Susanne Kratzer
Teaching
I have been involved in university teaching since 1989. I have taught in a large variety of subjects spanning from plant physiology over marine biology, ecology of macroalgae and phytoplankton, physical oceanography as well as marine remote sensing.
Recently, I have mostly taught Bio-optical Oceanography and Marine Remote Sensing at Stockholm University and at KTH.
During 2008-2016 I was main coordinator for the Nordic Network for Baltic Sea Remote Sensing and coordinated the PhD training and scientific workshops for the network: Nordic Network Events.
I have also been invited lecturer for the ERASMUS Mundus Masters course on Water and Coastal Managment. I taught at Plymouth University, UK and at the University of the Algarve, Faro (in the summers during 2005-2010).
My total teaching hours amount to 36 ECTS (13.5 ECTS on basic level, 13.5 ECTS on Master level and 9 ECTS on PhD level).
I have done more than 10 ECTS in formal university pedagogics training and I have published four book chapters on bio-optics and ocean colour remote sensing. I also contributed to making a film section on 'The colour of the Baltic Sea' in the film: The Science of Ocean Colour, directed by Roland Doerffer (46 min).
Besides that I am national advisor in bio-optics and provide vocational training on bio-optical measurements to the Swedish monitoring groups (SMHI, GU, UU, SU). The training workshops are funded by HaV, the Swedish Agency for Marine and Water Management.
Research
I am Principal Investigator of the Marine Remote Sensing Group (MRSG) at Stockholm Univeristy. Our research focus is on large-scale process studies of aquatic ecosystems, using bio-optical and remote sensing methods. My PhD thesis included a comparative study of the Irish Sea and the Baltic Sea in terms of bio-optical properties and is relevant both for ecological considerations as well as for marine remote sensing.
The strength of ocean colour research is that one uses a range of methods and scales of observations that provide us with a synoptic ‘window’ for the analysis of pelagic ecosystems, and therefore may lead to new understanding of these systems. Remote sensing data provides us with information on physical drivers and productivity in the sea (e.g. attenuation of light, wind, and sea surface temperature) and can help to monitor phytoplankton blooms. It also provides important information to evaluate the on-set of the spring bloom and the development of cyanobacteria blooms in summer, and to assess changes in phenology.
A strong focus in my research is to define the inherent optical properties of the Baltic Sea and to develop regional remote sensing algorithms (fundamental research). I have 20 years of experience in validating satellite data and I am active member of ESA's MERIS and Sentinel-3 validation teams. I am also PI of the NASA AERONET-OC station Pålgrunden. My research has also contibuted towards implementation of marine remote sensing methods in coastal and Baltic Sea management (applied research). Currently, I am also engaged in a project on the remote sensing of macroalgae.
I have also hosted several post docs in my group and was the main supervisor of 4 PhD students. Dr. Dmytro Kyryliuk defended his thesis ‘Baltic Sea from Space’ in September 2019. Dr. Elina Kari defended her thesis ‘Light conditions in seasonally ice-covered waters’ in September 2018. Besides this, Dr. Jose Beltrán-Abaunza defended his PhD thesis ‘Remote sensing in optically complex waters’ in Jan 2016, and Dr. Therese Harvey defended her PhD thesis ‘Bio-optics, satellite remote sensing and Baltic Sea ecosystems’ in Oct 2015. Additionally, I co-supervised Dr. Krista Alikas from Tartu Observatory, Univeristy of Tartu.
I have hosted several Master students from France in recent years (ERASMUS+): Martin Allart (INSA, Lyon), Vicky Bravo (INSA, Lyon) and Lise Suchet (AIX, Marseille). I have also supervised several Master students from the Department of Physical Geography, SU: Miho Ishii, Christian Vinterhav, Noemi Marsico and Viven Holub.
I have close collaborations with Umeå University, Strömbeck Consulting, Brockmann Geomatics Sweden AB, Pixalytics, Plymouth (UK), as well as JRC, Ispra (Italy), Tartu Observatory, University of Tartu (Estonia), SYKE, Helsinki (Finland), Brockmann Consult GmbH and Helmholtz-Zentrum Hereon (Germany) as well as Dublin City University and Maynooth University (Ireland).
Research projects
Publications
A selection from Stockholm University publication database
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Evaluation of Sentinel-3A OLCI products derived using the Case-2 Regional CoastColour Processor over the Baltic Sea
Dmytro Kyryliuk, Susanne Kratzer.
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Inorganic Suspended Matter as an indicator of terrestrial influence in Baltic Sea coastal areas - algorithm development, validation and ecological relevance
Susanne Kratzer, Dmytro Kyryliuk.
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Measurements of light transfer through sea ice in the northern Baltic Sea
Elina Kari (et al.).
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Retrieval of suspended pariculate matter from MERIS data: Algorithm development and validation
Elina Kari (et al.).
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Synergy of satellite, in situ and modeled data for addressing the scarcity of water quality information for eutrophication assessment and monitoring of Swedish coastal waters
Dmytro Kyryliuk (et al.).
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The effect of optical properties on Secchi depth and implications for eutrophication management
Therese Harvey (et al.).
Successful management of coastal environments requires reliable monitoring methods and indicators. Secchi depth and chlorophyll-a concentration (Chl-a) are used as indicators for the assessment of eutrophication, both within the European Commission’s Water Framework and Marine Strategy Directives and the Helsinki commission. Chl-a is a used as a proxy for phytoplankton biomass and Secchi depth is used as a measure of changes in Chl-a. However, Secchi depth is more closely correlated with the light climate, affecting for example benthic vegetation. The public strongly link Secchi depth to the perceived water quality. Due to its simple measurement method Secchi depth is included in many monitoring programmes, often with the longest available time-series. In optically complex waters, Secchi depth is influenced by other factors than Chl-a, such as coloured dissolved organic matter (CDOM) and suspended particulate matter (SPM). In this study we evaluate how much Chl-a, CDOM and inorganic SPM each contribute to the variations in Secchi depth. We collected in situ data from different Swedish coastal gradients in three regions, Bothnian Sea, Baltic proper and Skagerrak during 2010-2014. Two linear multiple regression models for each region, with Chl-a, CDOM and inorganic SPM as predictors, explained the Secchi depth well (R2adj=0.54/0.8 for the Bothnian Sea, R2adj=0.81/0.81 for the Baltic proper and R2adj=0.53/0.64 for the Skagerrak). The slope for inorganic SPM was not significant in all models, but still included in the models, as significant correlations were found, both with Secchi depth and between parameters. The follow-up analysis of the multiple regressions by commonality analyses showed differences between the regions in the unique and common effects of the variables to the variance of the R2adj for Secchi depth. In the Bothnian Sea the unique effects for Chl-a were relatively low, 6% and 20%. The highest unique effect were from CDOM (~46% in summer and 20% in spring), whereas inorganic SPM had no unique contribution in summer but in spring with ~6%. The common effects from CDOM and inorganic SPM were large (71% in spring and 42% in summer). In the Baltic proper the optical variables had a different effect on the Secchi depth, with the largest part from the common effects of all three parameters, explaining up to 42-45% of the variations. The largest unique effects were from inorganic SPM (24%) or from Chl-a (15%). The models in the Skagerrak showed another pattern with CDOM having a very high unique effect, 71% for one model and the almost equally to Chl-a in the other 26% (Chl-a 28%). The common effects between CDOM and Chl-a were also pronounced, ~21% and the inorganic SPM had the lowest effect. The models were used for applying the levels for the reference value and the threshold for good/moderate status for Chl-a within the EU directives. The results showed, that in optically complex waters, Secchi depth is not a sufficient indicator for eutrophication, or as a response to Chl-a changes. Differences in natural processes have an indirect effect on the optical components determining the Secchi depth. For example land and river run-off, resuspension, bottom substrate, hydrography and salinity may explain the differences seen between the regions. The natural coastal gradients in Secchi depth will influence the determination of reference conditions for other eutrophication indicators, such as the depth distribution of macro algae. Hence, setting targets for Secchi depth based on reducing Chl-a might in some cases have no or only limited effect.
