Search

Medium Resolution Imaging Spectrometer (MERIS) satellite data on chlorophyll a (Chl-a, μg L−1) and cyanobacteria (Cyan, %) content in Hartbeespoort Dam (HBPD) and 6 “control” reservoirs between 200...

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions.

A hyperspectral inversion algorithm was used to distinguish between cyanobacteria and algal blooms in optically complex inland waters. A framework for the algorithm is presented that incorporates a bio-optical model, a solution for the radiative transfer equation using the EcoLight-S radiative transfer model, and a non-linear optimization procedure. The natural variability in the size of phytoplankton populations was simulated using a two-layered sphere model that generated size-specific inherent optical properties (IOPs). The algorithm effectively determined the type of high-biomass blooms in terms of the relative percentage species composition of cyanobacteria. It also provided statistically significant estimates of population size (as estimated by the effective diameter), chlorophyll-a (chl-a) and phycocyanin pigment concentrations, the phytoplankton absorption coefficient, and the non-algal absorption coefficient. The algorithm framework presented here can in principle be adapted for distinguishing between phytoplankton groups using satellite and in situ remotely sensed reflectance.

Satellite remote sensing can make a significant contribution to monitoring water quality in South African standing water bodies. Eutrophication, defined as enrichment by nutrients, and toxin-producing cyanobacteria (blue-green algae) blooms pose a significant threat to the quality of South African surface water bodies. The status and trends of chlorophyll a (chl-a, a proxy for eutrophication), cyanobacterial blooms and cyanobacterial surface scum were determined for South Africa’s 50 largest water bodies between 2002 and 2012, using a recently developed algorithm and 10 years of data from the Medium Resolution Imaging Spectrometer (MERIS) satellite. The majority (62%) of the 50 water bodies were highly nutrient enriched or hypertrophic, while 26 had cyanobacterial blooms which posed a high health risk from surface scums. This study is the first of its kind to provide quantitative water quality information for South Africa’s water bodies from a time series of satellite remotely sensed data. We demonstrate the pivotal role that satellite remote sensing can play in greatly supplementing in-situ monitoring efforts such as the National Eutrophication Monitoring Programme. The finding that many water supply bodies are severely impacted by eutrophication and cyanobacterial blooms confirms that these remain issues of critical concern for water security and supply in South Africa.

In South Africa, little is known about the production of microcystin by the genus Anabaena Bory. In April 2012, during a cyanobacterial bloom event in Theewaterskloof Dam, Western Cape province, the plankton was sampled on 10 occasions. The dominant algae belonged to the genus Anabaena, a family of filamentous cyanobacteria known to produce cyanotoxins such as anatoxin-a, harmful to humans and the aquatic foodweb. The specimens isolated lacked the characteristic akinetes and/or heterocysts associated with this genus. Therefore the 16S rRNA gene was Sanger sequenced and a maximum parsimony tree was constructed, confirming its identity as Anabaena ucrainica (Schkorbatow) M. Watanabe. Enzyme-linked immunosorbent assay (ELISA) confirmed the presence of microcystin-LR in the isolated A. ucrainica field sample, while PCR analysis and sequencing further confirmed the presence of mcy genes in this species. It was speculated from the data that prevailing low water-column temperatures and strong gusty winds may hav...

This short communication describes several previously undocumented processing steps, pixel flagging procedures, and improvements made to the maximum peak height (MPH) algorithm, which is aimed at the operational detection of chlorophyll a (chl-a) and cyanobacteria blooms in inland and near-coastal waters. The improvements reduce false-positive cyanobacteria detection in oligotrophic waters; enable pixels in clear waters affected by environmental radiances (stray light) to be identified; and enhance detection of floating aquatic vegetation. Several case studies from around the globe are used to illustrate these improvements, and demonstrate new pixel flagging procedures and algorithm operation. The algorithm was validated using a large in situ dataset for chl-a from a wide range of inland water types. The MPH chl-a estimates were more stable than the fluorescence line height (FLH) and maximum chlorophyll index (MCI) values. The results demonstrate the potential for using the MPH algorithm, now released as a plug-in for the Basic ENVISAT A(ATSR) and MERIS (BEAM) processing toolbox, as a standard product for estimating chl-a (and trophic status) in inland and near-coastal waters using MERIS and the forthcoming Sentinel-3 Ocean and Land Colour Instrument.

