Cerulean Information Factory: A New European Space Agency-Funded Project to Develop Decision-Support Tools for the North Atlantic and Arctic Oceans
Notice bibliographique
Résumé
The The European Space Agency (ESA), responding to the European Green Deal-Europe's commitment to climate neutrality by 2050-has launched the Green Transition Information Factory (GTIF) program. Its goal is to use satellite and other data to create tools for decision-makers to support the transition to a greener economy. “The ESA Green Transition Information Factory (GTIF) allows users to interactively discover the underlying opportunities and complexities of transitioning to carbon neutrality by 2050 using the power of Earth Observation, cloud-computing and cutting-edge analytics.” - ESA The Green Economy is “one that results in improved human well-being and social equity, while significantly reducing environmental risks and ecological scarcities” (United Nations). The Blue Economy refers to “sustainable use of ocean resources for economic growth, improved livelihoods and jobs, and ocean ecosystem health.” (World Bank). Since the oceans are part of all natural cycles and, directly or indirectly, involved in all economic sectors, there cannot be a Green Transition without the blue component. ESA is sponsoring a GTIF that addresses a green transition for the blue economy named the Cerulean Information Factory (CIF) after the blue-green colour and reflecting the need to connect the Blue and Green Economies in order to have a successful Green Transition. The focus of the project, launched in Spring of 2024, will be on the North Atlantic and Arctic oceans between Canada and Europe. The initial capabilities will focus on three domains: 1.offshore Renewable Energy: Integrating multiple data sources to provide user-definable metrics for offshore renewable energy potential and risk for offshore renewable energy, including solar, tidal, wave, wind and current energy. Analytical capabilities will include: •energy potential of sites; •accessibility of sites, including water depth, and distance to shore and energy markets; •vulnerability of sites to adverse environmental conditions, including sea ice, icebergs, and extreme waves and winds; and, •forecasts for winds, sea ice, waves and currents. 2.Ship Carbon Intensity Minimisation and Arctic Accessibility: Providing a route optimization tool for vessels in ice that minimises fuel consumption, ship emissions, and travel time, while maintaining ship safety in sea ice and icebergs. This capability will provide a tool to support both: •Ship operators with voyage planning, and, •Policymakers in evaluating the impact of the International Maritime Organization's Carbon Intensity Indicator (CII) regulation and future changes in the accessibility of Arctic regions due to climate change. 3.Aquaculture: Providing indicators of ocean health and potential risks for aquaculture sites by enabling end-users to filter and combine ocean and meteorological observations and forecasts. This capability will support: •Assessment of aquaculture site suitability based on historical water quality and presence of microorganisms, such as temperatures and nutrients, and, •Early warning systems, such as harmful algal blooms, pollution and eutrophication. Throughout the project, the CIF team will be engaging with end users to identify requirements and co-develop the tools that decision-makers in industry, government and civil society need; transforming ocean data into information for decision making. The project team is made up of a consortium of organisations with Earth Observation expertise from both sides of the Atlantic Ocean, including Polar View, EOX, Danish Meteorological Institute, C-CORE, and the National Research Council Canada. At OCEANS 2024, we will demonstrate the initial capabilities of the CIF.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,011 | 0,007 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 0,012 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».