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Integrating mooring and ship-based data for improved validation of OLCI chlorophyll-a products in the Baltic Sea
2021. Susanne Kratzer, Matthew Plowey. International Journal of Applied Earth Observation and Geoinformation 94
ArticleA Water Quality Monitor (WQM) equipped with a range of oceanographic sensors was deployed from April 2017 to October 2017 in the North Western (NW) Baltic Sea. We assessed here if the data from a moored chlorophyll-a fluorometer can be used to improve satellite validation in coastal waters. Calibrated mooring data and ship-based chlorophyll-a concentrations from 2017 and 2018 were matched with OLCI (Ocean and Land Colour Instrument) data to validate the C2RCC (Case-2 Regional Coast Colour) processor, a locally-adapted version of C2RCC (LA-C2RCC), as well as the POLYMER processor. Using additional mooring data resulted in a substantial increase in paired observations compared to using ship-based data alone (C2RCC; N = 41-63, LA-C2RCC; N = 37-59, POLYMER; N = 108-166). However, the addition of mooring data only reduced the error and bias of the LA-C2RCC (MNB: from 24 % to 22 %, RMSE: from 60 % to 57 %, APD: both 47 %). In contrast, the statistical errors increased with the addition of mooring data both for C2RCC (MNB: -26 % to -33 %, RMSE: 50 %-51 %, APD 84 %-96 %) and for POLYMER (MNB: 26 %-36 %, RMSE: 79 % to 79 %, APD 64 %-64 %). The results indicate that the locally-adapted version of the C2RCC should be used for the area of investigation. These results are most likely also related to the effect of the System Vicarious Calibration (SVC). As opposed to C2RCC, the locally-adapted version had not been vicariously calibrated. The results indicate that SVC is not beneficial for Baltic Sea data and that more work needs to be done to improve SVC for Baltic Sea waters or for other waters with high CDOM absorption. In order to improve the validation capabilities of moored fluorometers in general, they should be strategically placed in waters with representative ranges of chl-a concentrations for the area of research in question.
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Inorganic suspended matter as an indicator of terrestrial influence in Baltic Sea coastal areas - Algorithm development and validation, and ecological relevance
2020. Susanne Kratzer, Dmytro Kyryliuk, Carsten Brockmann. Remote Sensing of Environment 237
ArticleSuspended particulate matter (SPM) consists both of an organic (OSPM) and an inorganic fraction (ISPM) and the latter can be used as an indicator for coastal influence in the Baltic Sea. The concentration of SPM can be derived from particle scatter if the specific scattering properties of the respective water body are known. In this paper we show that likewise, ISPM can be derived reliably from remotely sensed particle scatter. An empirical algorithm between particle scatter (AC9 data) and ISPM concentration (measured gravimetrically) was derived from in-water measurements. This regional algorithm was then applied to the iop_bpart level 2 product (i.e. the particle scatter measured at 443 nm) derived from OLCI data on Sentinel-A (S3A) using the C2RCC neural network and validated against an independent data set. The standard error of the derived OLCI match-up data was 10%, and was thus within the goal of the mission requirements of Sentinel-3. The generated S3 composite images from spring and autumn 2018 show that in the Baltic Sea most of the ISPM falls out rather close to the shore, whereas only a very small proportion of ISPM is carried further off-shore. This is also supported by in situ ISPM transects measured in the coastal zone. The ISPM images clearly highlight the areas that are most strongly influenced by terrestrial matter. Differences between the NE Baltic and the SE Baltic proper can be explained by the difference in hydrology and coastal influence as well as bathymetry and wind-wave stirring. The method is of interest for coastal zone management and for assessing the effect of seasonal changes in terrestrial run-off and wind-driven resuspension of sediments. It can also be used to evaluate the effect of climate change which has led to an increase of extreme storm and flooding events that are usually accompanied by increased erosion and run-off from land. Last but not least, turbidity caused by particles influences the light conditions in inner coastal areas and bays, which has a profound effect on pelagic productivity, the maximum growth of macroalgae as well as fish behaviour.
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Measurements of light transfer through drift ice and landfast ice in the northern Baltic Sea
2020. Elina Kari (et al.). Oceanologia 62 (3), 347-363
ArticleThe aim of this study was to investigate the light transfer through sea ice with a focus on bio-optical substances both in fast ice and in the drift ice zones in the northern Baltic Sea. The measurements included snow and ice structure, spectral irradiance and photo-synthetically active radiation below the sea ice. We also measured the concentrations of the three main bio-optical substances which are chlorophyll-a, suspended particulate matter, and coloured dissolved organic matter (CDOM). These bio-optical substances were determined for melted ice samples and for the underlying sea water. The present study provides the first spectral light transfer data set for drift ice in the Baltic Sea. We found high CDOM absorption values typical to the Baltic Sea waters also within sea ice. Our results showed that the transmittance through bare ice was lower for the coastal fast ice than for the drift ice sites. Bio-optical substances, in particular CDOM, modified the spectral distribution of light penetrating through the ice cover. Differences in crystal structure and the amount of gas inclusions in the ice caused variation in the light transfer. Snow cover on ice was found to be the dominant factor influencing the light field under ice, confirming previous studies. In conclusion, snow cover dominated the amount of light under the ice, but did not modify its spectral composition. CDOM in the ice absorbs strongly in the short wavelengths. As pure water absorbs most in the long wavelengths, the light transfer through ice was highest in the green (549-585 nm).
