Radiometric validation of atmospheric correction for MERIS in the Baltic Sea based on continuous observations from ships and AERONET-OC

The Baltic Sea is a semi-enclosed sea that is optically dominated by coloured dissolved organic material (CDOM) and has relatively low sun elevation which makes accurate ocean colour remote sensing challenging in these waters. The high absorption, low scattering properties of the Baltic Sea are representative of other optically similar water bodies including the Arctic Ocean, Black Sea, coastal regions adjacent to the CDOM-rich estuaries such as the Amazon, and highly absorbing lakes where radiometric validation is essential in order to develop accurate remote sensing algorithms. Previous studies in this region mainly focused on the validation and improvementofstandardChlorophyll-a (Chla)andattenuation coefficient(kd)ocean colourproducts.Theprimary input to derive these is the water-leaving radiance (Lw) or remote sensing reflectance (Rrs) and it is therefore fundamental toobtainthemostaccurate Lw orRrs beforederivinghigherlevelproducts.Tothisend,theretrieval accuracy of Rrs from Medium Resolution Imaging Spectrometer (MERIS) imagery using six atmospheric correction processors was assessed through above-water measurements at two sites of the Aerosol Robotic Network for Ocean Colour (AERONET-OC; 363 measurements) and a shipborne autonomous platform from which the highest number of measurements were obtained (4986 measurements). The six processors tested were the CoastColour processor (CC), the Case 2 Regional processor for lakes (C2R-Lakes), the Case 2 Regional CoastColour processor (C2R-CC), the FUB/WeW water processor (FUB), the MERIS ground segment processor (MEGS) andPOLYMER. Allprocessorsexceptfor CChadsmallaverage absolutepercentage differences(ψ)inthe wavelength rangefrom 490 nmto 709 nm(ψ 60%. Compared to in situ values, the Rrs(709)/Rrs(665) band ratio had ψ 0.6. Using a score system based on all statistical tests, POLYMER scored highest, while C2R-CC, C2RLakesandFUBhadlowerscores.ThisstudyrepresentsthelargestdatabaseofinsituRrs,themostcomprehensive analysis of AC models for highly absorbing waters and for MERIS, conducted to date. The results have implications for the new generation of Copernicus Sentinel ocean colour satellites

Validation of a spectral correction procedure for sun and sky reflections in above-water reflectance measurements

A three-component reflectance model (3C) is applied to above-water radiometric measurements to derive remote-sensing reflectance Rrs (λ). 3C provides a spectrally resolved offset Δ(λ) to correct for residual sun and sky radiance (Rayleigh- and aerosol-scattered) reflections on the water surface that were not represented by sky radiance measurements. 3C is validated with a data set of matching above- and below-water radiometric measurements collected in the Baltic Sea, and compared against a scalar offset correction Δ. Correction with Δ(λ) instead of Δ consistently reduced the (mean normalized root-mean-square) deviation between Rrs (λ) and reference reflectances to comparable levels for clear (Δ: 14.3 ± 2.5 %, Δ(λ): 8.2 ± 1.7 %), partly clouded (Δ: 15.4 ± 2.1 %, Δ(λ): 6.5 ± 1.4 %), and completely overcast (Δ: 10.8 ± 1.7 %, Δ(λ): 6.3 ± 1.8 %) sky conditions. The improvement was most pronounced under inhomogeneous sky conditions when measurements of sky radiance tend to be less representative of surface-reflected radiance. Accounting for both sun glint and sky reflections also relaxes constraints on measurement geometry, which was demonstrated based on a semi-continuous daytime data set recorded in a eutrophic freshwater lake in the Netherlands. Rrs (λ) that were derived throughout the day varied spectrally by less than 2 % relative standard deviation. Implications on measurement protocols are discussed. An open source software library for processing reflectance measurements was developed and is made publicly available

