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  • Journal article

    Improved hyperspectral inversion of aquatic reflectance under non-uniform vertical mixing

    Simis et al (2022). Improved hyperspectral inversion of aquatic reflectance under non-uniform vertical mixing. Optics Express. , http://doi.org/10.1364/OE.450374
    Abstract

    Estimating the concentration of water constituents by optical remote sensing assumes absorption and scattering processes to be uniform over the observation depth. Using hyperspectral reflectance, we present a method to direct the retrieval of the backscattering coefficient (bb(λ)) from reflectance (> 600 nm) towards wavebands where absorption by water dominates the reflectance curve. Two experiments demonstrate the impact of hyperspectral inversion in the selected band set. First, optical simulations show that the resulting distribution of bb(λ) is sensitive to particle mixing conditions, although a robust indicator of non-uniformity was not found for all scenarios of stratification. Second, in the absence of spectral backscattering profiles from in situ data sets, it is shown how substituting the median of bb(λ) into a near infra-red / red band ratio algorithm improved chlorophyll-a estimates (root mean square error 75.45 mg m-3 became 44.13 mg m-3). This approach also allows propagation of the uncertainty in bb estimates to water constituent concentrations.

  • Journal article

    Characterising retrieval uncertainty of chlorophyll-a algorithms in oligotrophic and mesotrophic lakes and reservoirs.

    Werther et al. (2022). Characterising retrieval uncertainty of chlorophyll-a algorithms in oligotrophic and mesotrophic lakes and reservoirs. . ISPRS-J Photogramm Remote Sens, http://doi.org/10.1016/j.isprsjprs.2022.06.015
    Abstract

    Remote sensing product uncertainties for phytoplankton chlorophyll-a (chla) concentration in oligotrophic and mesotrophic lakes and reservoirs were characterised across 13 existing algorithms using an in situ dataset of water constituent concentrations, inherent optical properties (IOPs) and remote-sensing reflectance spectra Rrsλ collected from 53 lakes and reservoirs (346 observations; chla concentration < 10 mg m-3, dataset median 2.5 mg m-3). Substantial shortcomings in retrieval accuracy were evident with median absolute percentage differences (MAPD) > 37% and mean absolute differences (MAD) > 1.82 mg m-3. Using the Hyperspectral Imager for the Coastal Ocean (HICO) band configuration improved the accuracies by 10–20% compared to the Ocean and Land Colour Instrument (OLCI) configuration. Retrieval uncertainties were attributed to optical and biogeochemical properties using machine learning models through SHapley Additive exPlanations (SHAP). The chla retrieval uncertainty of most semi-analytical algorithms was primarily determined by phytoplankton absorption and composition. Machine learning chla algorithms showed relatively high sensitivity to light absorption by coloured dissolved organic matter (CDOM) and non-algal pigment particulates (NAP). In contrast, the uncertainties of red/near-infrared algorithms, which aim for lower uncertainty in the presence of CDOM and NAP, were primarily explained through the total absorption by phytoplankton at 673 nm (aϕ(673)) and variables related to backscatter. Based on these uncertainty characterisations we discuss the suitability of the evaluated algorithm formulations, and we make recommendations for chla estimation improvements in oligo- and mesotrophic lakes and reservoirs.

  • Journal article

    Determination of optical markers of cyanobacterial physiology from fluorescence kinetics

    Courtecuisse et al. (2022). Determination of optical markers of cyanobacterial physiology from fluorescence kinetics. Journal of Plankton Research, http://doi.org/10.1093/plankt/fbac025
    Abstract