Eutrophication and increasing prevalence of potentially toxic cyanobacterial blooms among global inland water bodies is becoming a major concern and requires direct attention. The European Space Agency recently launched the Ocean and Land Color Instrument (OLCI) aboard the Sentinel 3 satellite. The success of the mission will depend on extensive validation efforts for the development of accurate and robust in-water algorithms. In this study, four full atmospheric correction methods are assessed over four inland water reservoirs in South Africa, along with a suite of red/NIR based semi-analytic and band difference models for chl-a estimation which were applied to both full and partial atmospherically corrected data. In addition, we tested a novel duplicate pixel correction method to account for duplicate pixels induced by high observation zenith angles. Radiometric errors associated with OLCI Top of Atmosphere (TOA) radiances over small water targets were also investigated by modeling in situ reflectance measurements to at-sensor radiances using MODTRAN. Of the four atmospheric corrections, the 6SV1 radiative transfer code showed the most promise for producing reasonable reflectances when compared to in-situ measurements. Empirically derived band difference models outperformed all other chl-a retrieval methods on both partially and fully corrected reflectances. The Maximum Peak Height (MPH) algorithm applied to Bottom of Rayleigh Reflectance (BRR) performed best overall (R2 = 0.55, RMSE(%) = 99), while the Maximum Chlorophyll Index (MCI) performed best on atmospherically corrected data using 6SV1 (R2 = 0.35, RMSE(%) = 107). Semi-analytic chl-a retrieval methods proved very successful when applied to in situ Rrs, however, are not reliable when applied to low quality reflectance data. The SIMilarity Environment Correction (SIMEC), an adjacency correction applied in conjunction with the image correction for atmospheric effects (iCOR) processor, did not improve retrieval results for these small water targets.

The medium resolution imaging spectrometer full resolution (MERIS FR) archive (2002 to 2012) over South Africa has been processed with the maximum peak height (MPH) algorithm for the 50 largest standing water bodies in South Africa. Time series of chlorophyll a (chl-a), cyanobacteria and surface scum area coverage were used to establish the status, seasonality and trends for each of the water bodies. The majority (62%) of the 50 water bodies were hypertrophic (mean chl-a > 30 mg m− 3), while 23 water bodies had intermediate to extensive cyanobacteria coverage. Cyanobacterial surface scum events posing a high health risk occurred in 26 of the water bodies in varying extents. Analysis of significant trends showed that water bodies both worsened and improved with regard to eutrophication, cyanobacteria and surface scum coverage between 2005 and 2012. Validation of the MPH algorithm using an independent in situ dataset demonstrated that gross trophic status through chl-a can be accurately determined in both eukaryote and cyanobacteria-dominant waters. Chl-a estimation in oligo/mesotrophic waters remains challenging due to a wide range of potential sources of error. This study is the first of its kind providing quantitative chl-a and phytoplankton species information in lakes from a time series of satellite remotely sensed data on a sub-continental scale, demonstrating how global analyses of changes in lake biogeochemistry might be performed in the future. It demonstrates the pivotal role that satellite remote sensing can play in supplementing in situ monitoring efforts, particularly in the developing world. The study concludes that eutrophication and cyanobacterial blooms are widespread in South African water bodies and remain issues of critical concern for water quality.

A two-layered sphere model is used to investigate the impact of gas vacuoles on the inherent optical properties (IOPs) of the cyanophyte Microcystis aeruginosa. Enclosing a vacuole-like particle within a chromatoplasm shell layer significantly altered spectral scattering and increased backscattering. The two-layered sphere model reproduced features in the spectral attenuation and volume scattering function (VSF) that have previously been attributed to gas vacuoles. This suggests the model is good at least as a first approximation for investigating how gas vacuoles alter the IOPs. Measured Rrs was used to provide a range of values for the central value of the real refractive index, 1 + ε, for the shell layer using measured IOPs and a radiative transfer model. Sufficient optical closure was obtained for 1 + ε between 1.1 and 1.14, which had corresponding Chl a-specific phytoplankton backscattering, bbφ*, between 3.9 and 7.2 × 10−3 m2 mg−1 at 510 nm. The bbφ* values are in close agreement with the literature and in situ particulate backscattering measurements. Rrs simulated for a population of vacuolate cells was greatly enlarged relative to a homogeneous population. A sensitivity analysis of empirical algorithms for estimating Chl a in eutrophic/hypertrophic waters suggests these are robust under variable constituent concentrations and likely to be species-sensitive. The study confirms that gas vacuoles cause significant increase in backscattering and are responsible for the high Rrs values observed in buoyant cyanobacterial blooms. Gas vacuoles are therefore one of the most important bio-optical substructures influencing the IOPs in phytoplankton.