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Evaluation of Sentinel-3A OLCI Products Derived Using the Case-2 Regional CoastColour Processor over the Baltic Sea
2019. Dmytro Kyryliuk, Susanne Kratzer. Sensors 19 (16)
ArticleIn this study, the Level-2 products of the Ocean and Land Colour Instrument (OLCI) data on Sentinel-3A are derived using the Case-2 Regional CoastColour (C2RCC) processor for the SentiNel Application Platform (SNAP) whilst adjusting the specific scatter of Total Suspended Matter (TSM) for the Baltic Sea in order to improve TSM retrieval. The remote sensing product kd_z90max (i.e., the depth of the water column from which 90% of the water-leaving irradiance are derived) from C2RCC-SNAP showed a good correlation with in situ Secchi depth (SD). Additionally, a regional in-water algorithm was applied to derive SD from the attenuation coefficient K-d(489) using a local algorithm. Furthermore, a regional in-water relationship between particle scatter and bench turbidity was applied to generate turbidity from the remote sensing product iop_bpart (i.e., the scattering coefficient of marine particles at 443 nm). The spectral shape of the remote sensing reflectance (R-rs) data extracted from match-up stations was evaluated against reflectance data measured in situ by a tethered Attenuation Coefficient Sensor (TACCS) radiometer. The L2 products were evaluated against in situ data from several dedicated validation campaigns (2016-2018) in the NW Baltic proper. All derived L2 in-water products were statistically compared to in situ data and the results were also compared to results for MERIS validation from the literature and the current S3 Level-2 Water (L2W) standard processor from EUMETSAT. The Chl-a product showed a substantial improvement (MNB 21%, RMSE 88%, APD 96%, n = 27) compared to concentrations derived from the Medium Resolution Imaging Spectrometer (MERIS), with a strong underestimation of higher values. TSM performed within an error comparable to MERIS data with a mean normalized bias (MNB) 25%, root-mean square error (RMSE) 73%, average absolute percentage difference (APD) 63% n = 23). Coloured Dissolved Organic Matter (CDOM) absorption retrieval has also improved substantially when using the product iop_adg (i.e., the sum of organic detritus and Gelbstoff absorption at 443 nm) as a proxy (MNB 8%, RMSE 56%, APD 54%, n = 18). The local SD (MNB 6%, RMSE 62%, APD 60%, n = 35) and turbidity (MNB 3%, RMSE 35%, APD 34%, n = 29) algorithms showed very good agreement with in situ data. We recommend the use of the SNAP C2RCC with regionally adjusted TSM-specific scatter for water product retrieval as well as the regional turbidity algorithm for Baltic Sea monitoring. Besides documenting the evaluation of the C2RCC processor, this paper may also act as a handbook on the validation of Ocean Colour data.
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Summer Distribution of Total Suspended Matter Across the Baltic Sea
2019. Dmytro Kyryliuk, Susanne Kratzer. Frontiers in Marine Science 5
ArticleThere are three optical in-water components that, besides water itself, govern the under-water light field: phytoplankton, total suspended matter (TSM), and colored dissolved organic matter (CDOM). In essence, it is the spectral absorption and scattering properties of each optical component that govern the underwater light field, and also the color of the sea that we can perceive, and that can also be measured remotely from space. The Baltic Sea is optically dominated by CDOM, apart from cyanobacteria blooms that often cover most of the Baltic proper during summer. Remote sensing images of TSM reveal large-and mesoscale features and currents, especially in the Southern Baltic, which are influenced both by atmospheric Rossby waves and the Coriolis force. In coastal waters, the optical properties are strongly influenced by inorganic suspended matter, which may originate from coastal erosion and from run-off from land, streams, and rivers. In this paper, we evaluate the distribution of TSM across the Baltic Sea using remote sensing data and statistically compare the TSM loads in the different Helsinki Commission (HELCOM)-defined basins. The total suspended matter (TSM) loads during summer vary substantially in the different basins, with the south-eastern Baltic overall being most influenced by cyanobacteria blooms. The Gdansk basin and the Gulf of Riga were distinguished both by relatively high TSM loads with high standard deviations, indicating strong fluvial input and/or resuspension of sediments. We also evaluate a coastal TSM transect in Himmerfjärden bay, which is located at the Swedish East coast in the Western Gotland Basin. The effect of wind-wave stirring on the distribution of TSM from source (shore) to sink (open sea) can be assessed using satellite data from European Space Agency’s (ESA) MEdium Resolution Imaging Spectrometer (MERIS) mission (2002–2012) with 300 m resolution. The TSM transect data from areas with low wind exposure and a stable thermocline showed a gradient distribution perpendicular to the coast for summer seasons 2009, 2010, 2011, and a 3-year summer composite, confirming a previous bio-optical study from the Western Gotland basin.
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Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters
2019. Susanne Kratzer (et al.). Remote Sensing 11 (17)
ArticleMonthly CHL-a and Secchi Depth (SD) data derived from the full mission data of the Medium Resolution Imaging Spectrometer (MERIS; 2002-2012) were analysed along a horizontal transect from the inner Braviken bay and out into the open sea. The CHL-a values were calibrated using an algorithm derived from Swedish lakes. Then, calibrated Chl-a and Secchi Depth (SD) estimates were extracted from MERIS data along the transect and compared to conventional monitoring data as well as to data from the Swedish Coastal zone Model (SCM), providing physico-biogeochemical parameters such as temperature, nutrients, Chlorophyll-a (CHL-a) and Secchi depth (SD). A high negative correlation was observed between satellite-derived CHL-a and SD (rho = -0.91), similar to the in situ relationship established for several coastal gradients in the Baltic proper. We also demonstrate that the validated MERIS-based estimates and data from the SCM showed strong correlations for the variables CHL-a, SD and total nitrogen (TOTN), which improved significantly when analysed on a monthly basis across basins. The relationship between satellite-derived CHL-a and modelled TOTN was also evaluated on a monthly basis using least-square linear regression models. The predictive power of the models was strong for the period May-November (R-2: 0.58-0.87), and the regression algorithm for summer was almost identical to the algorithm generated from in situ data in Himmerfjarden bay. The strong correlation between SD and modelled TOTN confirms that SD is a robust and reliable indicator to evaluate changes in eutrophication in the Baltic proper which can be assessed using remote sensing data. Amongst all three assessed methods, only MERIS CHL-a was able to correctly depict the pattern of phytoplankton phenology that is typical for the Baltic proper. The approach of combining satellite data and physio-biogeochemical models could serve as a powerful tool and value-adding complement to the scarcely available in situ data from national monitoring programs. In particular, satellite data will help to reduce uncertainties in long-term monitoring data due to its improved measurement frequency.
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Development of under-ice stratification in Himmerfjärden bay, north-western Baltic proper, and their effect on the phytoplankton spring bloom
2018. Elina Kari (et al.). Journal of Marine Systems 186, 85-95
ArticleSeasonal sea ice cover reduces wind-driven mixing and allows for under-ice stratification to develop. These under-ice plumes are a common phenomenon in the seasonal sea ice zone. They stabilize stratification and concentrate terrestrial runoff in the top layer, transporting it further offshore than during ice-free seasons. In this study, the effect of sea ice on spring stratification is investigated in Himmerfjärden bay in the NW Baltic Sea. Distinct under-ice plumes were detected during long ice seasons. The preconditions for the development of the under-ice plumes are described as well as the typical spatial and temporal dimensions of the resulting stratification patterns. Furthermore, the effect of the under-ice plume on the timing of the onset and the maximum of the phytoplankton spring bloom were investigated, in terms of chlorophyll-a (Chl-a) concentrations. At the head of the bay, bloom onset was delayed on average by 18 days in the event of an under-ice plume. However, neither the maximum concentration of Chl-a nor the timing of the Chl-a maximum were affected, implying that the growth period was shorter with a higher daily productivity. During this period from spring bloom onset to maximum Chl-a, the diatom biomass was higher and Mesodinium rubrum biomass was lower in years with under-ice plumes compared to years without under-ice plumes. Our results thus suggest that the projected shorter ice seasons in the future will reduce the probability of under-ice plume development, creating more dynamic spring bloom conditions. These dynamic conditions and the earlier onset of the spring bloom seem to favor the M. rubrum rather than diatoms.
