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VLIZ

Flanders Marine Institute
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73 Projects, page 1 of 15
  • Funder: European Commission Project Code: 101101473
    Overall Budget: 2,999,850 EURFunder Contribution: 2,999,850 EUR

    The EuropeThe European Green Deal recognises seas, oceans, and environment are a source of natural and economic wealth that we must preserve. The Mission Restore our Ocean and Waters aims at contributing to these goals with measurable targets. The UN Decade of Ocean Science for Sustainable Development is promoting to unlocking science for better decision making. Data and information are key enablers to these missions and the development of an EU Digital Twin of the Ocean (EDITO) is a key priority for Europe. EDITO-Infra, is to build the EU Public Infrastructure backbone for the first European DTO by upgrading, combining and integrating key service components the Copernicus Marine Service (CMS) and the European Marine Observation and Data Network (EMODnet) into a single digital framework that can be scaled up to an overarching knowledge system integrated with the DestinE initiative. It will provide the foundation for the development of the EU DTO initiative, hosting the deployment of future DTO projects (like ILIAD), of new generation of Ocean models (underlying models project) and of the Mission lighthouses projects. Led by Mercator Ocean international (MOi) as the Entrusted Entity leading the CMS, G7 FSOI secretary, GEO Blue Planet, Ocean Prediction DCC of the UN Decade of Ocean Science, and by Flanders Marine Institute (VLIZ) as manager of EMODnet Central Portal in an agreement between DG MARE and the Flanders Government, and representing the different EMODnet implementing partners, EDITO-Infra will provide public access and use to the widest possible range of open ocean observation datasets, data products, hosting for new sources of data, modelling capacities on Cloud, GPU or HPC, and a co-working environment with the objective of making ocean knowledge available to government, private sector, citizens, and scientific experts alike, enabling them to become partners in knowledge generation so that they assemble their own twins, for the pursuit of a healthy and productive ocean.

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  • Funder: European Commission Project Code: 101158669
    Funder Contribution: 1,496,430 EUR

    Technological areas such as Artificial Intelligence (AI) and ecosystems such as shipping, maritime and space have been strategically prioritised by Cyprus to improve its Research and Innovation (R&I) performance. At their intersection lies the need to enhance marine conservation efforts and maritime surveillance by leveraging deep learning (DL) methodologies built on standardized and robust data sets. Indeed, in-situ sampling stands as a cornerstone in marine conservation, offering a direct approach to monitoring marine biodiversity; while remote sensing stands as a pivotal addition to maritime surveillance, expanding the scope beyond traditional Automatic Identification System capabilities. DL, as a cutting-edge AI tool, holds immense potential to enhance the analysis of in-situ samples and remotely sensed data. AXOLOTL is proposed as a transformational international endeavour capable of enhancing the R&I capacity of CMMI, Cyprus and Europe in the interdisciplinary fields of DL-enhanced in-situ biodiversity assessment and DL-enhanced remote sensing for maritime surveillance. The project will contribute to closing the gap between a H2020 Teaming Centre of excellence and 2 strong innovators from France and Belgium through capacity-building, knowledge transfer, networking, and outreach activities at regional and international levels. Activities will go beyond the strictly scientific scope and support the mutual development, consolidation, and reinforcement of administrative, dissemination and entrepreneurial competencies, access to networks of excellence and the sustainable linkage between partners. The project’s R&I component will develop new strategies for improving data quality, standardization, and synchronization issues, devise novel interdisciplinary methodologies, develop robust DL models from state-of-the-art computer vision methods, and validate its proposed solutions in 2 relevant real-world contexts (biodiversity assessment and maritime surveillance).