    Compared to other methods to monitor and detect cyanobacteria in phytoplankton populations, fluorometry gives rapid, robust and reproducible results and can be used in situ. Fluorometers capable of providing biomass estimates and physiological information are not commonly optimized to target cyanobacteria. This study provides a detailed overview of the fluorescence kinetics of algal and cyanobacterial cultures to determine optimal optical configurations to target fluorescence mechanisms that are either common to all phytoplankton or diagnostic to cyanobacteria. We confirm that fluorescence excitation channels targeting both phycocyanin and chlorophyll a associated to the Photosystem II are required to induce the fluorescence responses of cyanobacteria. In addition, emission channels centered at 660, 685 and 730 nm allow better differentiation of the fluorescence response between algal and cyanobacterial cultures. Blue-green actinic light does not yield a robust fluorescence response in the cyanobacterial cultures and broadband actinic light should be preferred to assess the relation between ambient light and photosynthesis. Significant variability was observed in the fluorescence response from cyanobacteria to the intensity and duration of actinic light exposure, which needs to be taken into consideration in field measurements.

  • ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters

    Pahlevan N et al (2021). ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters. Remote Sensing of Environment, Volume: 258, http://doi.org/10.1016/j.rse.2021.112366
    Abstract

    Atmospheric correction over inland and coastal waters is one of the major remaining challenges in aquatic remote sensing, often hindering the quantitative retrieval of biogeochemical variables and analysis of their spatial and temporal variability within aquatic environments. The Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity, was initiated to enable a thorough evaluation of eight state-of-the-art atmospheric correction (AC) processors available for Landsat-8 and Sentinel-2 data processing. Over 1000 radiometric matchups from both freshwaters (rivers, lakes, reservoirs) and coastal waters were utilized to examine the quality of derived aquatic reflectances (ρ̂w). This dataset originated from two sources: Data gathered from the international scientific community (henceforth called Community Validation Database, CVD), which captured predominantly inland water observations, and the Ocean Color component of AERONET measurements (AERONET-OC), representing primarily coastal ocean environments. This volume of data permitted the evaluation of the AC processors individually (using all the matchups) and comparatively (across seven different Optical Water Types, OWTs) using common matchups. We found that the performance of the AC processors differed for CVD and AERONET-OC matchups, likely reflecting inherent variability in aquatic and atmospheric properties between the two datasets. For the former, the median errors in ρ̂w560 and ρ̂w664 were found to range from 20 to 30% for best-performing processors. Using the AERONET-OC matchups, our performance assessments showed that median errors within the 15–30% range in these spectral bands may be achieved. The largest uncertainties were associated with the blue bands (25 to 60%) for best-performing processors considering both CVD and AERONET-OC assessments. We further assessed uncertainty propagation to the downstream products such as near-surface concentration of chlorophyll-a (Chla) and Total Suspended Solids (TSS). Using satellite matchups from the CVD along with in situ Chla and TSS, we found that 20–30% uncertainties in ρ̂w490≤λ≤743nm yielded 25–70% uncertainties in derived Chla and TSS products for top-performing AC processors. We summarize our results using performance matrices guiding the satellite user community through the OWT-specific relative performance of AC processors. Our analysis stresses the need for better representation of aerosols, particularly absorbing ones, and improvements in corrections for sky- (or sun-) glint and adjacency effects, in order to achieve higher quality downstream products in freshwater and coastal ecosystems.

  • Journal article

    Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data

    Burggraaff O, Werther M, Boss E, Simis S, Snik F (2022). Accuracy and Reproducibility of Above-Water Radiometry With Calibrated Smartphone Cameras Using RAW Data. Front. Remote Sens.,, http://doi.org/10.3389/frsen.2022.940096
    Abstract

    Consumer cameras, especially on smartphones, are popular and effective instruments for above-water radiometry. The remote sensing reflectance Rrs is measured above the water surface and used to estimate inherent optical properties and constituent concentrations. Two smartphone apps, HydroColor and EyeOnWater, are used worldwide by professional and citizen scientists alike. However, consumer camera data have problems with accuracy and reproducibility between cameras, with systematic differences of up to 40% in intercomparisons. These problems stem from the need, until recently, to use JPEG data. Lossless data, in the RAW format, and calibrations of the spectral and radiometric response of consumer cameras can now be used to significantly improve the data quality. Here, we apply these methods to above-water radiometry. The resulting accuracy in Rrs is around 10% in the red, green, and blue (RGB) bands and 2% in the RGB band ratios, similar to professional instruments and up to 9 times better than existing smartphone-based methods. Data from different smartphones are reproducible to within measurement uncertainties, which are on the percent level. The primary sources of uncertainty are environmental factors and sensor noise. We conclude that using RAW data, smartphones and other consumer cameras are complementary to professional instruments in terms of data quality. We offer practical recommendations for using consumer cameras in professional and citizen science.