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

This chapter provides an overview of current methods for estimating the concentration of chlorophyll-a (chl-a) pigment from remotely sensed reflectance measurements made from space, airborne and ground-based instruments. It reviews the fundamental principles of the “optical pathways” for obtaining chl-a concentration information, including absorption, sun-induced chl-a fluorescence, and particulate cellular (back)scattering, while highlighting the challenges associated with cyanobacteria versus algae as distinct phytoplankton groups; and presents current techniques (algorithms) likely to offer the greatest value with simple, robust implementation. It assesses the utility of available satellite sensors for estimating chl-a, and the likely sensitivity of chl-a measurements made from space given instrument and biophysical constraints.

A novel algorithm is presented for detecting trophic status (chlorophyll-a), cyanobacterial blooms, surface scum and floating vegetation in coastal and inland waters using top-of-atmosphere data from the Medium Resolution Imaging Spectrometer (MERIS). The maximum peak-height algorithm (MPH) uses a baseline subtraction procedure to calculate the height of the dominant peak across the red and near-infrared MERIS bands between 664 and 885 nm caused by sun-induced chlorophyll fluorescence (SICF) and particulate backscatter. Atmospheric correction of the MERIS TOA reflectance data for gaseous absorption and Rayleigh scattering proved adequate given the spectral proximity of the relevant bands and the sufficiently large differential spectral signal. This avoided the need to correct for atmospheric aerosols, a procedure which is typically prone to large errors in turbid and high-biomass waters. A combination of switching algorithms for estimating chl-a were derived from coincident in situ chl-a and MERIS bottom-of-Rayleigh reflectance measurements. These algorithms are designed to cover a wide trophic range, from oligotrophic/mesotrophic waters (chl-a 20 mg m− 3) and surface scums or dry floating algae or vegetation. Cyanobacteria-dominant waters were differentiated from those dominated by eukaryote algal species (dinoflagellates/diatoms) on the basis of the magnitude of the MPH variable. This is supported by evidence that vacuolate cyanobacteria (Microcystis aeruginosa) possess enhanced chl-a specific backscatter which is an important bio-optical distinguishing feature. This enables these phytoplankton groups to be distinguished from space. An algorithm derived from cyanobacteria-dominant waters had a r2 value of 0.58 for chl-a between 33 and 362 mg m− 3 and an error of 33.7% (N = 17). The operational algorithm for eukaryote-dominant algal assemblages gave a coefficient of determination of 0.71 and a mean absolute percentage error of 60% for chl-a in the range 0.5–350 mg m− 3 (N = 48). A flag based on cyanobacteria-specific spectral pigmentation and fluorescence features was used to identify cyanobacterial-dominance in eutrophic waters. Global applications demonstrate how the MPH algorithm can offer rapid and effective assessment of trophic status, cyanobacterial-dominance, surface scums and floating vegetation in inland and coastal waters.

The empirical approach of remote sensing has a proven capability to provide timely and accurate information on inland and near-coastal transitional waters. This article gives a thorough review of empirical algorithms for quantitatively estimating a variety of parameters from space-borne, airborne and in situ remote sensors in inland and transitional waters, including chlorophyll-a, total suspended solids, Secchi disk depth (z SD), turbidity, absorption by coloured dissolved organic matter (a CDOM) and other parameters, for example, phycocyanin. Current remote-sensing instruments are also reviewed. The theoretical basis of the empirical algorithms is given using fundamental bio-optical theory of the inherent optical properties (IOPs). Bands, band ratios and band arithmetic algorithms that could be used to produce common biogeophysical products for inland/transitional waters are identified. The article discusses the potential role that empirical algorithms could play alongside more advanced model-based algo...

