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Tag: AI4Science

ESA Digital Twin Earth Components: Open Science Meeting 2026

February 2, 2026 - February 5, 2026
ESA-ESRIN, Largo Galileo Galilei, 1
Frascati, RM 00044 Italy

Background There is an undeniable urgency to act on the unprecedented ‘triple crisis’ of climate change, biodiversity loss and pollution. This requires new advances in the way we observe, understand and predict the dynamic evolution of the Earth system and its complex interactions with human activities and ecosystems. Digital Twins have recently emerged as potential …

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BiDS | Big Data from Space 2025

September 29 - October 3
The University of Latvia, Raiņa bulvāris 19, Centra rajons,
Rīga, Lettonia LV-1586 Latvia

Background Big Data from Space 2025 (BiDS25) is a major biennial event co-organised by the European Space Agency (ESA), the European Commission, and the EU Satellite Centre (SatCen). It brings together professionals from academia, industry, government, and beyond to explore how large-scale space data and advanced technologies—like AI, cloud computing, and data platforms—can address key …

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AI4SCIENCE – FCP – DEEPFEATURES

Prime company: Leipzig University (DE)

Although spectral indices (SIs) represent specific enhanced properties of the Earth’s system dynamics, there is no holistic, data driven approach that combines them. Studies typically focus on a few SIs out of more than two hundred. Our AI approach synthesises and optimises these SIs by using AI dimension reduction to reduce the number variables required …

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CLIMATE ADAPTATION, EXTREMES, MULTI-HAZARDS AND GEO-HAZARDS SCIENCE – ARCEME

Prime company: Leipzig University (DE)

Extreme weather and climate hazard can cause dramatic impacts on both natural ecosystems and human wellbeing and/or infrastructure and thereby harm society as a whole. Of particular concern are compound weather and climate extreme events, where the hazardous conditions of various extreme events combine and may have more detrimental effects than individual extremes. Increasing the …

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AI4IS: AI FORECASTING FOR ICE SHELF CALVING

Prime company: Science [&] Technology Norway (NO)

The instability of Antarctic ice shelves is one of the most critical open questions in polar science, due to its capacity to drive rapid sea level change at – and beyond – current high-end climate projections. Yet forecasting future instability is notoriously difficult because of the complex, non-linear forcing mechanisms controlling an ice shelf’s response, …

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AI4SNOW-ARTIFICIAL INTELLIGENCE FOR SNOW COVER IN MOUNTAIN REGIONS

Prime company: DLR – GERMAN AEROSPACE CENTER (DE)

The component of the Earth System addressed in this project is snow cover in mountain regions. The main scientific and technical objectives of AI4Snow are the development and training of AI methods to greatly improve remote sensing-based snow cover products for mountain regions as well as the implementation of data cubes containing all necessary datasets …

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AI4CH4: An End-to-End AI Framework for Methane Plume Detection and Quantification using Satellite Imagery

Prime company: C-CORE (CA)

Methane (CH4) is a significant anthropogenic greenhouse gas, second only to carbon dioxide (CO2) in contributing to global warming. It constitutes approximately 25% of the warming effect since pre-industrial times. Traditional methods for monitoring methane emissions rely on bottom-up approaches, calculating emissions by multiplying activity levels with emission factors. Satellites offer a more efficient alternative, …

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The DeepESDL AI-Ready Earth System Data Lab 

Prime company: BROCKMANN CONSULT GMBH (DE)

The Deep Earth System Data Lab (DeepESDL) delivers a service to the Earth Science community. The lab provides convenient access to relevant data sets, many of them generated in ESA’s science projects, in an analysis-ready format. Moreover, DeepESDL comprises a powerful data science environment with a focus on machine-learning and artificial intelligence workflows. We are …

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Explainable AI: application to trustworthy super-resolution (OpenSR) 

Prime company: UNIVERSITY OF OXFORD (GB)

The project aims to bring robust, accountable, and scalable multi-spectral super-resolution techniques to the Earth Observation (EO) community for the ubiquitous L2 and L3 pre-processing of the Sentinel-2 (S2) revisits archive. Super-resolution (SR) is a nascent technology and the roadmap to maturity will require insights from many disciplines. Super-resolution is not just about image generation, …

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Artificial Intelligence for SAR at High Resolution (AI4SAR HighRes)

Prime company: ICEYE OY (FI)

AI4SAR is an attempt to harness AI techniques for high-resolution, high-fidelity SAR data, both in time and spatially. It aims to process rapid-revisit SAR data  and develop modular applications for high-frequency monitoring of Earth.  The inherent complexity of the backscattered SAR signal presents a daunting challenge to data scientists and machine learning (ML) engineers, thereby increasing …

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