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  • Funder: European Commission Project Code: 101119164
    Overall Budget: 13,222,000 EURFunder Contribution: 13,222,000 EUR

    The landscapes that extended for millions of square kilometres offshore of the world’s coastlines due to low sea-level during the last glaciation and were then drowned by sea-level rise, are known to preserve valuable archives of landscapes, palaeoclimatic change and stratified archaeological remains, with the potential to transform understanding of human history in this period of dramatic change. The absence of archaeological sites across much of this vast area prevents realisation of this potential. In SUBNORDICA we propose a systematic approach to develop new methods for recreating the submerged landscapes and human settlement of NW Europe and assess the impact of postglacial sea-level rise. We will address two questions: (1) What changes to the topography and environment of the submerged landscape were brought about by rising sea level and climate change? (2) How was the distribution of archaeological settlements and other traces of cultural activity impacted by this changing palaeolandscape, and can we recover them in sufficient detail to investigate human impact and human response? Combining information from 4 regions in the southern North Sea and the southern Baltic, we will use artificial intelligence to develop machine-learning routines to (a) integrate existing and newly acquired geophysical and geological data to map key areas of the changing landscape, and (b) combine this information with data from known underwater archaeological sites to identify new targets of archaeological potential for more detailed investigation. Investigating these targets will use high-resolution geophysical methods, sediment coring, archaeological excavation, and geochronological, palaeoenvironmental, sedimentological and biological analyses of recovered deposits. We will reveal a new chapter in human prehistory, provide a world-leading model for the investigation of submerged landscapes, and offer improved policy guidance for underwater cultural heritage management.

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  • Funder: European Commission Project Code: 101094649
    Overall Budget: 3,285,940 EURFunder Contribution: 3,285,940 EUR

    In order to protect and manage marine species and habitats, there is an immediate need for the creation of robust evidence-based methods and integrated platforms. Therefore, there is a need to undertake marine research projects that are developed and implemented collaboratively, strategically, and at a sufficient scale. Animal tracking is the study of animal movements across various spatiotemporal scales (local, regional, continental, global; minutes to decades). Although animal tracking is not a new field of research, only recently have these electronic technologies necessary to follow marine animal movements across larger and longer scales have only recently become widely available. Strategic Infrastructure for improved animal Tracking in European Seas (STRAITS) will leverage ongoing acoustic tracking projects across the four corners of Europe (i.e., North Channel, Danish Straits, Straits of Gibraltar and the Bosporus/Dardanelles) by expanding efforts to connect initiatives on species-based biodiversity management while developing data management plans and networking channels to deliver data to national and international governing bodies. Coordinating aquatic animal tracking and environmental observation efforts at a scale that will be usable to make progress on international marine management and planning, is a major step towards an operational European Tracking Network (ETN) that contributes to major European biodiversity initiatives, conservation, and policy.

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  • Funder: French National Research Agency (ANR) Project Code: ANR-23-EBIP-0011
    Funder Contribution: 156,189 EUR

    In order to protect and manage marine species and habitats, there is an immediate need for the creation of robust evidence-based methods. Therefore, there is a need to undertake marine research projects that are developed and implemented collaboratively, strategically, and at a sufficient scale. NorTrack will leverage ongoing acoustic tracking projects across the Northeast Atlantic (NEA) region and Europe by expanding efforts to connect initiatives on species-based biodiversity management while developing data management plans and networking channels to deliver data to national and international governing bodies. Coordinating aquatic animal tracking efforts at a scale that will be usable to make progress on international marine management and planning is a major step towards an operational European Tracking Network (ETN) that contributes to major European biodiversity initiatives, conservation, and policy. Acoustic telemetry has vast potential when it comes to understanding the behaviours of mobile marine species both within and across territorial waters. Acoustic telemetry refers to the use of transmitters or “tags” attached to target species that emit sound pulses that are heard by underwater receivers. This system allows researchers to track target species as they move through networks or across lines of receivers. The more complex the network of receivers, the more robust the dataset becomes. Knowledge of how key species use marine space allows for the creation of tailored strategies for protection, management, and development, which take into account how marine species use critical habitats. Recent efforts to develop aquatic telemetry networks have been at local or bilateral levels in Europe while larger networks in North America and Australia have established and are providing critical data relevant to management. The NorTrack project will support and enhance the existing and planned a basin-wide network of acoustic receivers in the NEA and across European seas, which is the next step towards a cohesive and integrated European-wide telemetry network.

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