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Influence of allochthonous dissolved organic matter on pelagic basal production in a northerly estuary
2018. A. Andersson (et al.). Estuarine, Coastal and Shelf Science 204, 225-235
ArticlePhytoplankton and heterotrophic bacteria are key groups at the base of aquatic food webs. In estuaries receiving riverine water with a high content of coloured allochthonous dissolved organic matter (ADOM), phytoplankton primary production may be reduced, while bacterial production is favoured. We tested this hypothesis by performing a field study in a northerly estuary receiving nutrient-poor, ADOM-rich riverine water, and analyzing results using multivariate statistics. Throughout the productive season, and especially during the spring river flush, the production and growth rate of heterotrophic bacteria were stimulated by the riverine inflow of dissolved organic carbon (DOC). In contrast, primary production and photosynthetic efficiency (i.e. phytoplankton growth rate) were negatively affected by DOC. Primary production related positively to phosphorus, which is the limiting nutrient in the area. In the upper estuary where DOC concentrations were the highest, the heterotrophic bacterial production constituted almost 100% of the basal production (sum of primary and bacterial production) during spring, while during summer the primary and bacterial production were approximately equal. Our study shows that riverine DOC had a strong negative influence on coastal phytoplankton production, likely due to light attenuation. On the other hand DOC showed a positive influence on bacterial production since it represents a supplementary food source. Thus, in boreal regions where climate change will cause increased river inflow to coastal waters, the balance between phytoplankton and bacterial production is likely to be changed, favouring bacteria. The pelagic food web structure and overall productivity will in turn be altered.
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Inherent Optical Properties of the Baltic Sea in Comparison to Other Seas and Oceans
2018. Susanne Kratzer, Gerald Moore. Remote Sensing 10 (3)
ArticleIn 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 a(d) [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 m(2) g(-1)) vs. 0.578 m(2) 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) over tilde was calculated fitting a Fournier-Forand PF to the normalized VSF data. (b) over tilde 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.
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A Novel Statistical Approach for Ocean Colour Estimation of Inherent Optical Properties and Cyanobacteria Abundance in Optically Complex Waters
2017. Monika Soja-Woźniak (et al.). Remote Sensing 9 (4)
ArticleEutrophication is an increasing problem in coastal waters of the Baltic Sea. Moreover, algal blooms, which occur every summer in the Gulf of Gdansk can deleteriously impact human health, the aquatic environment, and economically important fisheries, tourism, and recreation industries. Traditional laboratory-based techniques for water monitoring are expensive and time consuming, which usually results in limited numbers of observations and discontinuity in space and time. The use of hyperspectral radiometers for coastal water observation provides the potential for more detailed remote optical monitoring. A statistical approach to develop local models for the estimation of optically significant components from in situ measured hyperspectral remote sensing reflectance in case 2 waters is presented in this study. The models, which are based on empirical orthogonal function (EOF) analysis and stepwise multilinear regression, allow for the estimation of parameters strongly correlated with phytoplankton (pigment concentration, absorption coefficient) and coloured detrital matter abundance (absorption coefficient) directly from reflectance spectra measured in situ. Chlorophyll a concentration, which is commonly used as a proxy for phytoplankton biomass, was retrieved with low error (median percent difference, MPD = 17%, root mean square error RMSE = 0.14 in log(10) space) and showed a high correlation with chlorophyll a measured in situ (R = 0.84). Furthermore, phycocyanin and phycoerythrin, both characteristic pigments for cyanobacteria species, were also retrieved reliably from reflectance with MPD = 23%, RMSE = 0.23, R-2 = 0.77 and MPD = 24%, RMSE = 0.15, R-2 = 0.74, respectively. The EOF technique proved to be accurate in the derivation of the absorption spectra of phytoplankton and coloured detrital matter (CDM), with R-2 (lambda) above 0.83 and RMSE around 0.10. The approach was also applied to satellite multispectral remote sensing reflectance data, thus allowing for improved temporal and spatial resolution compared with the in situ measurements. The EOF method tested on simulated Medium Resolution Imaging Spectrometer (MERIS) or Ocean and Land Colour Instrument (OLCI) data resulted in RMSE = 0.16 for chl-a and RMSE = 0.29 for phycocyanin. The presented methods, applied to both in situ and satellite data, provide a powerful tool for coastal monitoring and management.
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Improved retrieval of Secchi depth for optically-complex waters using remote sensing data
2017. Krista Alikas, Susanne Kratzer. Ecological Indicators 77, 218-227
ArticleWater transparency is one of the ecological indicators for describing water quality and the underwater light field which determines its productivity. In the European Water Framework Directive (WFD) as well as in the European Marine Strategy Framework Directive (MSFD) water transparency is used for ecological status classification of inland, coastal and open sea waters and it is regarded as an indicator for eutrophication in Baltic Sea management (HELCOM, 2007). We developed and compared different empirical and semi-analytical algorithms for lakes and coastal Nordic waters to retrieve Secchi depth (Z(SD)) from remote sensing data (MERIS, 300 m resolution).The algorithms were developed in water bodies with high coloured dissolved organic matter absorption (a(CNOM)(442) ranging 1.7-4.0 m(-1)), Chl a concentration (0.5-73 mg m(-3)) and total suspended matter (0.7-37.5 g m(-3)) and validated against an independent data set over inland and coastal waters (0.6 m < Z(SD) < 14.8 m). The results indicate that for empirical algorithms, using longer wavelengths in the visible spectrum as a reference band decreases the RMSE and increases the coefficient of determination (R-2). The accuracy increased (R-2 = 0.75, RMSE = 1.33 m, n = 134) when Z(SD) was retrieved via an empirical relationship between Z(SD) and K-d (490). The best agreement with in situ data was attained when Z(SD) was calculated via both the diffuse and the beam attenuation coefficient (R-2 = 0.89, RMSE = 0.77 m, n = 89). The results demonstrate that transparency can be retrieved with high accuracy over various optical water types by the means of ocean color remote sensing, improving both the spatial and temporal coverage. The satellite derived Z(SD) product could be therefore used as an additional source of information for WFD and MSFD reporting purposes.