  • Journal article

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

    T. Jordan, S. Simis, P. Grötsch and J Wood (2022). Incorporating a Hyperspectral Direct-Diffuse Pyranometer in an Above-Water Reflectance Algorithm. Remote Sens, Pages: 14(10), 2491, http://doi.org/10.3390/rs14102491
    Abstract

    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

  • Journal article

    Community monitoring of coliform pollution in Lake Tanganyika

    H. Anold Moshi, D. Shilla, I Kimirei, C O'Reilly, W Clymans, I Bishop, S Loiselle (2022). Community monitoring of coliform pollution in Lake Tanganyika. PLOS ONE, http://doi.org/10.1371/journal.pone.0262881
    Abstract

    Conventional water quality monitoring has been done for decades in Lake Tanganyika, under different national and international programs. However, these projects utilized monitoring approaches, which were temporally limited, labour intensive and costly. This study examines the use of citizen science to monitor the dynamics of coliform concentrations in Lake Tanganyika as a complementary method to statutory and project-focused measurements. Persons in five coastal communities (Kibirizi, Ilagala, Karago, Ujiji and Gombe) were trained and monitored total coliforms, faecal coliforms and turbidity for one year on a monthly basis, in parallel with professional scientists. A standardized and calibrated Secchi tube was used at the same time to determine turbidity. Results indicate that total and faecal coliform concentrations determined by citizen scientists correlated well to those determined by professional scientists. Furthermore, citizen scientist-based turbidity values were shown to provide a potential indicator for high FC and TC concentrations. As a simple tiered approach to identify increased coliform loads, trained local citizen scientists could use low-cost turbidity measurements with follow up sampling and analysis for coliforms, to inform their communities and regulatory bodies of high risk conditions, as well as to validate local mitigation actions. By comparing the spatial and temporal dynamics of coliform concentrations to local conditions of infrastructure, population, precipitation and hydrology in the 15 sites (3 sites per community) over 12 months, potential drivers of coliform pollution in these communities were identified, largely related to precipitation dynamics and the land use.

  • Technical note

    Validation of S3 OLCI observations using one year of semi-continuous WISPstation measurementsin the high dynamic area of the Eems Estuary

    Peters S. et al (2020). Validation of S3 OLCI observations using one year of semi-continuous WISPstation measurementsin the high dynamic area of the Eems Estuary. http://doi.org/10.5281/zenodo.4570188
    Abstract

    The Eems Estuary is a very dynamic area featuring highly variable turbidity and Chlorophyll-a values. There is an interest to decrease theturbidity and monitoring is being put into place to observe the current status and changes. Remote sensing using Sentinel 3 OLCIobservations is a candidate monitoring technique but should provide robust and validated results.
    Obtaining high quality turbidity estimates starts with validated Bottom of Atmosphere reflectances.
    To validate BOA reflectances a WISPstation (Peters et al., 2019) was placed on a fixed structure in open water at 53.4743N and 6.8216Wfrom 13-11-2018 until 05-11-2019. The WISPstation contains 2 sets of sensors (Lup: 40 degrees, Lsky: 40 degrees and Ed): measurementswere taken in two directions, N and NE. Some shadowing of the Ed sensors occurred and needed to be filtered out.

