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DNA barcoding the Lake Edward basin: high taxonomic coverage of a tropical freshwater ichthyofauna
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RBINS Staff Publications 2022
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Review of the Adoretini of Cambodia with six new species (Coleoptera, Scarabaeidae, Rutelinae)
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RBINS Staff Publications 2022 OA
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Presence of Placiphorella atlantica (Verrill & S. I. Smith, 1882) (Polyplacophora, Mopaliidae) in the Denmark Strait (West Iceland)
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RBINS Staff Publications 2022 OA
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First report of the occurrence of the genus Megobaralipton Lepesme & Breuning, 1952 in Vietnem (Coleoptera, Cerambycidae, Prioninae, Aegosomatini)
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RBINS Staff Publications 2018
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The palaeogenetics of cat dispersal in the ancient world
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The cat has long been important to human societies as a pest-control agent, object of symbolic value and companion animal, but little is known about its domestication process and early anthropogenic dispersal. Here we show, using ancient DNA analysis of geographically and temporally widespread archaeological cat remains, that both the Near Eastern and Egyptian populations of Felis silvestris lybica contributed to the gene pool of the domestic cat at different historical times. While the cat’s worldwide conquest began during the Neolithic period in the Near East, its dispersal gained momentum during the Classical period, when the Egyptian cat successfully spread throughout the Old World. The expansion patterns and ranges suggest dispersal along human maritime and terrestrial routes of trade and connectivity. A coat-colour variant was found at high frequency only after the Middle Ages, suggesting that directed breeding of cats occurred later than with most other domesticated animals.
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RBINS Staff Publications 2017
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Assessment and data reporting of significant acute pollution events under the MSFD – Criteria D8C3/D8C4 of the Marine Strategy Framework Directive (MSFD)
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RBINS Staff Publications 2025
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Atmospheric Correction Inter-Comparison eXercise, ACIX-III Land: An Assessment of Atmospheric Correction Processors for EnMAP and PRISMA over Land
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Correcting atmospheric effects on hyperspectral optical satellite scenes is paramount to ensuring the accuracy of derived bio-geophysical products. The open-access benchmark Atmospheric Correction Inter-comparison eXercise (ACIX) was first initiated in 2016 and has now been extended to provide a comprehensive assessment of atmospheric processors of space-borne imaging spectroscopy missions (EnMAP and PRISMA) over land surfaces. The exercise contains 90 scenes, covering stations of the Aerosol Robotic Network (AERONET) for assessing aerosol optical depth (AOD) and water vapour (WV) retrievals, as well as stationary networks (RadCalNet and HYPERNETS) and ad hoc campaigns for surface reflectance (SR) validation. AOD, WV, and SR retrievals were assessed using accuracy, precision, and uncertainty metrics. For AOD retrieval, processors showed a range of uncertainties, with half showing overall uncertainties of <0.1 but going up to uncertainties of almost 0.4. WV retrievals showed consistent offsets for almost all processors, with uncertainty values between 0.171 and 0.875 g/cm2. Average uncertainties for SR retrievals depend on wavelength, processor, and sensor (uncertainties are slightly higher for PRISMA), showing average values between 0.02 and 0.04. Although results are biased towards a limited selection of ground measurements over arid regions with low AOD, this study shows a detailed analysis of similarities and differences of seven processors. This work provides critical insights for understanding the current capabilities and limitations of atmospheric correction algorithms for imaging spectroscopy, offering both a foundation for future improvements and a first practical guide to support users in selecting the most suitable processor for their application needs.
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RBINS Staff Publications 2025
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A generalized physics-based correction for adjacency effects
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Atmospheric scattering occurs over a horizontal scale of several kilometers. This results in influence from neighboring surface features on the signal recorded over a given position, reducing contrast and the accuracy of quantitative retrievals of surface reflectance from satellite imagery. This atmospheric blurring, or adjacency effect, must be accounted for when both contrast in surface reflectance and magnitude of atmospheric scattering are significant. Taking into account the adjacency effect is of particular importance for aquatic remote sensing of inland and coastal waters due to the high contrast between water and different land cover types, as well as the small spatial scale of most inland water bodies. In this paper, we present a physics-based processor to retrieve surface reflectance over all surface types, regardless of the subscene composition and sensor waveband configuration. The processor is implemented in the free and open source ACOLITE software and is composed of two modules: (1) TSDSF for the estimation of aerosol properties and (2) RAdCor for the retrieval of surface reflectance. We demonstrate the performance of the TSDSF $+$ RAdCor processor for the Operational Land Imager (OLI) onboard Landsat 8 and the Multispectral Instrument (MSI) onboard Sentinel-2A and 2B over a set of small ($\lt1\;\rm km^2$) inland waters in Belgium, and compare the performance with other common processors for these sensors, including C2RCC, POLYMER, Sen2Cor, iCOR, ACOLITE/DSF, and LaSRC. For clear sky matchups, the relative deviation againstin situ data in the visible wavebands ranged between 6% and 18% for OLI, and between 14% and 31% for MSI, except for the MSI waveband centered at 443 nm where the relative deviation was 70%. In the near-infrared wavebands, the relative deviation varied from 70% to 150%, with the exception of the MSI waveband centered at 704 nm, for which the performance was 17%. Overall, the new processor outperformed the other evaluated processors in the visible range, with the exception of the MSI waveband centered at 443 nm, and was outperformed by C2RCC and POLYMER in the near-infrared wavebands. Recommendations on how to use TSDSF and RAdCor in ACOLITE are provided.
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RBINS Staff Publications 2025
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Generation of super-resolution gap-free ocean colour satellite products using data-interpolating empirical orthogonal functions (DINEOF)
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In this work we present a super-resolution approach for deriving high-spatial-resolution and high-temporal-resolution ocean colour satellite datasets. The technique is based on DINEOF (data-interpolating empirical orthogonal functions), a data-driven method that uses the spatio-temporal coherence of analysed datasets to infer missing information. DINEOF is used here to effectively increase the spatial resolution of satellite data and is applied to a combination of Sentinel-2 and Sentinel-3 datasets. The results show that DINEOF is able to infer the spatial variability observed in the Sentinel-2 data to the Sentinel-3 data while reconstructing missing information due to clouds and reducing the amount of noise in the initial dataset. In order to achieve this, the Sentinel-2 and Sentinel-3 datasets have undergone the same pre-processing, including a comprehensive, region-independent, and pixel-based automatic switching scheme for choosing the most appropriate atmospheric correction and ocean colour algorithm to derive in-water products. The super-resolution DINEOF has been applied to two different variables (turbidity and chlorophyll) and two different domains (Belgian coastal zone and the whole of the North Sea), and the sub-mesoscale variability of the turbidity along the Belgian coastal zone has been studied.
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RBINS Staff Publications 2025
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The systematics and evolution of the Sri Lankan rainforest land snail Corilla: New insights from RADseq-based phylogenetics
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RBINS Staff Publications 2023 OA