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Retrieval of suspended particulate matter from turbidity - model development, validation, and application to MERIS data over the Baltic Sea
2017. Elina Kari (et al.). International Journal of Remote Sensing 38 (7), 1983-2003
ArticleSuspended particulate matter (SPM) causes most of the scattering in natural waters and thus has a strong influence on the underwater light field, and consequently on the whole ecosystem. Turbidity is related to the concentration of SPM which usually is measured gravimetrically, a rather time-consuming method. Measuring turbidity is quick and easy, and therefore also more cost-effective. When derived from remote sensing data the method becomes even more cost-effective because of the good spatial resolution of satellite data and the synoptic capability of the method. Turbidity is also listed in the European Union's Marine Strategy Framework Directive as a supporting monitoring parameter, especially in the coastal zone. In this study, we aim to provide a new Baltic Sea algorithm to retrieve SPM concentration from in situ turbidity and investigate how this can be applied to satellite data. An in situ dataset was collected in Swedish coastal waters to develop a new SPM model. The model was then tested against independent datasets from both Swedish and Lithuanian coastal waters. Despite the optical variability in the datasets, SPM and turbidity were strongly correlated (r = 0.97). The developed model predicts SPM reliably from in situ turbidity (R-2 = 0.93) with a mean normalized bias (MNB) of 2.4% for the Swedish and 14.0% for the Lithuanian datasets, and a relative error (RMS) of 25.3% and 37.3%, respectively. In the validation dataset, turbidity ranged from 0.3 to 49.8 FNU (Formazin Nephelometric Unit) and correspondingly, SPM concentration ranged from 0.3 to 34.0 g m(-3) which covers the ranges typical for Baltic Sea waters. Next, the medium-resolution imaging spectrometer (MERIS) standard SPM product MERIS Ground Segment (MEGS) was tested on all available match-up data (n = 67). The correlation between SPM retrieved from MERIS and in situ SPM was strong for the Swedish dataset with r = 0.74 (RMS = 47.4 and MNB = 11.3%; n = 32) and very strong for the Lithuanian dataset with r = 0.94 (RMS = 29.5% and MNB = -1.5%; n = 35). Then, the turbidity was derived from the MERIS standard SPM product using the new in situ SPM model, but retrieving turbidity from SPM instead. The derived image was then compared to existing in situ data and showed to be in the right range of values for each sub-area. The new SPM model provides a robust and cost-efficient method to determine SPM from in situ turbidity measurements (or vice versa). The developed SPM model predicts SPM concentration with high quality despite the high coloured dissolved organic matter (CDOM) range in the Baltic Sea. By applying the developed SPM model to already existing remote sensing data (MERIS/Envisat) and most importantly to a new generation of satellite sensors (in particular OLCI on board the Sentinel-3), it is possible to derive turbidity for the Baltic Sea.
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Using MERIS data to assess the spatial and temporal variability of phytoplankton in coastal areas
2017. José M. Beltrán-Abaunza, Susanne Kratzer, Helena Hoglander. International Journal of Remote Sensing 38 (7), 2004-2028
ArticleThis study aims to highlight how satellite data can be used for an improved understanding of ecological processes in a narrow coastal bay. The usefulness of the Medium Resolution Imaging Spectrometer (MERIS) data (2003-2011) as a complement to the in situ monitoring in Himmerferdenn (HF) bay is used as an example that can also be applied to other coastal areas. HF bay is one of the most frequently monitored coastal areas in the world, allowing for a rigorous comparison between satellites and ship-based monitoring data. MERIS data was used for the integration of chlorophyll-a (chl-a) over each waterbody in the HF area, following the national waterbody classification by the Swedish Meteorological and Hydrological Institute (SMHI). Chl-a anomaly maps were produced for the bay and its adjacent areas. The maps could be used to show events with high chl-a, both with natural causes (e.g. a Prymnesium polylepis bloom observed in summer 2008) and of anthropogenic causes (e.g. failure in the local sewage treatment plant resulting in a strong spring bloom in 2006). Anomaly maps thereby allow to scan larger coastal stretches to discriminate areas that may require additional sampling by ship, or to identify areas that do not differ much from the median value of the MERIS time series.
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Satellite-based water quality monitoring in Lake Vänern, Sweden
2016. Petra Philipson (et al.). International Journal of Remote Sensing 37 (16), 3938-3960
ArticleLake Vänern, Sweden, is one of Europe’s largest lakes and has a historical, cultural, ecological as well as economic importance. Lake water quality monitoring is required by national and international legislations and directives, but present programmes are insufficient to meet the requirements. To complement in situ based monitoring, the possibility to obtain reliable information about spatial and temporal water quality trends in Lake Vänern from the ENVISAT mission’s MERIS instrument was evaluated. The complete archive (2002–2012) of MERIS (Medium Resolution Imaging Spectrometer) full resolution data was processed using the water processor developed by Free University Berlin (FUB) to derive aerosol optical thickness (AOT), remote-sensing reflectance (Rrs) and water quality parameters: chlorophyll-a (chl-a) concentration, coloured dissolved organic matter absorption at 443 nm (CDOM), and total suspended matter (TSM) concentration. The objective was to investigate if, either, FUB reflectance products in combination with potential lake-specific band ratio algorithms for water quality estimation, or directly, FUB water quality products, could complement the existing monitoring programme.
Application of lake-specific band ratio algorithms requires high-quality reflectance products based on correctly estimated AOT. The FUB reflectance and AOT products were evaluated using Aerosol Robotic Network – Ocean Color (AERONET-OC) match-up data measured at station Pålgrunden in Lake Vänern. The mean absolute percentage differences (MAPDs) of the final reflectance retrievals at 413, 443, 490, 555, and 665 nm were 510%, 48%, 33%, 34%, and 33%, respectively, corresponding to a large positive bias in 413 nm, positive bias in 443–555 nm, and a negative bias in 665 nm. AOT was strongly overestimated in all bands.
The FUB water quality products were evaluated using match-up in situ data of chl-a, filtered absorbance (AbsF(420)) and turbidity as AbsF(420) is related to CDOM and turbidity is strongly related to TSM. The in situ data was collected within the Swedish national and regional monitoring programmes. In order to widen the range of water constituents and add more data to the analysis, data from four large Swedish lakes (Vänern, Vättern, Mälaren, and Hjälmaren) was included in the analysis. High correlation (r ≥ 0.85) between in situ data and MERIS FUB derived water quality estimates were obtained, but the absolute levels were over- (chl-a) or under- (CDOM) estimated. TSM was retrieved without bias.
Calibration algorithms were established for chl-a and CDOM based on the match-up data from all four lakes. After calibration of the MERIS FUB data, realistic time series could be derived that were well in line with in situ measurements. The MAPDs of the final retrievals of chl-a, AbsF(420) and Turbidity in Lake Vänern were 37%, 15%, and 35%, respectively, corresponding to mean absolute differences (MADs) of 0.9 µg l−1, 0.17 m−1, and 0.32 mg l−1 in absolute values.
The partly inaccurate reflectance estimations in combination with both positive and negative bias imply that successful application of band ratio algorithms is unlikely. The high correlation between MERIS FUB water quality products and in situ data, on the other hand, shows a potential to complement present water quality monitoring programmes and improve the understanding and representability of the temporally and spatially sparse in situ observations. The monitoring potential shown in this study is applicable to the Sentinel-3 mission’s OLCI (Ocean Land Colour Instrument), which was launched by the European Space Agency (ESA) in February 2016 as a part of the EC Copernicus programme.
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Relationships between colored dissolved organic matter and dissolved organic carbon in different coastal gradients of the Baltic Sea
2015. E. Therese Harvey, Susanne Kratzer, Agneta Andersson. Ambio 44 (3), 392-401
ArticleDue to high terrestrial runoff, the Baltic Sea isrich in dissolved organic carbon (DOC), the light-absorbing fraction of which is referred to as coloreddissolved organic matter (CDOM). Inputs of DOC andCDOM are predicted to increase with climate change,affecting coastal ecosystems. We found that therelationships between DOC, CDOM, salinity, and Secchidepth all differed between the two coastal areas studied; theW Gulf of Bothnia with high terrestrial input and the NWBaltic Proper with relatively little terrestrial input. TheCDOM:DOC ratio was higher in the Gulf of Bothnia,where CDOM had a greater influence on the Secchi depth,which is used as an indicator of eutrophication and henceimportant for Baltic Sea management. Based on the resultsof this study, we recommend regular CDOM measurements in monitoring programmes, to increase the value ofconcurrent Secchi depth measurements.
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Robust remote sensing algorithms to derive the diffuse attenuation coefficient for lakes and coastal waters
2015. Krista Alikas (et al.). Limnology and Oceanography 13 (8), 402-415
ArticleIn this study, empirical and semianalytical algorithms are developed and compared for optically complex waters to retrieve the diffuse attenuation coefficient of downwelling irradiance (Kd(lambda)) from satellite data. In the first approach, a band ratio algorithm was used. Various sets of MERIS band ratios were tested to achieve the best estimates for K-d(490) based on the in situ dataset which was measured in Nordic lakes (oligotrophic to eutrophic conditions). In the second approach, K-d(490) was expressed as a function of inherent optical properties which were retrieved from MERIS standard products. The algorithms from both approaches were tested against an independent data set and validated in optically complex coastal waters in the Baltic Sea and in Nordic lakes with high concentrations of coloured dissolved organic matter (0.3 < a(cdom)(442) m(-1) < 4.5), chlorophyll a (Chl a) (0.7< C-Chl a(mg m(-3))< 67.5) and total suspended matter (TSM) (0.5 < C-TSM(g m(-3)) < 26.4). MERIS-derived K-d(490) values showed reliable estimates in case of both methods. The results indicate that for band ratio algorithms, the root mean square error (RMSE) decreases and the coefficient of determination (R-2) increases when using longer wavelengths in the visible spectrum as a reference band. It was found that the best estimates were retrieved from MERIS data when using the ratio of R-rs(490)/R-rs(709) for coastal waters (K-d(490) < 2.5 m(-1)) and the ratio R-rs(560)/R-rs(709) for more turbid inland waters (Kd(490) > 2.5 m(-1)). As a result, a combined band ratio algorithm was developed, which provides a promising approach R-2 = 0.98, RMSE= 17%, N = 34, p < 0.05) for estimating K-d(490) over a wide range of values (0.3-6.1 m(-1)).
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The impact of air mass advection on aerosol optical properties over Gotland (Baltic Sea)
2016. Agnieszka Zdun, Anna Rozwadowska, Susanne Kratzer. Atmospheric research 182, 142-155
ArticleIn the present paper, measurements of aerosol optical properties from the Gotland station of the AERONET network, combined with a two-stage cluster analysis of back trajectories of air masses moving over Gotland, were used to identify the main paths of air mass advection to the Baltic Sea and to relate them to aerosol optical properties, i.e. the aerosol optical thickness at the wavelength lambda = 500 nm, AOT (500) and the Angstrom exponent for the spectral range from 440 to 870 nm, alpha(440,870). One-to six-day long back trajectories ending at 300, 500 and 3000 m above the station were computed using the HYSPLIT model. The study shows that in the Gotland region, variability in aerosol optical thickness AOT(500) is more strongly related to advections in the boundary layer than to those in the free troposphere. The observed variability in AOT(500) was best explained by the advection speeds and directions given by clustering of 4-day backward trajectories of air arriving in the boundary layer at 500 m above the station. 17 clusters of 4-day trajectories arriving at altitude 500 m above the Gotland station (sea level) derived using two-stage cluster analysis differ from each other with respect to trajectory length, the speed of air mass movement and the direction of advection. They also show different cluster means of AOT(500) and alpha(440,870). The cluster mean AOT(500) ranges from 0342 +/- 0.012 for the continental clusters M2 (east-southeast advection with moderate speed) and 0294 +/- 0.025 for S5 (slow south-southeast advection) to 0.064 +/- 0.002 and 0.069 +/- 0.002 for the respective marine clusters L3 (fast west-northwest advection) and M3 (north-northwest advection with moderate speed). The cluster mean a(440,870) varies from 1.65-1.70 for the short-trajectory clusters to 0.98 +/- 0.03 and 1.06 +/- 0.03 for the Arctic marine cluster L4 (fast inflow from the north) and marine cluster L5 (fast inflow from the west) respectively.
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SIMilarity Environment Correction (SIMEC) applied to MERIS data over inland and coastal waters
2015. S. Sterckx (et al.). Remote Sensing of Environment 157, 96-110
ArticleThe launch of several new satellites such as Sentinel-2, Sentinel-3, HyspIRI, EnMAP and PRISMA in the very near future, opens new perspectives for the inland and coastal water community. The monitoring of the water quality closer to the coast, within estuaries or small lakes with satellite data will become feasible. However for these inland and nearshore coastal waters, adjacency effects may hamper the correct retrieval of water quality parameters from remotely sensed imagery. Here, we present a sensor-generic adjacency pre-processing method, SIMilarity Environment Correction (SIMEC). The correction algorithm estimates the contribution of the background radiance based on the correspondence with the Near-INfrared (NIR) similarity spectrum. The performance of SIMEC was tested on MERIS FR images both above highly reflecting waters with high SPM loads, as well as dark lake waters with high CDOM absorption. The results show that SIMEC has a positive or neutral effect on the normalized remote sensing reflectance above optically-complex waters, retrieved with the MERIS MEGS or UR processor.
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Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters
2015. E. Therese Harvey, Susanne Kratzer, Petra Philipson. Remote Sensing of Environment 158, 417-430
ArticleThe coastal zones are the most inhabited areas of the world and are therefore strongly affected by humans, leading to undesirable environmental changes that may alter the ecosystems, such as eutrophication. In order to evaluate changes in the environment an effective water quality monitoring system for the coastal zones must be in place. The chlorophyll-a concentration is commonly used as a proxy for phytoplankton biomass and as indicator for eutrophication and it can be retrieved from ocean colour remote sensing data. Several operational monitoring systems based on remote sensing are in place to monitor the open sea and, to some extent, the coastal zones. However, evaluations of coastal monitoring systems based on satellite data are scarce. This paper compares the chlorophyll-a concentrations retrieved from an operational satellite system based on MERIS (Medium Resolution Imaging Spectrophotometer) data with ship-based monitoring for the productive seasons in 2008 and 2010, in a coastal area in the Baltic Sea. The comparisons showed that the satellite-based monitoring system is reliable and that the estimations of chlorophyll-a concentration are comparable to in situ measurements in terms of accuracy and quantitative retrieval. A very strong correlation was found between measurements from satellite-derived chlorophyll-a compared to in situ measurements taken close in time (0-3 days), with RMSE of 64% and a MNB of 17%. The comparison of the monthly means showed improved RMSE and a MNB of only 8%. Furthermore, this study shows that MERIS is better at capturing spatial dynamics and the extent of phytoplankton blooms than ship-based monitoring, since it has a synoptic view and higher temporal resolution. Satellite-based monitoring also increases the frequency of chlorophyll-a observations considerably, where the degree of improvement is dependent on the sampling frequency of the respective monitoring programme. Our results show that ocean colour remote sensing can, when combined with field sampling, provide an improved basis for more effective monitoring and management of the coastal zone. These results are important for eutrophication assessment and status classifications of water basins and can be applied to a larger extent within national and international agreements considering the coastal zones, e.g. the European Commission's Water Framework Directive.
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Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM
2014. José M. Beltrán-Abaunza, Susanne Kratzer, C. Brockmann. Ocean Science 10 (3), 377-396
ArticleIn this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using four different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http://vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improves the retrieval of spectral reflectance for all processors. Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5 %, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg m(-3)), data dispersion dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and data dispersion were obtained with MEGS for suspended particulate matter, for which overestimations in the range of 8-16% were found. Only the FUB retrieved CDOM (coloured dissolved organic matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjarden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in the presence of high CDOM attenuation.
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The use of ocean color remote sensing in integrated coastal zone management - A case study from Himmerfjärden, Sweden
2013. Susanne Kratzer, E. Therese Harvey, Petra Philipson. Marine Policy 43, 29-39
ArticleIn this study the use of ocean color data as a diagnostic tool in integrated coastal zone management was investigated as part of the Science Policy Integration for Coastal Systems Assessment (SPICOSA) project. Parallel to this, an operational coastal monitoring system has been set up in close collaboration with end-users. The core work of the bio-optical part in the project was to develop Secchi depth and attenuation of light as indicators for coastal zone management, by linking remote sensing with the socio-economic and ecological model developed in SPICOSA. The article emphasizes the benefits of stakeholder involvement and end-user feedback for efficient and improved system development. Furthermore, conceptual models were developed on how to integrate remote sensing data into coastal zone management and into a physical-biological model of the Baltic Sea. One of the work packages in the SPICOSA project was academic training. In this work package, on-line teaching material in the field of remote sensing and bio-optics was developed and disseminated on the SETnet web page. The article presented here may act as supportive material for training in bio-optics and remote sensing.
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In situ determination of the remote sensing reflectance: an inter comparison
2012. G. Zibordi (et al.). Ocean Science 8 (4), 567-586
ArticleInter-comparison of data products from simultaneous measurements performed with independent systems and methods is a viable approach to assess the consistency of data and additionally to investigate uncertainties. Within such a context the inter-comparison called Assessment of In Situ Radiometric Capabilities for Coastal Water Remote Sensing Applications (ARC) was carried out at the Acqua Alta Oceanographic Tower in the northern Adriatic Sea to explore the accuracy of in situ data products from various in- and above-water optical systems and methods. Measurements were performed under almost ideal conditions, including a stable deployment platform, clear sky, relatively low sun zenith angles and moderately low sea state. Additionally, all optical sensors involved in the experiment were inter-calibrated through absolute radiometric calibration performed with the same standards and methods. Inter-compared data products include spectral waterleaving radiance L-w(lambda), above-water downward irradiance E-d(0(+),lambda) and remote sensing reflectance R-rs(lambda). Data products from the various measurement systems/methods were directly compared to those from a single reference system/method. Results for R-rs(lambda) indicate spectrally averaged values of relative differences comprised between - 1 and +6 %, while spectrally averaged values of absolute differences vary from approximately 6% for the above-water systems/methods to 9 % for buoy-based systems/methods. The agreement between R-rs(lambda) spectral relative differences and estimates of combined uncertainties of the inter-compared systems/methods is noteworthy.
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Intercomparison in the field between the new WISP-3 and other radiometers (TriOS Ramses, ASD FieldSpec, and TACCS)
2012. Annelies Hommersom (et al.). Journal of Applied Remote Sensing 6
ArticleOptical close-range instruments can be applied to derive water quality parameters for monitoring purposes and for validation of optical satellite data. In situ radiometers are often difficult to deploy, especially from a small boat or a remote location. The water insight spectrometer (WISP-3) is a new hand-held radiometer for monitoring water quality, which automatically performs measurements with three radiometers (L-sky, L-u, E-d) and does not need to be connected with cables and electrical power during measurements. The instrument is described and its performance is assessed by an intercomparison to well-known radiometers, under real fieldwork conditions using a small boat and with sometimes windy and cloudy weather. Root mean squared percentage errors relative to those of the TriOS system were generally between 20% and 30% for remote sensing reflection, which was comparable to those of the other instruments included in this study. From this assessment, it can be stated that for the tested conditions, the WISP-3 can be used to obtain reflection spectra with accuracies in the same range as well-known instruments. When tuned with suitable regional algorithms, it can be used for quick scans for water quality monitoring of Chl, SPM, and aCDOM.
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Seasonal variability in the optical properties of Baltic aerosols
2011. Agnieszka Zdun, Anna Rozwadowska, Susanne Kratzer. Oceanologia 53 (1), 7-34
ArticleA five-year dataset of spectral aerosol optical thickness was used to analyse the seasonal variability of aerosol optical properties (the aerosol optical thickness (AOT) at wavelength lambda = 500 urn, AOT(500) and the Angstrom exponent for the 440-870 urn spectral range, a(440, 870)) over the Baltic Sea and dependence of these optical properties on meteorological factors (wind direction, wind speed and relative humidity). The data from the Gotland station of the global radiometric network AERONET (Aerosol Robotic Network, http://aeronet.gsfc.nasa.gov)were taken to be representative of the Baltic Sea conditions. Meteorological observations from Farosund were also analysed. Analysis of the data from 1999 to 2003 revealed a strong seasonal cycle in AOT. (500) and alpha(440, 870). Two maxima, of monthly mean values of AOT(500) over the Baltic were observed. In April, an increase in the monthly mean aerosol optical thickness over Gotland most probably resulted from agricultural waste straw burning, mainly in northern Europe and Russia as well as in the Baltic states, Ukraine and Belarus. During July and August, the aerosol optical thickness was affected by uncontrolled fires (biomass burning). There was a local minimum of AOT(500) in June. Wind direction, a local meteorological parameter strongly related to air mass advection, is the main meteorological factor influencing the variability of aerosol optical properties in each season. The highest mean values of AOT(500) and alpha(440, 870) occurred with easterly winds in both spring and summer, but with southerly winds in autumn.