  • Journal article

    New Radiometric Approaches to Compute Underwater Irradiances: Potential Applications for High-Resolution and Citizen Science-Based Water Quality Monitoring Programs

    C. Rodero, E. Olmedo, R. Bardaji and J. Piera (2021). New Radiometric Approaches to Compute Underwater Irradiances: Potential Applications for High-Resolution and Citizen Science-Based Water Quality Monitoring Programs . Sensors, Volume: 21(16), Pages: 5537, http://doi.org/10.3390/s21165537
    Abstract

    Measuring the diffuse attenuation coefficient (Kd) allows for monitoring the water body’s environmental status. This parameter is of particular interest in water quality monitoring programs because it quantifies the presence of light and the euphotic zone’s depth. Citizen scientists can meaningfully contribute by monitoring water quality, complementing traditional methods by reducing monitoring costs and significantly improving data coverage, empowering and supporting decision-making. However, the quality of the acquisition of in situ underwater irradiance measurements has some limitations, especially in areas where stratification phenomena occur in the first meters of depth. This vertical layering introduces a gradient of properties in the vertical direction, affecting the associated Kd. To detect and characterize these variations of Kd in the water column, it needs a system of optical sensors, ideally placed in a range of a few cm, improving the low vertical accuracy. Despite that, the problem of self-shading on the instrumentation becomes critical. Here, we introduce a new concept that aims to improve the vertical accuracy of the irradiance measurements: the underwater annular irradiance (Ea). This new concept consists of measuring the irradiance in an annular-shaped distribution. We first compute the optimal annular angle that avoids self-shading and maximizes the light captured by the sensors. Second, we use different scenarios of water types, solar zenith angle, and cloud coverage to assess the robustness of the corresponding diffuse attenuation coefficient, Ka. Finally, we derive empirical functions for computing Kd from Ka. This new concept opens the possibility to a new generation of optical sensors in an annular-shaped distribution which is expected to (a) increase the vertical resolution of the irradiance measurements and (b) be easy to deploy and maintain and thus to be more suitable for citizen scientists.

  • Journal article

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

    M. Warren, S. Simis, N. Selmes (2021). Complementary water quality observations from high and medium resolution Sentinel sensors by aligning chlorophyll-a and turbidity algorithms. Remote Sensing of Environment, Volume: 265, http://doi.org/10.1016/j.rse.2021.112651
    Abstract

    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.

  • Book chapter

    Stakeholder engagement in water quality research: A case study based on the Citclops and MONOCLE projects

    Ceccaroni, L., & Piera, J (2018). Stakeholder engagement in water quality research: A case study based on the Citclops and MONOCLE projects. Citizen Science: Innovation in Open Science, Society and Policy , Pages: 201-209, http://doi.org/10.14324/111.9781787352339
  • Journal article

    Standardized spectral and radiometric calibration of consumer cameras

    O. Burggraaff, N. Schmidt, J. Zamorano, K. Pauly, S. Pascual, C. Tapia, E. Spyrakos, and F. Snik (2019). Standardized spectral and radiometric calibration of consumer cameras. Optics Express, Volume: 27, Pages: 19075-19101, http://doi.org/10.1364/OE.27.019075
    Abstract

    Consumer cameras, particularly onboard smartphones and UAVs, are now commonly used as scientific instruments. However, their data processing pipelines are not optimized for quantitative radiometry and their calibration is more complex than that of scientific cameras. The lack of a standardized calibration methodology limits the interoperability between devices and, in the ever-changing market, ultimately the lifespan of projects using them. We present a standardized methodology and database (SPECTACLE) for spectral and radiometric calibrations of consumer cameras, including linearity, bias variations, read-out noise, dark current, ISO speed and gain, flat-field, and RGB spectral response. This includes golden standard ground-truth methods and do-it-yourself methods suitable for non-experts. Applying this methodology to seven popular cameras, we found high linearity in RAW but not JPEG data, inter-pixel gain variations >400% correlated with large-scale bias and read-out noise patterns, non-trivial ISO speed normalization functions, flat-field correction factors varying by up to 2.79 over the field of view, and both similarities and differences in spectral response. Moreover, these results differed wildly between camera models, highlighting the importance of standardization and a centralized database.

  • Journal article

    Biases from incorrect reflectance convolution

    O.Burggraaff (2020). Biases from incorrect reflectance convolution. Optics Express, Volume: 28, Issue 9, Pages: 13801-13816, http://doi.org/10.1364/OE.391470
    Abstract

    Reflectance, a crucial earth observation variable, is converted from hyperspectral to multispectral through convolution. This is done to combine time series, validate instruments, and apply retrieval algorithms. However, convolution is often done incorrectly, with reflectance itself convolved rather than the underlying (ir)radiances. Here, the resulting error is quantified for simulated and real multispectral instruments, using 18 radiometric data sets (N = 1799 spectra). Biases up to 5% are found, the exact value depending on the spectrum and band response. This significantly affects extended time series and instrument validation, and is similar in magnitude to errors seen in previous validation studies. Post-hoc correction is impossible, but correctly convolving (ir)radiances prevents this error entirely. This requires publication of original data alongside reflectance.

  • Conference paper

    iSPEX 2: A universal smartphone add-on for portable spectroscopy and polarimetry

    O. Burggraaff, A. Perdujin, R. van Hek, N. Schmidt, C. Keller and F. Snik (2020). iSPEX 2: A universal smartphone add-on for portable spectroscopy and polarimetry. Proc. SPIE 11389, Micro- and Nanotechnology Sensors, Systems, and Applications XII, 113892K, http://doi.org/10.1117/12.2558562
    Abstract

    Spectropolarimetry is a powerful technique for remote sensing of the environment. It enables the retrieval of particle shape and size distributions in air and water to an extent that traditional spectroscopy cannot. SPEX is an instrument concept for spectropolarimetry through spectral modulation, providing snapshot, and hence accurate, hyperspectral intensity and degree and angle of linear polarization. Successful SPEX instruments have included groundSPEX and SPEX airborne, which both measure aerosol optical thickness with high precision, and soon SPEXone, which will fly on PACE. Here, we present a low-cost variant for consumer cameras, iSPEX 2, with universal smartphone support. Smartphones enable citizen science measurements which are significantly more scaleable, in space and time, than professional instruments. Universal smartphone support is achieved through a modular hardware design and SPECTACLE data processing. iSPEX 2 will be manufactured through injection molding and 3D printing. A smartphone app for data acquisition and processing is in active development. Production, calibration, and validation will commence in the summer of 2020. Scientific applications will include citizen science measurements of aerosol optical thickness and surface water reflectance, as well as low-cost laboratory and portable spectroscopy.

  • Technical note

    Construction of the Solar-tracking Radiometry platform (So-Rad)

    A. Wright & S. Simis. (2021). Construction of the Solar-tracking Radiometry platform (So-Rad). Zenodo, http://doi.org/10.5281/zenodo.4485805
    Abstract

    The purpose of the Solar-tracking Radiometry platform is to maintain optimal viewing angles of radiance sensors recording water-leaving reflectance (water colour), avoiding sun glint and platform shading even from moving platforms such as ships or buoys. The system is developed to operate autonomously, with low power consumption, integrating commercially available (ir)radiance sensors and providing remote connectivity. All hardware and software are open-source, through this repository and the associated software repository (https://github.com/monocle-h2020/so-rad). Their use is licensed under a creative commons non-commercial license.

  • Journal article

    Citizen science with colour blindess: A case study on the Forel-Ule scale

    O. Burggraaff, S. Panchagnula, F. Snik (2021). Citizen science with colour blindess: A case study on the Forel-Ule scale. PLOS ONE, Volume: 16(4): e0249755, http://doi.org/10.1371/journal.pone.0249755
    Abstract

    Many citizen science projects depend on colour vision. Examples include classification of soil or water types and biological monitoring. However, up to 1 in 11 participants are colour blind. We simulate the impact of various forms of colour blindness on measurements with the Forel-Ule scale, which is used to measure water colour by eye with a 21-colour scale. Colour blindness decreases the median discriminability between Forel-Ule colours by up to 33% and makes several colour pairs essentially indistinguishable. This reduces the precision and accuracy of citizen science data and the motivation of participants. These issues can be addressed by including uncertainty estimates in data entry forms and discussing colour blindness in training materials. These conclusions and recommendations apply to colour-based citizen science in general, including other classification and monitoring activities. Being inclusive of the colour blind increases both the social and scientific impact of citizen science.