Contrasting seasonality in optical-biogeochemical properties of the Baltic Sea

Optical-biogeochemical relationships of particulate and dissolved organic matter are presented in support of remote sensing of the Baltic Sea pelagic. This system exhibits strong seasonality in phytoplankton community composition and wide gradients of chromophoric dissolved organic matter (CDOM), properties which are poorly handled by existing remote sensing algorithms. Absorption and scattering properties of particulate matter reflected the seasonality in biological (phytoplankton succession) and physical (thermal stratification) processes. Inherent optical properties showed much wider variability when normalized to the chlorophyll-a concentration compared to normalization to either total suspended matter dry weight or particulate organic carbon. The particle population had the largest optical variability in summer and was dominated by organic matter in both seasons. The geographic variability of CDOM and relationships with dissolved organic carbon (DOC) are also presented. CDOM dominated light absorption at blue wavelengths, contributing 81% (median) of the absorption by all water constituents at 400 nm and 63% at 442 nm. Consequentially, 90% of water-leaving radiance at 412 nm originated from a layer (z90) no deeper than approximately 1.0 m. With water increasingly attenuating light at longer wavelengths, a green peak in light penetration and reflectance is always present in these waters, with z90 up to 3.0–3.5 m depth, whereas z90 only exceeds 5 m at biomass < 5 mg Chla m-3. High absorption combined with a weakly scattering particle population (despite median phytoplankton biomass of 14.1 and 4.3 mg Chla m-3 in spring and summer samples, respectively), characterize this sea as a dark water body for which dedicated or exceptionally robust remote sensing techniques are required. Seasonal and regional optical-biogeochemical models, data distributions, and an extensive set of simulated remote-sensing reflectance spectra for testing of remote sensing algorithms are provided as supplementary data

Complementary water quality observations from high and medium resolution Sentinel sensors by aligning chlorophyll-a and turbidity algorithms

High resolution imaging spectrometers are prerequisite to address significant data gaps in inland optical water quality monitoring. In this work, we provide a data-driven alignment of chlorophyll-a and turbidity derived from the Sentinel-2 MultiSpectral Imager (MSI) with corresponding Sentinel-3 Ocean and Land Colour Instrument (OLCI) products. For chlorophyll-a retrieval, empirical ‘ocean colour’ blue-green band ratios and a near infra-red (NIR) band ratio algorithm, as well as a semi-analytical three-band NIR-red ratio algorithm, were included in the analysis. Six million co-registrations with MSI and OLCI spanning 24 lakes across five continents were analysed. Following atmospheric correction with POLYMER, the reflectance distributions of the red and NIR bands showed close similarity between the two sensors, whereas the distribution for blue and green bands was positively skewed in the MSI results compared to OLCI. Whilst it is not possible from this analysis to determine the accuracy of reflectance retrieved with either MSI or OLCI results, optimizing water quality algorithms for MSI against those previously derived for the Envisat Medium Resolution Imaging Spectrometer (MERIS) and its follow-on OLCI, supports the wider use of MSI for aquatic applications. Chlorophyll-a algorithms were thus tuned for MSI against concurrent OLCI observations, resulting in significant improvements against the original algorithm coefficients. The mean absolute difference (MAD) for the blue-green band ratio algorithm decreased from 1.95 mg m− 3 to 1.11 mg m− 3, whilst the correlation coefficient increased from 0.61 to 0.80. For the NIR-red band ratio algorithms improvements were modest, with the MAD decreasing from 4.68 to 4.64 mg m− 3 for the empirical red band ratio algorithm, and 3.73 to 3.67 for the semi-analytical 3-band algorithm. Three implementations of the turbidity algorithm showed improvement after tuning with the resulting distributions having reduced bias. The MAD reduced from 0.85 to 0.72, 1.22 to 1.10 and 1.93 to 1.55 FNU for the 665, 708 and 778 nm implementations respectively. However, several sources of uncertainty remain: adjacent land showed high divergence between the sensors, suggesting that high product uncertainty near land continues to be an issue for small water bodies, while it cannot be stated at this point whether MSI or OLCI results are differentially affected. The effect of spectrally wider bands of the MSI on algorithm sensitivity to chlorophyll-a and turbidity cannot be fully established without further availability of in situ optical measurements

