Replay Φ-week 2021

ESA’s Φ-week fourth edition took place last 11-15 October, focusing on the New Space economy and its associated innovations.

Recordings of the sessions from this hybrid formula event (virtual for the public and in person for invited speakers) are now publicly available.

Find here below direct links to recordings of a selection of EO science for society – specific sessions.


Earth Observation System of Systems and Application Scenarios
Explore the concept of EO system-of-systems, which could merge the world-leading Earth monitoring capacity built through the EU’s Copernicus programme with national and private (ongoing and planned) initiatives. This system-of-systems, powered by disruptive technologies such as Artificial Intelligence (Machine Learning), IoT, Blockchains, Quantum Technologies, and in general the digital revolution, will deliver what we could call our future Earth Intelligence system.

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DTE Precursors
Hear about the results of the precursor studies launched by ESA in preparation of the Digital Twin Earth implementation activities, including a series of preparatory activities addressing different themes: Forestry and carbon, Climate hot spots, Food systems, Ocean, Hydrology, Polar regions.

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ESA Virtual Labs
Explore the latest advancements in collaborative Earth system science research, offered by the combination of Open data, Open Tools and Virtual Laboratories. You will learn about the what scientific results have been achieved, the new functionalities that are available, as well as the future pathways and trends in the development of Open Innovation tools.

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Network of Resources
The ESA Network of Resource Initiative promotes the use of cloud services for users who wish to work with EO data. In this session many of the Platform Service providers in the NoR community describe what services they have available that can benefit Research, Development and Commercial users.

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Enabling EO Platforms

This session provides the status and future plans – including availability of AI capabilities – of several key platforms that are providing operational services on top of cloud infrastructures to the community. Aim is to accelerate science and value adding processes delegating the “heavy lifting” to experts in managing scalable processing environments and to allow the community to share the results.

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Accelerating New Space Uptake

An increasing number of European SmallSat developers/operators use private sector investment to develop, launch and operate dedicated EO satellites to deliver focused commercial services to clearly defined customer groups. However, in many cases the data from these systems are also of potential interest to stakeholders that cannot be effectively engaged in the short term or which may not be addressable under conventional business models. ESA has already set up some projects to test whether ESA-funded actions to specify demonstration exercises can accelerate wider uptake among such customers of the data and services provided by the NewSpace operators. This leads to increased commercial revenue streams and a more attractive investment proposition for future financing rounds. This session investigates with the key players if and how this model can be expanded and what other actors would need to be engaged.

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Recent ML/AI advances offer a huge potential to contribute to answering grand scientific questions and can play a major role in accelerating knowledge discovery by automatically learning patterns and models from the data, while taking into account the wealth of knowledge accumulated in physics-based model representations of geoscience processes. Open Science frameworks on top of EO Platform technologies, together with HPC and other advances in ICT provide the underlying layer enabling data-intensive ML/AI at scale, for big geoscience problems.

In this session we discussed with experts in Earth System Science, AI and Data systems from NASA, Microsoft, Barcelona Supercomputing Centre and the University of Valencia to learn more about various approaches to AI for Big Earth System Science, how AI and technological advances can support sustainable science at scale, and what kind of requirements emerge from specific scientific cases such as extreme events characterisation, detection and attribution, statistical downscaling and bias correction techniques, or data-driven parameterisations.

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Side event recordings are also available as a playlist in our EO Open Science YouTube channel.

Among others, you will find: