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X-ORIGINAL-URL:https://destination-earth.eu
X-WR-CALDESC:Events for Destination Earth
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DTSTART;TZID=Europe/Rome:20231213T120000
DTEND;TZID=Europe/Rome:20231213T130000
DTSTAMP:20260405T212715
CREATED:20231116T103708Z
LAST-MODIFIED:20231220T201417Z
UID:4210-1702468800-1702472400@destination-earth.eu
SUMMARY:Roadshow Webinar: DestinE in action - meet the first DESP use cases
DESCRIPTION:In this phase of Destination Earth\, the three core components are being validated by dedicated use cases. In this webinar\, you’ll meet the first 5 use cases procured to validate the Destination Earth Service Platform (DESP) being developed by ESA. \nThe use cases will be applied across a wide range of application domains\, including agriculture\, natural resource management\, fisheries\, and the polar area. In practise\, use cases will develop software applications that use data and services from DestinE. The purpose is to create predictions that can be used in those different domains and that can inform climate change adaption and extreme weather policy at various levels. During this webinar you can hear directly from each use case about their methods and objectives. \nWho should attend?\n\nDestinE Contractors\nProspective Users\nInterested Parties\nMember State Representatives\nMedia\n\nAgenda\n\n\n\nTime\nTitle\n\n\n\n\n12:00\nIntroduction\nRob Carrillo (Trust-IT)\n\n\n12:05\nWhat is the DESP? – Download Slides\nBarbara Borgia (Serco)\n\n\n\n12:15\nUse Case Lightning Presentations – Moderation by Antonio Romeo (RHEA) \n\nGlobal Fish Tracking System (GFTS) – Mathieu Woillez (Ifremer) – Download Slides\nUrbanSquare – Tarek Habib (MURMURATION) – Download Slides\nCITYNEXUS – Alessandra Feliciotti (MindEarth) – Download Slides\nDestination Renewable Energy (DRE) – Georgios Koutalieris (ENORA INNOVATION) – Download Slides\nDestinE Sea Ice Decision Enhancement (DESIDE) – David Arthurs (Polar View) – Download Slides\n\n\n\n\n12:50\nAudience Q&A\nRob Carrillo (Trust-IT)
URL:https://destination-earth.eu/event/destine-in-action-meet-the-first-desp-use-cases/
LOCATION:Online
CATEGORIES:Webinar
ATTACH;FMTTYPE=image/webp:https://destination-earth.eu/wp-content/uploads/2023/11/DESTINE_Webinar_WebsiteBanner_Dec2023-1.webp
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DTSTART;TZID=Europe/Rome:20231215T231000
DTEND;TZID=Europe/Rome:20231216T004000
DTSTAMP:20260405T212715
CREATED:20231128T115111Z
LAST-MODIFIED:20231128T115111Z
UID:4276-1702681800-1702687200@destination-earth.eu
SUMMARY:AGU2023\, WIDE.OPEN.SCIENCE: exploring machine learning and Digital Twin technologies for climate and weather simulation
DESCRIPTION:The AGU2023 “Wide.Open.Science” conference\, the annual gathering of the American Geophysical Union (AGU)\, is set to occur at the Moscone Centre in San Francisco and virtually from 11 to 15 December 2023. \nAI Applications Lead of DestinE Rochelle Schneider (ESA) will co-convene a session titled “Machine Learning and Digital Twin Technologies for Climate and Weather Simulation” on 15 December 2023. \nThis session aims to foster general discussions on the application of Machine Learning (ML) and Digital Twins (DT) technologies in climate and weather simulation and impact assessment. Attendees can expect insights into cutting-edge technologies developed for specific applications. \nWith a history spanning over a century\, AGU has consistently championed the cause of open science—creating pathways to discovery and raising awareness to tackle climate change. The conference serves as a dynamic platform for in-depth discussions on the latest advancements in Digital Twin Technologies\, with a specific focus on climate and weather simulations. \nMake sure you don’t miss important DestinE updates. Join the DestinE Community newsletter now. \nJoin the DestinE Community
URL:https://destination-earth.eu/event/agu2023-digital-twin-technologies-for-climate-and-weather-simulation/
LOCATION:Moscone Centre\, eLightning Theater VI\, Hall D - South (Exhibition Level\, South\, MC)\, San Francisco\, CA\, United States
ATTACH;FMTTYPE=image/jpeg:https://destination-earth.eu/wp-content/uploads/2023/11/AGU-2023_v3-scaled.jpg
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