96 research outputs found

    Unattended processing of shipborne hyperspectral reflectance measurements

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    AbstractHyperspectral remote-sensing reflectance (Rrs) from above-surface (ir)radiance measurements is derived using a new, automated method that is suitable for use on moving platforms. The sensors are mounted on a rotating platform that compensates for changing solar and ship azimuth angles, optimizing the sensor azimuth for minimal contribution of sky radiance to measured water-leaving radiance. This sea-surface reflectance (Ļs) lies in the order of 2.5ā€“8% of sky radiance, and is determined through spectral optimization, minimizing the propagation of atmospheric absorption features to Rrs. Up to 15 of these gas absorption features are frequently recognized in (ir)radiance spectra under clear and overcast skies. Rrs was satisfactorily reproduced for a wide range of simulated Case 2 waters and clear sky conditions. A set of 13,784 in situ measurements collected with optimized viewing angles on the high-absorption, low-scattering Baltic Sea was collected in April and July 2010ā€“2011. The processing procedure yielded a 22% retrieval rate of Ļs for the field data. The shape of the subsurface irradiance reflectance measurements (R(0āˆ’)) measured at anchor stations was well reproduced in above-surface Rrs in those cases where the algorithm converged on a solution for Ļs, except under unstable or weak illumination conditions. Clear-sky conditions resulted in the best correspondence of Rrs and R(0āˆ’) and gave the highest (>50%) retrieval rates of Ļs. Two indices, derived from the available sensor data, are given to describe illumination conditions, and are shown to predict the ability of the algorithm to retrieve Rrs

    Spatiotemporal Statistical Downscaling for the Fusion of In-lake and Remote Sensing Data

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    This paper addresses the problem of fusing data from in-lake monitoring programmes with remote sensing data, through statistical downscaling. A Bayesian hierarchical model is developed, in order to fuse the in-lake and remote sensing data using spatially-varying coefficients. The model is applied to an example dataset of log(chlorophyll-a) data for Lake Erie, one of the Great Lakes of North America

    Diversity of luciferase sequences and bioluminescence production in Baltic Sea Alexandrium ostenfeldii

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    The toxic dinoflagellate Alexandrium ostenfeldii is the only bioluminescent bloom-forming phytoplankton in coastal waters of the Baltic Sea. We analysed partial luciferase gene (lcf) sequences and bioluminescence production in Baltic A. ostenfeldii bloom populations to assess the distribution and consistency of the trait in the Baltic Sea, and to evaluate applications for early detection of toxic blooms. Lcf was consistently present in 61 Baltic Sea A. ostenfeldii strains isolated from six separate bloom sites. All Baltic Sea strains except one produced bioluminescence. In contrast, the presence of lcf and the ability to produce bioluminescence did vary among strains from other parts of Europe. In phylogenetic analyses, lcf sequences of Baltic Sea strains clustered separately from North Sea strains, but variation between Baltic Sea strains was not sufficient to distinguish between bloom populations. Clustering of the lcf marker was similar to internal transcribed spacer (ITS) sequences with differences being minor and limited to the lowest hierarchical clusters, indicating a similar rate of evolution of the two genes. In relation to monitoring, the consistent presence of lcf and close coupling of lcf with bioluminescence suggests that bioluminescence can be used to reliably monitor toxic bloom-forming A. ostenfeldii in the Baltic Sea.Peer reviewe

    Atmospheric Correction Performance of Hyperspectral Airborne Imagery over a Small Eutrophic Lake under Changing Cloud Cover

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    Atmospheric correction of remotely sensed imagery of inland water bodies is essential to interpret water-leaving radiance signals and for the accurate retrieval of water quality variables. Atmospheric correction is particularly challenging over inhomogeneous water bodies surrounded by comparatively bright land surface. We present results of AisaFENIX airborne hyperspectral imagery collected over a small inland water body under changing cloud cover, presenting challenging but common conditions for atmospheric correction. This is the first evaluation of the performance of the FENIX sensor over water bodies. ATCOR4, which is not specifically designed for atmospheric correction over water and does not make any assumptions on water type, was used to obtain atmospherically corrected reflectance values, which were compared to in situ water-leaving reflectance collected at six stations. Three different atmospheric correction strategies in ATCOR4 was tested. The strategy using fully image-derived and spatially varying atmospheric parameters produced a reflectance accuracy of ±0.002, i.e., a difference of less than 15% compared to the in situ reference reflectance. Amplitude and shape of the remotely sensed reflectance spectra were in general accordance with the in situ data. The spectral angle was better than 4.1° for the best cases, in the spectral range of 450–750 nm. The retrieval of chlorophyll-a (Chl-a) concentration using a popular semi-analytical band ratio algorithm for turbid inland waters gave an accuracy of ~16% or 4.4 mg/m3compared to retrieval of Chl-a from reflectance measured in situ. Using fixed ATCOR4 processing parameters for whole images improved Chl-a retrieval results from ~6 mg/m3difference to reference to approximately 2 mg/m3. We conclude that the AisaFENIX sensor, in combination with ATCOR4 in image-driven parametrization, can be successfully used for inland water quality observations. This implies that the need for in situ reference measurements is not as strict as has been assumed and a high degree of automation in processing is possible

    The Role of Citizen Science in Promoting Ocean and Water Literacy in School Communities: The ProBleu Methodology

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    Human activities continue to degrade oceanic, coastal and inland waters. The generational change in the role of society in actively looking after the health of water resources can be achieved through the expansion of ocean and water literacy in schools. The Network of European Blue Schools established under the EU4Ocean Coalition for Ocean Literacy has improved ocean and water literacy; however, this Network needs to grow and be supported. Here, we present ProBleu, a recently funded EU project that will expand and support the Network, partly through the use of citizen science. The core of the proposed methodology is facilitating school activities related to ocean and water literacy through funding calls to sustain and enrich current school activities, and kick-start and support new activities. The outcomes of the project are anticipated to have widespread and long-term impacts across society, and oceanic, coastal and inland water environments

    Determination of optical markers of cyanobacterial physiology from fluorescence kinetics

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    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

    Optimising Multispectral Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae

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    This study assesses the ability of a new active fluorometer, the LabSTAF, to diagnostically assess the physiology of freshwater cyanobacteria in a reservoir exhibiting annual blooms. Specifically, we analyse the correlation of relative cyanobacteria abundance with photosynthetic parameters derived from fluorescence light curves (FLCs) obtained using several combinations of excitation wavebands, photosystem II (PSII) excitation spectra and the emission ratio of 730 over 685 nm (Fo(730/685)) using excitation protocols with varying degrees of sensitivity to cyanobacteria and algae. FLCs using blue excitation (B) and greenā€“orangeā€“red (GOR) excitation wavebands capture physiology parameters of algae and cyanobacteria, respectively. The greenā€“orange (GO) protocol, expected to have the best diagnostic properties for cyanobacteria, did not guarantee PSII saturation. PSII excitation spectra showed distinct response from cyanobacteria and algae, depending on spectral optimisation of the light dose. Fo(730/685), obtained using a combination of GOR excitation wavebands, Fo(GOR, 730/685), showed a significant correlation with the relative abundance of cyanobacteria (linear regression, p-value < 0.01, adjusted R2 = 0.42). We recommend using, in parallel, Fo(GOR, 730/685), PSII excitation spectra (appropriately optimised for cyanobacteria versus algae), and physiological parameters derived from the FLCs obtained with GOR and B protocols to assess the physiology of cyanobacteria and to ultimately predict their growth. Higher intensity LEDs (G and O) should be considered to reach PSII saturation to further increase diagnostic sensitivity to the cyanobacteria component of the community
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