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CORDIS - EU research results
CORDIS

Earth Observation & Weather Data Federation with AI Embeddings

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

Use Case Implementation Report (opens in new window)

This deliverable will describe the implementation features of the Use Cases of the first development phase, also considering the requirements.

Analysis of ARD data and APIs (opens in new window)

Report on current state of the ARD and associated data processing APIs

Data access for AI-compressors (opens in new window)

Documentation, complete source code and configuration files. Pull Requests on OpenEO and OpenDataCube git repositories.

Reference Code for AI-compressors (opens in new window)

Python code as sample reference of the AI-compressor methodologies for Earth observation

Dissemination and Communication Strategy and Plan (opens in new window)

This deliverable provides the dissemination and communication foundation, including the strategic guidance to direct Embed2Scale community building activities for broad and durable impact. It will be led by Task 5.1.

SSL4EO-S12-downstream benchmark dataset (opens in new window)

Provides an open-source benchmark dataset to assess AI-compressor methodologies

AI-compressor containerization CICD pipeline (opens in new window)

Documentation, complete source code and configuration files

Report on State-of-the-Art in AI-compressors (opens in new window)

Review on AI-compressors in the light of the Embed2Scale application pillars Embed2{Train,Infer,Transfer,Find}

Benchmarking environment for AI-compressors (opens in new window)

Benchmarking environment to evaluate AI-compressor performance available to run an Earth observation community data challenge

Publications

Earth Observation Applications through Neural Embedding Compression from Foundation Models (opens in new window)

Author(s): Carlos Gomes, Thomas Brunschwiler
Published in: 2024
Publisher: Copernicus GmbH
DOI: 10.5194/egusphere-egu24-19460

Geospatial Foundation Models for Efficient Retrieval of Remote Sensing Images (opens in new window)

Author(s): Brunschwiler, T., Blumenstiel, B., Moor, V., and Kienzler, R.
Published in: 2024
Publisher: EGU General Assembly 2024
DOI: 10.5194/egusphere-egu24-18300

Scalable Efficient Compression in Large-Scale Earth Observation (opens in new window)

Author(s): Erik Scheurer, Jiangtao Wang, Rocco Sedona, Stefano Maurogiovanni, Benedikt Blumenstiel, Johannes Jakubik, Paolo Fraccaro, Thomas Brunschwiler, Stefan Kesselheim, Gabriele Cavallaro
Published in: 2025
Publisher: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-19016

"Neural Embedding Compression for Earth Observation Data – an Ablation Study" (opens in new window)

Author(s): Amelie Koch, Isabelle Wittmann, Carlos Gomez, Rikard Vinge, Michael Marszalek, Conrad Albrecht, Thomas Brunschwiler
Published in: 2025
Publisher: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-17172

Earth Observation embeddings at the test: A novel benchmark to evaluate (neural) compression for satellite imagery (opens in new window)

Author(s): Rikard Vinge, Michael L Marszalek, Jannik Schneider, Conrad M Albrecht
Published in: 2025
Publisher: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-16756

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