with direct detection of water-leaving UV radiance. The absorption spectrum of CDOM is typically modeled as an exponential function in which a spectral slope parameter, S, describes the rate of decrease in absorption with increase in wavelength. Significant functional relationships are observed in aquatic environments between S and the CDOM absorption coefficient at 443nm, a CDOM(443). In this paper, we use a large, systematic dataset of spectroscopic CDOM measurements from the U.S. CO2/CLIVAR Repeat Hydrography Survey to examine the relationship between S and a CDOM(443) as a means to model a CDOM(λ) in the UV from ocean color. Our resultant model predicts a CDOM(λ) at wavelengths from 325 to 412nm from the absorption coefficient of colored dissolved and detrital materials (CDM) at 443nm, a CDM(443), retrieved by an existing semi-analytical ocean color algorithm. Expected agreement (near 1:1) with the training dataset was achieved (r2 =0.71–0.85, p=0, n=127). Considering inherent satellite data uncertainties as well as the model's limitations in regions with potential terrestrial influence, good correspondence between modeled and in situ values was observed during independent validation with open ocean CDOM data, such as from BIOSOPE (r2 =0.77–0.85, p<0.05, n=29). The model has immediate application in global scale assessments of photochemical rate processes and CDOM cycling in the open ocean due to its simplicity and optimization using a large base of field data (>7500 samples) from diverse Case I waters. [Copyright &y& Elsevier]

Abstract: Establishing a link between the optical and biogeochemical properties of near-shore waters continues to be a challenge for both riverine and estuarine areas worldwide due to terrestrial influences. This study aimed to evaluate the effectiveness of an inversion algorithm for the extraction of riverine and estuarine CDOM properties at global scales. Our CDOM evaluation focused on five aspects: 1) the range of worldwide CDOM levels, 2) spatial distribution patterns, (3) climatic influences, (4) influences of land cover change, and (5) seasonal effects. The study locations consisted of the estuarine and coastal regions of 10 major rivers spread across five continents. Our approach was to examine the QAA-CDOM algorithm by extracting CDOM properties from hundreds of EO-1 Hyperion images acquired during the last decade (2001–2011). Preliminary results showed that CDOM absorption coefficients at 440nm within the 10 selected rivers exhibited a broad range (0.02–7.2m−1). Spatial CDOM distribution patterns showed many plumes dispersing from source areas (e.g. adjacent terrestrial vegetated areas) along the direction of flow. Seasonal variations in CDOM levels are also evident (i.e. 0.5–4.0m−1) as illustrated by the January, April, August and October images of the Volga River. CDOM levels also appeared to trend upward with the increase in forest coverage (i.e. terrestrial influence) within the watersheds studied over the last decade. Our results strongly suggest that the algorithm is effective in distinguishing riverine and estuarine CDOM levels affected by factors such as global biogeography, climate conditions and regional land surface processes. [Copyright &y& Elsevier]

Abstract: In this paper we develop a neural network (NN) algorithm for retrieving inherent optical properties (IOP) from above water remote sensing reflectances (Rrs) at available MODIS (or similar satellite) wavelengths. In previous work we used Hydrolight5 simulations of Rrs with widely varying globally representative constituent physical parameters as a training basis to develop a neural network algorithm, which, using the Rrs at the MODIS visible wavelengths (412, 443, 488, 531, 547 and 667nm) as input, retrieves the in-water particulate backscattering (bbp ), phytoplankton (aph ) and non-phytoplankton (adg ) absorption coefficients at 443nm. In this work, using the same dataset, we develop a NN which takes these same Rrs as input, and produces an output which is used to separate the non-phytoplankton absorption coefficient (adg ) at 443nm into dissolved (ag ) and particulate (adm ) components. We then apply this synthetically trained algorithm to the NASA bio-Optical Marine Algorithm Data set (NOMAD) Rrs to retrieve IOP at 443nm, with the measured NOMAD and retrieved IOP values showing good agreement. These retrieved IOP along with their related Rrs values are then used to train an additional NN that produces chlorophyll concentration [Chl] as output. It is shown that these [Chl] values are retrieved more accurately when compared with ones retrieved with a similar approach which does not use IOP as input, as well as with those derived using the MODIS OC3 algorithm. [Copyright &y& Elsevier]

Abstract: Aircraft-mounted hyperspectral spectrometers were used to collect imagery with high spatial and spectral resolution for use in measuring optically active water quality characteristics of major rivers of Minnesota. Ground-based sampling undertaken concurrent with image acquisition provided calibration data for chlorophyll, suspended solids, turbidity and other measures of water clarity. Our approach identified the spectral characteristics that distinguish waters dominated by several inherent optical properties (IOPs), and we used those characteristics to develop models to map water quality characteristics in optically complex waters. For phytoplankton related variables (volatile suspended solids (VSS) and chlorophyll a (chl a)), the ratios of the scattering peak at the red edge (~700nm) with the reflectance troughs caused by chlorophyll absorption at ~670nm and other plant pigment absorption peaks at 592 and 620nm all were strong predictors of chl a and VSS (r2 values of 0.73–0.94). The scattering peak at ~700nm was a strong predictor of variables related to water clarity (total suspended solids (TSS), turbidity and turbidity tube (T-tube)) (r2 values of 0.77–0.93). For mineral-based variables (nonvolatile suspended solids (NVSS) and the ratio NVSS:TSS), combinations of the TSS and chl a relationships described above were strong predictors (r2 values of 0.73–0.97) and the most robust because this model corrects for the scattering of phytoplankton at ~700nm. Application of the methods to quantify spatial variations in water quality for stretches of the Mississippi River and its tributaries indicate that hyperspectral imagery can be used to distinguish and map key variables under complex IOP conditions, particularly to separate and map inorganic suspended sediments independently of chlorophyll levels. [Copyright &y& Elsevier]

Abstract: Three MERIS Case II water processors included in the BEAM software package were studied for estimating the water quality in the coastal waters of the northern Baltic Sea. The processors, named Case II Regional (C2R), boreal (BOR), and eutrophic (EUT), for the associated lake types, have been developed for different types of coastal or inland (Case II) waters. Chlorophyll-a (chl-a), total suspended matter (TSM), absorption of colored dissolved organic matter (a CDOM (443)), and signal depth (Z 90 ) products of the BEAM processors were compared with in situ data. In addition, total absorption (a TOT ) and scattering of TSM (b TSM ) from different BEAM processors were compared against the results of coastal field campaign measurements. The in situ water quality data consisted of monitoring station data gathered by the Finnish environmental administration during 2006–2009 and data from coastal field campaigns with a flow-through system. AERONET-OC (SeaPRISM) data from the Helsinki Lighthouse station were used to validate the BEAM reflectance products. The comparison with the BEAM processor results and in situ data showed that the bias of the original BEAM algorithms can be decreased through adjustment of the coefficients that relate IOPs such as the absorption of pigments and the scattering of TSM to water quality constituents such as chl-a and turbidity. The TSM products of the BEAM processors can be used to estimate the turbidity measured at monitoring stations with an r² of 0.76–0.84 and an RMSE of 0.7–0.85 FNUs (Formazin Nephelometric Units) on the coast of Finland. The best functionality for turbidity estimation was observed with the EUT processor, but the C2R processor also gave a sound performance. The BOR and C2R processors proved to be the best for deriving chl-a concentration. However, the accuracy of chl-a estimations was low with both processors (r² ranged from 0.45 to 0.47 and RMSE was between 44 and 45%). Chl-a products, particularly during the phytoplankton bloom seasons of spring and summer, require further development. The Z 90 product from the BOR processor was used to derive an algorithm for Secchi disk depth estimation with r 2 0.48 and RMSE 0.97m. The BOR processor was the most successful at CDOM estimation (r² 0.6 and RMSE 0.49 1/m), but a simple reflectance ratio was actually able to perform better (r² 0.75 and RMSE 0.39 1/m). In many cases, the differences between the outcomes of processors were small and related only to a part of the in situ dataset. [Copyright &y& Elsevier]