  • Journal article

    Meta-classification of remote sensing reflectance to estimate trophic status of inland and nearshore waters

    M . Werther, E. Spyrakos, S. Simis, D. Odermatt, K. Stelzer, H. Krawczyk, O. Berlage, P. Hunter, A. Tyler (2021). Meta-classification of remote sensing reflectance to estimate trophic status of inland and nearshore waters. ISPRS Journal of Photogrammetry and Remote Sensing, Volume: 176, Pages: 109-126, http://doi.org/10.1016/j.isprsjprs.2021.04.003
    Abstract

    Common aquatic remote sensing algorithms estimate the trophic state (TS) of inland and nearshore waters through the inversion of remote sensing reflectance (Rrs (λ)) into chlorophyll-a (chla) concentration. In this study we present a novel method that directly inverts Rrs (λ)) into TS without prior chla retrieval. To successfully cope with the optical diversity of inland and nearshore waters the proposed method stacks supervised classification algorithms and combines them through meta-learning. We demonstrate the developed methodology using the waveband configuration of the Sentinel-3 Ocean and Land Colour Instrument on 49 globally distributed inland and nearshore waters (567 observations). To assess the performance of the developed approach, we compare the results with TS derived through optical water type (OWT) switching of chla retrieval algorithms. Meta-classification of TS was on average 6.75% more accurate than TS derived via OWT switching of chla algorithms. The presented method achieved 90% classification accuracies for eutrophic and hypereutrophic waters and was 12% more accurate for oligotrophic waters than derived through OWT chla retrieval. However, mesotrophic waters were estimated with lower accuracy from both our developed method and through OWT chla retrieval (52.17% and 46.34%, respectively), highlighting the need for improved base algorithms for low - moderate biomass waters. Misclassified observations were characterised by highly absorbing and/or scattering optical properties for which we propose adaptations to our classification strategy.

  • Journal article

    Consistency between satellite ocean colour products under high coloured dissolved organic matter absorption in the Baltic Sea.

    G. Tilstone, S. Pardo, S. Simis, P. Qin, N. Selmes, D. Dessailly, E. Kwiatkowska (2021). Consistency between satellite ocean colour products under high coloured dissolved organic matter absorption in the Baltic Sea.. http://doi.org/10.3390/rs14010089
    Abstract

    Ocean colour (OC) remote sensing is an important tool for monitoring phytoplankton in the global ocean. In optically complex waters such as the Baltic Sea, relatively efficient light absorption by substances other than phytoplankton increases product uncertainty. Sentinel-3 OLCI-A, Suomi-NPP VIIRS and MODIS-Aqua OC radiometric products were assessed using Baltic Sea in situ remote sensing reflectance (Rrs) from ferry tracks (Alg@line) and at two Aerosol Robotic Network for Ocean Colour (AERONET-OC) sites from April 2016 to September 2018. A range of atmospheric correction (AC) processors for OLCI-A were evaluated. POLYMER performed best with <23 relative % difference at 443, 490 and 560 nm compared to in situ Rrs and 28% at 665 nm, suggesting that using this AC for deriving Chl a will be the most accurate. Suomi-VIIRS and MODIS-Aqua underestimated Rrs by 35, 29, 22 and 39% and 34, 22, 17 and 33% at 442, 486, 560 and 671 nm, respectively. The consistency between different AC processors for OLCI-A and MODIS-Aqua and VIIRS products was relatively poor. Applying the POLYMER AC to OLCI-A, MODIS-Aqua and VIIRS may produce the most accurate Rrs and Chl a products and OC time series for the Baltic Sea.