Variability of adjacency effects in sky reflectance measurements

Sky reflectance Rsky(l) is used to correct in situ reflectance measurements in the remote detection of water colour. We analysed the directional and spectral variability in Rsky(l) due to adjacency effects against an atmospheric radiance model. The analysis is based on one year of semi-continuous Rsky(l) observations that were recorded in two azimuth directions. Adjacency effects contributed to Rsky(l) dependent on season and viewing angle, and predominantly in the near-infrared (NIR). For our test area, adjacency effects spectrally resembled a generic vegetation spectrum. The adjacency effect was weakly dependent on the magnitude of Rayleigh- and aerosol-scattered radiance. Reflectance differed between viewing directions 5.4 +/- 6.3% for adjacency effects and 21.0 +/- 19.8% for Rayleigh- and aerosol-scattered Rsky(l), in the NIR. It is discussed under which conditions in situ water reflectance observations require dedicated correction for adjacency effects. We provide an open source implementation of our method to aid identification of such conditions. Copyright 2017 Optical Society of America

Incorporating a Hyperspectral Direct-Diffuse Pyranometer in an Above-Water Reflectance Algorithm

In situ hyperspectral remote-sensing reflectance (Rrs(λ)) is used to derive water quality products and perform autonomous monitoring of aquatic ecosystems. Conventionally, above-water Rrs(λ) is estimated from three spectroradiometers which measure downwelling planar irradiance(Ed(λ)), sky radiance (Ls(λ)), and total upwelling radiance (Lt(λ)), with a scaling of Ls(λ)/Ed(λ)used to correct for surface-reflected radiance. Here, we incorporate direct and diffuse irradiance,(Edd(λ)) and Eds(λ)), from a hyperspectral pyranometer (HSP) in an Rrs(λ) processing algorithm from a solar-tracking radiometry platform (So-Rad). HSP measurements of sun and sky glint (scaled Edd(λ)/Ed(λ) and Eds(λ)/Ed(λ)) replace model-optimized terms in the 3C (three-glint component) Rrs(λ) algorithm, which estimates Rrs(λ) via spectral optimization of modelled atmospheric and water properties with respect to measured radiometric quantities. We refer to the HSP-enabled method as DD (direct-diffuse) and compare differences in Rrs(λ) and Rrs(λ) variability (assessed over 20 min measurement cycles) between 3C and DD as a function of atmospheric optical state using data from three ports in the Western Channel. The greatest divergence between the algorithms occurs in the blue part of the spectrum where DD has significantly lower Rrs(λ) variability than 3C in clearer sky conditions. We also consider Rrs(λ) processing from a hypothetical two-sensor configuration (using only the Lt(λ) spectroradiometer and the HSP and referred to as DD2) as a potential lower-cost measurement solution, which is shown to have comparable Rrs(λ) and Rrs(λ) variability to DD in clearer sky conditions. Our results support that the HSP sensor can fulfil a dual role in aquatic ecosystem monitoring by improving precision in Rrs(λ) alongside its primary function to characterize aerosols

Extending Landsat 8: Retrieval of an Orange contra-Band for Inland Water Quality Applications

The Operational Land Imager (OLI) onboard Landsat 8 has found successful application in inland and coastal water remote sensing. Its radiometric specification and high spatial resolution allows quantification of water-leaving radiance while resolving small water bodies. However, its limited multispectral band set restricts the range of water quality parameters that can be retrieved. Identification of cyanobacteria biomass has been demonstrated for sensors with a band centered near 620 nm, the absorption peak of the diagnostic pigment phycocyanin. While OLI lacks such a band in the orange region, superposition of the available multispectral and panchromatic bands suggests that it can be calculated by a scaled difference. A set of 428 in situ spectra acquired in diverse lakes in Belgium and The Netherlands was used to develop and test an orange contra-band retrieval algorithm, achieving a mean absolute percentage error of 5.39 % and a bias of −0.88 % in the presence of sensor noise. Atmospheric compensation error propagated to the orange contra-band was observed to maintain about the same magnitude (13 % higher) observed for the red band and thus results in minimal additional effects for possible base line subtraction or band ratio algorithms for phycocyanin estimation. Generality of the algorithm for different reflectance shapes was tested against a set of published average coastal and inland Optical Water Types, showing robust retrieval for all but relatively clear water types (Secchi disk depth > 6 m and chlorophyll a < 1.6 mg m−3). The algorithm was further validated with 79 matchups against the Ocean and Land Colour Imager (OLCI) orange band for 10 globally distributed lakes. The retrieved band is shown to convey information independent from the adjacent bands under variable phycocyanin concentrations. An example application using Landsat 8 imagery is provided for a knowncyanobacterialbloominLakeErie,US.ThemethodisdistributedintheACOLITEatmospheric correction code. The contra-band approach is generic and can be applied to other sensors with overlapping bands. Recommendations are also provided for development of future sensors with broad spectral bands with the objective to maximize the accuracy of possible spectral enhancement