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Improvement of MERIS level 2 products in Baltic Sea coastal areas by applying the Improved Contrast between Ocean and Land processor (ICOL) - data analysis and validation
2010. Susanne Kratzer, Christian Vinterhav. Oceanologia 52 (2), 211-236
ArticleIn this paper we compare the following MERIS processors against sea-truthing data: the standard MERIS processor (MEGS 7.4.1), the Case 2 Regional processor (C2R) of the German Institute for Coastal Research (GKSS), and the Case 2 Water Properties processor developed at the Freie Universitat Berlin (FUB). Furthermore, the Improved Contrast between Ocean and Land processor (ICOL), a prototype processor for the correction of adjacency effects from land, was tested on all three processors, and the retrieval of level 2 data was evaluated against sea-truthing data, before and after ICOL processing. The results show that by using ICOL the retrieval of spectral reflectance in the open sea was improved for all processors. After ICOL processing, the FUB showed rather small errors in the blue, but underestimated in the red -34% Mean Normalised Bias (MNB) and 37% Root Mean Square (R,MS). For MEGS the reflectance in the red was underestimated by about -20% MNB and 23% RMS, whereas the reflectance in the other channels was well predicted, even without any ICOL processing. The C2R, underestimated the red with about -27% MNB and 29% RMS and at 412 nm it overestimated the reflectance with about 23% MNB and 29% RMS. At the outer open sea stations ICOL processing did not have a strong effect: the effect of the processor diminishes progressively up to 30 km from land. At the open sea stations the ICOL processor improved chlorophyll retrieval using MEGS from -74% to about 34% MU; and TSM retrieval from -63% to about 22% MNB. Using FUB in combination with ICOL gave even better results for both chlorophyll (25% MNB and 45% RMS) and TSM (-4% MNB and 36% EMS) in the open Baltic Sea. All three processors predicted TSM rather well, but the standard processor gave the best results (-12% MNB and 17% RMS). The C2R had a very low MNB for TSM (1%), but a rather high RMS (54%). The FUB was intermediate with -16% MNB and 31% RMS. In coastal waters, the spectral diffuse attenuation coefficient K-d (490) was well predicted using PUB or MEGS in combination with ICOL (MNB about 12% for FUB and 0.4% for MEGS). Chlorophyll was rather well predicted in the open Baltic Sea using FUB with ICOL (MNB 25%) and even without ICOL processing (MNB about 15%). ICOL-processed MEGS data also gave rather good retrieval of chlorophyll in the coastal areas (MNB of 19% and RMS of 28%). In the open Baltic Sea chlorophyll retrieval gave a MNB of 34% and RMS of 70%, which may be due to the considerable patchiness caused by cyanobacterial blooms. The results presented here indicate that with the MERIS mission, ESA and co-workers are in the process of solving some of the main issues regarding the remote sensing of coastal waters: spatial resolution; land-water adjacency effects; improved level 2 product retrieval in the Baltic Sea, i.e. the retrieval of spectral reflectance and of the water quality products TSM and chlorophyll.
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Using bio-optics to investigate the extent of coastal waters: A Swedish case study
2009. Susanne Kratzer, Paul Tett. Hydrobiologia 629 (1), 169-186
ArticleIn order to develop an optical model to map the extent of coastal waters, the authors analyzed variations in bio-optical constituents and submarine optical properties along a transect from the nutrient-enriched coastal bay, Himmerfjärden, out into the open Baltic Sea. The model is a simple implementation of the “ecosystem approach,” because the optical constituents are proxies for important components of ecosystem state. Yellow substance or colored dissolved organic matter (CDOM) is often a marker for terrestrial freshwater or decay processes in the littoral zone. Phytoplankton pigments, especially chlorophyll a, are used as a proxy for phytoplankton biomass that may be stimulated by fluvial or coastal inputs of anthropogenic nutrients. Suspended particulate matter (SPM) is placed in suspension by tidal or wind-wave stirring of shallow seabeds, and is therefore an indicator for physical forcing. It is the thesis of this article that such constituents, and the optical properties that they control, can be used to provide an ecological definition of the extent of the coastal zone. The spatial distribution of the observations was analyzed using a steady-state model that assumes diffusional transport of bio-optical variables along an axis perpendicular to the coast. According to the model, the resulting distribution along this axis can be described as a low-order polynomial (of order 1–3) when moving from a “source” associated with land to the open-sea “sink.” Order 1 implies conservative mixing, and the higher orders imply significant biological or chemical processes within the gradient. The analysis of the transect data confirmed that the trend of each optical component could be described well using a low-order polynomial. Multiple regression analysis was then used to weigh the contribution of each optical component to the spectral attenuation coefficient K d(490) along the transect. The results showed that in this Swedish Baltic case study, the inorganic fraction of the SPM may be used to distinguish between coastal and open-sea waters, as it showed a clear break between coastal and open-sea waters. Alternative models may be needed for coastal waters in which fronts interrupt the continuity of mixing.
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Using MERIS full resolution data to monitor coastal waters: A case study from Himmerfjärden, a fjord-like bay in the northwestern Baltic Sea
2008. Susanne Kratzer, Carsten Brockmann, Gerald Moore. Remote Sensing of Environment 112 (5), 2284-2300
ArticleIn this paper we investigate if MERIS full resolution (FR) data (300 m) is sufficient to monitor changes in optical constituents in Himmerfjärden, a fjord-like, north– south facing bay of about 30 km length and 4 km width. The MERIS FR products were derived using a coastal processor (FUB Case-2 Plug-In). We also compared the performance between FUB and standard processor (MEGS 7.4), using reduced resolution (RR) data (1 km resolution) from the open Baltic Sea, and compared the products to sea-truthing data. The optical variables measured for seatruthing
were chlorophyll, suspended particulate matter (SPM), as well as coloured dissolved organic matter (CDOM, also termed yellow substances), and the spectral diffuse attenuation coefficient, K d (490). The comparison of the RR data to the sea-truthing data showed that, in the open Baltic Sea, the MERIS standard processor overestimated chlorophyll by about 59%, and SPM by about 28%, and underestimated yellow substance by about 81%, whereas the FUB processor underestimated SPM by about 60%, CDOM by about 78%, and chlorophyll a by about 56%.
The FUB processor showed a relatively high precision for all optical components (standard deviation: 6– 18%), whereas the precision for the MEGS 7.4 was rather low (standard deviation: 43– 73%), except for CDOM (standard deviation: 13%). The analysis of the FR data showed that all FR level 2 water products derived from MERIS followed a polynomial decline in concentration when moving off-shore. The distribution of chlorophyll and SPM was best described by a 2nd order polynomial, and the distribution of CDOM by a 3rd order polynomial, verifying the
diffusional model described in Kratzer and Tett [Kratzer, S. and Tett, P. (in press). Using bio-optics to investigate the extent of coastal waters— a Swedish case study. Hydrobiologia.]. A new K d (490) and Secchi depth algorithm based on MERIS channel 3 (490 nm) and channel 6 (620 nm) each was derived from radiometric sea-truthing data (TACCS, Satlantic). Applying the K d (490) algorithm to the MERIS FR data over Himmerfjärden, and comparing to sea-truthing data the results showed a strong correlation (r =0.94). When comparing the FR data to the seatruthing
data CDOM and K d (490) showed a low accuracy, but a high precision with a rather constant off-set. In summary, one may state that the precision of MERIS data improves by applying the FUB Case-2 processor and the accuracy improves with improved spatial resolution for chlorophyll and SPM. Furthermore, the FUB processor can be used off-the-shelf for open Baltic Sea monitoring, provided one corrects for the respective off-set from sea-truthing data which is most likely caused by an inaccuracy in the atmospheric correction. Additionally, the FR data can
be used to derive CDOM, K d (490) and Secchi depth in Himmmerfjärden if one corrects for the respective off-set. We will need to perform more comparisons between sea-truthing and MERIS FR data before the new K d (490) algorithm can be made operational, including also scenes from other times of year. In order to provide a level 2 product that can be used reliably by the Baltic Sea user community, our recommendation to ESA is to include the spectral attenuation coefficient as a MERIS standard product.
Show all publications by Susanne Kratzer at Stockholm University