An optical system for detecting and describing major algal blooms in coastal and oceanic waters around India

Abstract

An optical system is developed with the aim to detect and monitor three major algal blooms (including harmful algal blooms ''HABs'') over ecologically relevant scales around India and to strengthen algal forecasting system. This system is designed to be capable of utilizing remote sensing, in situ, and radiative transfer techniques to provide species-specific data necessary for increasing capabilities of an algal forecasting system. With the ability to measure in-water optical properties by means of remote sensing and in situ observations, the optical system developed infers the desired phytoplankton signal from spectral distributions and utilize these data in a numerical classification technique to generate species-specific maps at given spatial and temporal scales. A simple radiative transfer model is adopted for this system to provide a means to optimally interpolate to regions with sparse in situ observation data and to provide a central component to generate in-water optical properties from remotely sensed data. For a given set of inherent optical properties along with surface and bottom boundary conditions, the optical system potentially provides researchers and managers coverage at different locations and depths for tracking algal blooms in the water column. Three major algal blooms focused here include Noctiluca scintillans/miliaris, Trichodesmium erythraeum, and Cochlodinium polykrikoides, which are recurring events in coastal and oceanic waters around India. Because satellite sensors provide a synoptic view of the ocean, both spatially and temporally, our initial efforts tested this optical system using several MODIS-Aqua images and ancillary data. Validation of the results with coincident in situ data obtained from either surface samples or depth samples demonstrated the robustness and potential utility of this approach, with an accuracy of 80-90% for delineating the presence of all three blooms in a heterogeneous phytoplankton community. Despite its limitation in detecting specific species during their prebloom phases and indicating whether a particular bloom is toxic or harmful, the proposed optical system will provide managers with the specific phytoplankton bloom maps to structure monitoring efforts and a powerful tool for studying the dynamics of algal blooms at various temporal and spatial scales.

Remotely sensing harmful algal blooms in the Red Sea

“…MODIS-Aqua datasets, corresponding to the time periods where previous in situ data are available, were acquired to: a) train the model, and b) validate the model results (Table 1). The satellite data were processed to Level 2 using the new atmospheric correction algorithm incorporated in the SeaDAS software (version 7.5) [19,34]. Data products that were extracted from the Level 2 MODIS-Aqua files included remote sensing reflectance ( R rs ) (for wavelengths 412, 443, 488, 531, 547, 667, 678, and 748 nm), and the algal bloom index (ABI) derived Chl-a concentration.…”

“…Examples of the R rs spectra of these HABs in the MODIS-Aqua wavelengths are shown in Fig 3. We note that each HAB species has its unique absorption and backscattering characteristics [19, 39–42] (see S1 and S2 Figs for particulate absorption and backscattering spectra). For instance, the raphidophyte H. akashiwo exhibits high R rs values at 531 and 547 nm, which implies low absorption of pigment concentrations (including fucoxanthin and diadinoxanthin) with high backscattering coefficients at these wavelengths.…”

“…The R rs spectra of the dinoflagellate N. scintillans/miliaris exhibits two distinct peaks: one at ~ 531 nm and the other at ~ 678 nm (Fig 3d) [41]. The first peak is due to low absorption and high backscattering caused by a green endosymbiont, whilst the latter is due to the combined effect of reduced absorption and enhanced backscattering [19,41]. In Fig 3e, the strong reflectance peak for C. polykrikoides at ~ 547 nm reflects absorption related to the presence of carotenoids [19,22].…”

“…Previous studies have demonstrated that HABs can be detected and described using satellite remote sensing, which provides bio-optical measurements at spatial and temporal scales not attainable with traditional in situ approaches [19,20]. To date, several remote sensing algorithms based on bio-optical and ecological methods have been established to discriminate the aforementioned HABs in the global oceans, including regions adjacent to the Red Sea, such as the Arabian Sea, Indian Ocean and Mediterranean Sea [19–33]. However, to the best of our knowledge no such technique has been utilized to discriminate these HABs in the Red Sea basin.…”

Use of Hyperspectral Remote Sensing to Estimate Water Quality

“…Algal concentrations in water through hyperspectral remote sensing images have been undertaken in the estimation of chlorophyll that is then used as an estimate for monitoring algal content and hence water quality. This approach has been adopted because wavelengths corresponding with the peak reflectance of blue-green and green algae are close together; it is harder to differentiate between them [19,41,42]. Hakvoorth et al [43], however, demonstrate that hyperspectral imagers permit for improved detection of chlorophyll and hereafter algae, as a result of acquired narrow spectral bands between 450 nm and 600 nm [20,44].…”