Earth Observation & Weather Data Federation with AI Embeddings

Información del proyecto

Embed2Scale

Identificador del acuerdo de subvención: 101131841

DOI

10.3030/101131841

Fecha de la firma de la CE 11 Diciembre 2023

Fecha de inicio 1 Enero 2024

Fecha de finalización 31 Diciembre 2026

Financiado con arreglo a

• Digital, Industry and Space

Coste total

€ 2 618 047,50

Aportación de la UE

€ 2 618 047,50

Coordinado por

MARTEL INNOVATE BV
Netherlands

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

Documents, reports (8)

Use Case Implementation Report

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

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

Data access for AI-compressors

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

Reference Code for AI-compressors

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

Dissemination and Communication Strategy and Plan

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

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

AI-compressor containerization CICD pipeline

Documentation, complete source code and configuration files

Report on State-of-the-Art in AI-compressors

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

Other (1)

Benchmarking environment for AI-compressors

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

Publicaciones

Conference proceedings (2)

Earth Observation Applications through Neural Embedding Compression from Foundation Models

Autores: Carlos Gomes, Thomas Brunschwiler
Publicado en: 2024
Editor: Copernicus GmbH
DOI: 10.5194/egusphere-egu24-19460

Geospatial Foundation Models for Efficient Retrieval of Remote Sensing Images

Autores: Brunschwiler, T., Blumenstiel, B., Moor, V., and Kienzler, R.
Publicado en: 2024
Editor: EGU General Assembly 2024
DOI: 10.5194/egusphere-egu24-18300

Other (3)

Scalable Efficient Compression in Large-Scale Earth Observation

Autores: Erik Scheurer, Jiangtao Wang, Rocco Sedona, Stefano Maurogiovanni, Benedikt Blumenstiel, Johannes Jakubik, Paolo Fraccaro, Thomas Brunschwiler, Stefan Kesselheim, Gabriele Cavallaro
Publicado en: 2025
Editor: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-19016

"Neural Embedding Compression for Earth Observation Data – an Ablation Study"

Autores: Amelie Koch, Isabelle Wittmann, Carlos Gomez, Rikard Vinge, Michael Marszalek, Conrad Albrecht, Thomas Brunschwiler
Publicado en: 2025
Editor: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-17172

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

Autores: Rikard Vinge, Michael L Marszalek, Jannik Schneider, Conrad M Albrecht
Publicado en: 2025
Editor: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-16756