Abstract: Recent studies indicate that lakes are regulators of carbon cycling and climate. Therefore, it is important to know how the lake carbon content has changed over the last decades. In situ long time data series about the amount of dissolved organic carbon (DOC) in lakes are rare. The only potential way to study retrospectively the changes in lake carbon over the last decades is by means of remote sensing data provided there are sensors that can provide data about coloured dissolved organic matter (CDOM) in lakes over long periods. Landsat data archive contains images from 1984 to nowadays and covers the whole Earth. Although the sensors were not designed for remote sensing of aquatic environments it is still tempting to utilise the long data series. Landsat 4, Landsat 5 and Landsat 7 imagery available in free Landsat image archive was compared with time series of CDOM in situ data from 19 sampling stations available in the Swedish University of Natural Sciences lake monitoring database. There was no correlation between the image and in situ data when all the above mentioned data were used. Low radiometric resolution of the sensor, small size of many lakes (=large adjacency effects) and high concentration of CDOM (negligible water leaving radiation) could be the reasons. The results were more promising (R2 =0.62) when Lake Mälaren stations were analysed separately. The lake is sufficiently large and with variable, but not extremely high, CDOM content. The Lake Mälaren in situ data showed very different trends in CDOM concentrations in different basins of the lake over the last 45years. Although the correlation between the image and in situ data was a bit low for accurate daily estimation of CDOM concentrations from Landsat data it could allow detecting general trends in lake CDOM content. Unfortunately, there is currently a gap in Landsat archive (for our study sites) between 1988 and 1998 which makes calculations of long time trends unreasonable for the time being. [Copyright &y& Elsevier]

Abstract: For remote sensing of aerosol over the ocean, there is a contribution from light scattered under water. The brightness and spectrum of this light depends on the biomass content of the ocean, such that variations in the color of the ocean can be observed even from space. Rayleigh scattering by pure sea water, and Rayleigh–Gans type scattering by plankton, causes this light to be polarized with a distinctive angular distribution. To study the contribution of this underwater light polarization to multiangle, multispectral observations of polarized reflectance over ocean, we previously developed a hydrosol model for use in underwater light scattering computations that produces realistic variations of the ocean color and the underwater light polarization signature of pure sea water. In this work we review this hydrosol model, include a correction for the spectrum of the particulate scattering coefficient and backscattering efficiency, and discuss its sensitivity to variations in colored dissolved organic matter (CDOM) and in the scattering function of marine particulates. We then apply this model to measurements of total and polarized reflectance that were acquired over open ocean during the MILAGRO field campaign by the airborne Research Scanning Polarimeter (RSP). Analyses show that our hydrosol model faithfully reproduces the water-leaving contributions to RSP reflectance, and that the sensitivity of these contributions to Chlorophyll a concentration [Chl] in the ocean varies with the azimuth, height, and wavelength of observations. We also show that the impact of variations in CDOM on the polarized reflectance observed by the RSP at low altitude is comparable to or much less than the standard error of this reflectance whereas their effects in total reflectance may be substantial (i.e. up to >30%). Finally, we extend our study of polarized reflectance variations with [Chl] and CDOM to include results for simulated spaceborne observations. [Copyright &y& Elsevier]

Abstract: Empirical algorithms based on first order relationships between ocean color and the chlorophyll concentration ([Chl]; mg m−3) are widely used, but cannot explain the statistical dispersion or “anomalies” around the mean trends. We use an empirical approach that removes the first order effects of [Chl] from satellite ocean color, thus allowing us to quantify the impact on the ocean color signal of optical anomalies that vary independently of the global mean trends with remotely sensed [Chl]. We then present statistical and modeling analyses to interpret the observed anomalies in terms of their optical sources (i.e. absorption and backscattering coefficients). We identify two main sources of second order variability for a given [Chl]: 1) the amount of non-algal absorption, especially due to colored dissolved organic matter; and 2) the amplitude of the backscattering coefficient of particles. The global distribution of the anomalies displays significant regional and seasonal trends, providing important information for characterizing the marine optical environment and for inferring biogeochemical influences. We subsequently use our empirically determined anomalies to estimate the backscattering coefficient of particles and the combined absorption coefficient for colored detrital and dissolved materials. This purely empirical approach provides an independent assessment of second order optical variability for comparison with existing methods that are generally based on semi-analytical models. [Copyright &y& Elsevier]