Eutrophication and cyanobacterial algal blooms present an increasing threat to the health of freshwater ecosystems and to humans who use these resources for drinking and recreation. Remote sensing is being used increasingly as a tool for monitoring these phenomena in inland and near-coastal waters. This study uses the Medium Resolution Imaging Spectrometer (MERIS) to view Zeekoevlei, a small hypertrophic freshwater lake situated on the Cape Flats in Cape Town, South Africa, dominated by Microcystis cyanobacteria. The lake's small size, highly turbid water, and covariant water constituents present a challenging case for both algorithm development and atmospheric correction. The objectives of the study are to assess the optical properties of the lake, to evaluate various atmospheric correction procedures, and to compare the performance of empirical and semi-analytical algorithms in hypertrophic water. In situ water quality parameter and radiometric measurements were made simultaneous to MERIS overpasses. Upwelling radiance measurements at depth 0.66 m were corrected for instrument self-shading and processed to water-leaving reflectance using downwelling irradiance measurements and estimates of the vertical attenuation coefficient for upward radiance, K u , generated from a simple bio-optical model estimating the total absorption, a ( λ ), and backscattering coefficients, b b ( λ ). The normalised water-leaving reflectance was used for assessing the accuracy of image-based Dark Object Subtraction and 6S Radiative Transfer Code atmospheric correction procedures applied to MERIS. Empirical algorithms for estimating chlorophyll a (Chl a ), Total Suspended Solids (TSS), Secchi Disk depth ( z SD ) and absorption by CDOM ( a CDOM ) were derived from simultaneously collected in situ and MERIS measurements. The empirical algorithms gave high correlation coefficient values, although they have a limited ability to separate between signals from covariant water constituents. The MERIS Neural Network algorithms utilised in the standard Level 2 Case 2 waters product and Eutrophic Lakes processor were also used to derive water constituent concentrations. However, these failed to produce reasonable comparisons with in situ measurements owing to the failure of atmospheric correction and divergence between the optical properties and ranges used to train the algorithms and those of Zeekoevlei. Maps produced using the empirical algorithms effectively show the spatial and temporal variability of the water quality parameters during April 2008. On the basis of the results it is argued that MERIS is the current optimal sensor for frequent change detection applications in inland waters. This study also demonstrates the considerable potential value for simple TOA algorithms for hypertrophic systems. It is recommended that regional algorithm development be prioritized in southern Africa and that remote sensing be integrated into future operational water quality monitoring systems.

The Benguela, as a highly productive upwelling system, suffers from the occurrence of a variety of harmful algal blooms, most of which are associated with elevated biomass; a feature common to the shelf environment of upwelling systems. Most harmful blooms have in the past been attributed to one or another dinoflagellate species, but more recently harmful impacts have also been ascribed to other groups of phytoplankton, including diatom and autotrophic ciliate species. Typical bloom assemblages, forcing mechanisms and harmful impacts are outlined, and bloom types most amenable to detection with ocean colour radiometry are identified. Inherent and apparent optical properties of these algal assemblage types are described, and a preliminary evaluation is made of the suitability of available ocean colour data and algorithms. The evolution of several bloom events is described using various algorithms applied to ocean colour data from the Medium Resolution Imaging Spectrometer (MERIS), and recommendations are made about optimal ocean colour usage for high biomass algal blooms in coastal zones.

The accurate description of a water body's volume scattering function (VSF), and hence its phase functions, is critical to the determination of the constituent inherent optical properties (IOPs), the associated spectral water-leaving reflectance, and consequently the retrieval of phytoplankton functional type (PFT) information. The equivalent algal populations (EAP) model has previously been evaluated for phytoplankton-dominated waters, and offers the ability to provide phytoplankton population-specific phase functions, unveiling a new opportunity to further understanding of the causality of the PFT signal. This study presents and evaluates the wavelength dependent, spectrally variable EAP particle phase functions and the subsequent effects on water-leaving reflectance. Comparisons are made with frequently used phase function approximations e.g. the Fournier Forand formulation, as well as with phase functions inferred from measured VSFs in coastal waters. Relative differences in shape and magnitude are quantified. Reflectance modelled with the EAP phase functions is then compared against measured reflectance data from phytoplankton-dominated waters. Further examples of modelled phytoplankton-dominated waters are discussed with reference to choice of phase function for two PFTs (eukaryote and prokaryote) across a range of biomass. Finally a demonstration of the sensitivity of reflectance due to the choice of phase function is presented. The EAP model phase functions account for both spectral and angular variability in phytoplankton backscattering i.e. they display variability which is both spectral and shape-related. It is concluded that phase functions modelled in this way are necessary for investigating the effects of assemblage variability on the ocean colour signal, and should be considered for model closure even in relatively low scattering conditions where phytoplankton dominate the IOPs.

We regret that the Rrs spectra shown for the EAP modelled high biomass validation in Fig. 7 [Opt. Express, 22, 16745 (2014)] are incorrect. They are corrected here. The closest match of modelled to measured effective diameter is for a generalised 16 μm dinoflagellate population and not a 12 μm one as previously stated. These corrections do not affect the discussion or the conclusions of the paper.

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.