Sensitivity of remotely sensed pigment concentration via Mixture Density Networks (MDNs) to uncertainties from atmospheric correction

Lake Erie, the shallowest of the five North American Laurentian Great Lakes, exhibits degraded water quality associated with recurrent phytoplankton blooms. Optical remote sensing of these optically com�plex inland waters is challenging due to the uncertainties stemming from atmospheric correction (AC) procedures. In this study, the accuracy of remote sensing reflectance (Rrs) derived from three different AC algorithms applied to Ocean and Land Colour Instrument (OLCI) observations of western Lake Erie (WLE) is evaluated through comparison to a regional radiometric dataset. The effects of uncertainties in Rrs products on the retrieval of near-surface concentration of pigments, including chlorophyll-a (Chla) and phycocyanin (PC), from Mixture Density Networks (MDNs) are subsequently investigated. Results show that iCOR contained the fewest number of processed (unflagged) days per pixel, compared to ACOLITE and POLYMER, for parts of the lake. Limiting results to the matchup dataset in common between the three AC algorithms shows that iCOR and ACOLITE performed closely at 665 nm, while out�performing POLYMER, with the Median Symmetric Accuracy (MdSA) of �30 %, 28 %, and 53 %, respec�tively. MDN applied to iCOR- and ACOLITE-corrected data (MdSA < 37 %) outperformed MDN applied to POLYMER-corrected data in estimating Chla. Large uncertainties in satellite-derived Rrs propagated to uncertainties �100 % in PC estimates, although the model was able to recover concentrations along the 1:1 line. Despite the need for improvements in its cloud-masking scheme, we conclude that iCOR combined with MDNs produces adequate OLCI pigment products for studying and monitoring Chla across WL

Loadings of dissolved organic matter and nutrients from the Neva River into the Gulf of Finland – Biogeochemical composition and spatial distribution within the salinity gradient

We studied the loadings of dissolved organic matter (DOM) and nutrients from the Neva River into the Eastern Gulf of Finland, as well as their distribution within the salinity gradient. Concentrations of dissolved organic carbon (DOC) ranged from 390 to 840 μM, and were related to absorption of colored DOM (CDOM) at 350 nm, aCDOM(350), ranging from 2.70 to 17.8 m-1. With increasing salinity both DOC and aCDOM decreased, whereas the slope of aCDOM spectra, SCDOM(300-700), ranging from 14.3 to 21.2 μm-1, increased with salinity

Basin-scale spatio-temporal variability and control of phytoplankton photosynthesis in the Baltic Sea: The first multiwavelength fast repetition rate fluorescence study operated on a ship-of-opportunity

This study presents the results of the first field application of a flow-through multi-wavelength Fast Repetition Rate fluorometer (FRRF) equipped with two excitation channels (458 and 593 nm). This device aims to improve the measurement of mixed cyanobacteria and algae community's photosynthetic parameters and was designed to be easily incorporated into existing ferrybox systems. We present a spatiotemporal analysis of the maximum photochemical efficiency (Fv/Fm) and functional absorption cross section (σPSII) recorded from April to August 2014 on a ship-of-opportunity commuting twice per week between Helsinki (Finland) and Travemünde (Germany). Temporal variations of Fv/Fm and σPSII differed between areas of the Baltic Sea. However, even though the Baltic Sea is characterized by several physico-chemical gradients, no gradient was observed in Fv/Fm and σPSII spatial distribution suggesting complex interactions between biotic and abiotic controls. σPSII was sensitive to phytoplankton seasonal succession and thus differed according to the wavelength used to excite photosystems II (PSII) pigments. This was particularly true in summer when high σPSII(593) values were observed later and longer than high σPSII(458) values, reflecting the role of cyanobacteria in photosynthetic light uptake measured at community scale. In contrast, Fv/Fm variations were similar after excitation at 458 nm or 593 nm suggesting that the adjustment of Fv/Fm in response to environmental factors was similar for the different groups (algae vs. cyanobacteria) present within the phytoplankton community