We investigated the use of ocean color remote sensing to measure the transport of dissolved organic carbon (DOC) by the Mississippi River to the Gulf of Mexico. From 2000 to 2005 we recorded surface measurements of DOC, colored dissolved organic matter (CDOM), salinity, and water-leaving radiances during five cruises to the Mississippi River Plume. These measurements were used to develop empirical relationships to derive DOC, CDOM, and salinity from monthly composites of SeaWiFS imagery collected from 1998 through 2005. We compared our remote sensing estimates of river flow and DOC transport with data collected by the United States Geological Survey (USGS) from 1998 through 2005. Our remote sensing estimates of river flow and DOC transport correlated well (r 2 ∼0.70) with the USGS data. Our remote sensing estimates and USGS field data showed low variability in DOC concentrations in the river end-member (7–11%), and high seasonal variability in river flow (∼50%). Therefore, changes in river flow control the variability in DOC transport, indicating that the remote sensing estimate of river flow is the most critical element of our DOC transport measurement. We concluded that it is possible to use this method to estimate DOC transport by other large rivers if there are data on the relationship between CDOM, DOC, and salinity in the river plume. [Copyright &y& Elsevier]

Abstract: The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) has three bands in the visible and near-infrared (VNIR) with 15-m spatial resolution. The high spatial resolution has advantages for studying small aquatic areas, such as bay and lakes. Coastal areas are optically characterized by high concentrations of colored suspended matter, various phytoplankton pigments and colored dissolved organic matter (CDOM). The color ratio bio-optical algorithms often used for open sea are very difficult to apply in optically complex coastal water, since it is assumed that the constituents of seawater are mainly phytoplankton pigments. The Neural Network (NN) method, which is one of inverse modeling, has the potential to estimate chlorophyll a, suspended matter and CDOM from remotely sensed data. In the present investigation, we implemented the NN method in the analysis of ASTER data of Tokyo Bay, as a case study in the coastal waters in order to demonstrate the usefulness of remote sensing with high spatial resolution. After validation of the NN using simulated data sets and a field data set observed from a ship, estimation of the concentration of TSS and Chl-a was reasonably accurate. However, in the case of CDOM, the result is not reliable. Disadvantages of the NN method are discussed in this paper. [Copyright &y& Elsevier]

Abstract: Near real-time data from the MODIS satellite sensor was used to detect and trace a harmful algal bloom (HAB), or red tide, in SW Florida coastal waters from October to December 2004. MODIS fluorescence line height (FLH in W m−2 μm−1 sr−1) data showed the highest correlation with near-concurrent in situ chlorophyll-a concentration (Chl in mg m−3). For Chl ranging between 0.4 to 4 mg m−3 the ratio between MODIS FLH and in situ Chl is about 0.1 W m−2 μm−1 sr−1 per mg m−3 chlorophyll (Chl=1.255 (FLH×10)0.86, r =0.92, n =77). In contrast, the band-ratio chlorophyll product of either MODIS or SeaWiFS in this complex coastal environment provided false information. Errors in the satellite Chl data can be both negative and positive (3–15 times higher than in situ Chl) and these data are often inconsistent either spatially or temporally, due to interferences of other water constituents. The red tide that formed from November to December 2004 off SW Florida was revealed by MODIS FLH imagery, and was confirmed by field sampling to contain medium (104 to 105 cells L−1) to high (>105 cells L−1) concentrations of the toxic dinoflagellate Karenia brevis. The FLH imagery also showed that the bloom started in mid-October south of Charlotte Harbor, and that it developed and moved to the south and southwest in the subsequent weeks. Despite some artifacts in the data and uncertainty caused by factors such as unknown fluorescence efficiency, our results show that the MODIS FLH data provide an unprecedented tool for research and managers to study and monitor algal blooms in coastal environments. [Copyright &y& Elsevier]

Abstract: Given the importance of coloured dissolved organic matter (CDOM) for the structure and function of lake ecosystems, a method to estimate the amount of CDOM in lake waters over large geographic areas would be highly desirable. Advanced Land Imager (ALI) images were acquired in southern Finland (in 2002) and southern Sweden (in 2003) together with in situ measurements of bio-optical properties of 34 lakes (39 measuring stations). Based on this dataset, a band-ratio type algorithm was developed using ALI band 2 and band 3 for estimating CDOM content (absorption of filtrated water at 420 nm) in lakes. Correlation between in situ measured CDOM and the remote sensing estimate of CDOM was high, r 2=0.73. The CDOM retrieval algorithm obtained on the basis of two images and in situ data was validated on a third ALI image (eastern Finland, 2002) that was available in the ALI image archive. In situ water-colour monitoring data from 22 lakes (27 measuring stations) in the third image were available in a database of the Finnish Environment Administration. The water-colour data were converted to CDOM absorption values, which were then compared to the results from a third ALI image. The correlation between remotely estimated and in situ CDOM values in the algorithm validation image was high, r 2=0.83. These results support the conclusion that CDOM content in lakes over a wide range of concentrations (a CDOM(420) between 0.68 and 11.13 m−1) can be mapped using Advanced Land Imager data. [Copyright &y& Elsevier]

