Recap: Domino-E Webinar Session #2

Date: March 26, 2025 Title: Developing within Domino: Examples from Domino-E Speakers: Philippe Pavero (ADS), Jakub Rezler (ITTI), Marie Devant (Capgemini), Cédric Pralet (ONERA), Cyrille de Lussy (ADS), and Raivis Skadins (Tilde) Host(s): Thomas Stollenwerk (Oikoplus), Michael Anranter (Oikoplus) In the second session of the Domino-E webinar series, we moved from theory to practice: three…

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Recap: Domino-E Webinar Session #1

Date: March 19, 2025, 10:30-12:00 CET Title: Understanding the Domino Architecture – A New Era of Earth Observation Speakers: Jean-François Vinuesa (ADS), Daniel Novak (ADS), Michael Anranter (Oikoplus) Hosts: Thomas Stollenwerk (Oikoplus), Michael Anranter (Oikoplus) The first session of the Domino-E webinar series commenced with a thorough exploration of the history, challenges, and innovations in…

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Applying Earth Observation: Energy Poverty

The 3,5-year project EnergyMeasures is wrapping up in Brussels. The EU-funded project was launched to identify households affected by energy poverty, to develop strategies that would  support them in adopting less energy-intensive behaviours, and to provide decision-makers of all levels with evidence-based policy recommendations to tackle energy poverty. As the project winds down, one of the key conclusions was to…

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Along the river: the stream of Earth observation

Rivers are divided into upstream, midstream, and downstream. This tripartite division also helps to understand the earth observation processing chain. Rivers are traditionally divided into three sections along their course based on the gradient between their source and delta: upstream, midstream and downstream. This division is often used metaphorically to describe industrial value chains.  The…

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Machine learning in Domino-E use cases

What exactly is machine learning (ML) and  how does Domino-E make use of it in planning, resource allocation and human-computer interactions? In what ways does it benefit users? In this article we focus on answering these and other questions regarding machine learning in Earth Observation.  Earth Observation (EO) produces a vast quantity of often unstructured data.…

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