Spatial and temporal patterns of bio-optical properties were studied in the Northern Gulf of Mexico during cruises in April and October of 2000, a year during which the discharge volume from the Mississippi River was unusually low. Highly variable surface Chl a concentrations (0.1 to 17 mg m−3) and colored dissolved organic matter (CDOM) absorption (0.07 to 1.1 m−1 at 412 nm) were observed in the study region that generally decreased with increasing salinity waters, being highest nearshore and decreasing at offshore stations. The optical properties of absorption, scattering, and diffuse attenuation coefficients reflected these distributions with phytoplankton particles and CDOM contributing to most of the spatial, vertical, and seasonal variability. The diffuse attenuation coefficient Kd(λ) and spectral remote sensing reflectance Rrs(λ) were linear functions of absorption and backscattering coefficients a(λ) and bb(λ) through the downward average cosine μd and the ratio of variables f/Q at the SeaWiFS wavebands for waters with widely varying bio-optical conditions. Although various Rrs(λ) ratio combinations showed high correlation with surface Chl a concentrations and CDOM absorption at 412 nm, power law equations derived using the Rrs(490)/Rrs(555) and Rrs(510)/Rrs(555) ratios provided the best retrievals of Chl a concentrations and CDOM absorption from SeaWiFS reflectance data. [Copyright &y& Elsevier]

The optically active component of dissolved organic material in aquatic ecosystems, or colored dissolved organic matter (CDOM), is represented by the coefficient of absorption due to the dissolved aquatic constituents at 440 nm, a CDOM (440). Remote sensing of a CDOM (440) enables characterization of ecosystem processes and aids in retrieval of chlorophyll a , a proxy for phytoplankton biomass. Spectrally adjacent band-ratio domains, e.g., blue to green, have previously been applied for remote sensing of a CDOM (440) in coastal and oceanic waters with similar results compared to more complex semi-analytical algorithms. Estimation of a CDOM (440) from ratios of the most spectrally separated ocean color wavebands (end members), e.g., ultraviolet (UV) to near-infrared (NIR), termed end-member analysis (EMA), has previously been shown to increase the accuracy of global a CDOM (440) retrievals from in-water observations of diffuse attenuation and to enable a unified algorithmic perspective without requiring regional adjustment of internal bio-optical parameters. EMA of above-water observations is evaluated herein, with a focus on coastal and inland waters in which increasing optical complexity and likelihood of bottom reflectance challenge the oceanic algorithms developed for deep and optically simple (case-1) waters. Analysis herein of three independent, in situ , bio-optical datasets indicates significant correlation between a CDOM (440) and end-member band ratios (next-generation 320 and 780 nm or legacy 412 and 670 nm ratios) with a coefficient of determination, R 2, of 0.87 (log-scale) or higher based on a dataset spanning the dynamic range of global, conservative water bodies. For applicable wavelengths, EMA algorithms are shown to agree with case-1 relationships and to produce consistent log-scale uncertainties across more than three orders of magnitude in a CDOM (440) values (0.001–2.305 m−1). EMA using UV and NIR wavelengths (320 and 780 nm) is applied to low-altitude airborne observations and satisfies 25% uncertainty based on unbiased percent differences (UPDs) within each of three dissimilar match-up sites ranging in a CDOM (440) from 0.02–0.57 m−1. Results demonstrate that EMA is a useful and robust approach for the remote sensing of a CDOM (440) in coastal and inland waters, which are generally shallower, contain more optically complex environments, and span a greater range in a CDOM (440) than oceanic waters. • Spectral separation increases dynamic range of aCDOM band-ratio algorithms. • UV-NIR algorithms mitigate bottom reflectance effects in shallow waters. • UV-NIR aCDOM algorithms satisfy proposed uncertainty criteria for global waters. • UV-NIR aCDOM algorithms produce consistent global log-scale aCDOM uncertainties. [ABSTRACT FROM AUTHOR]