EVOLUTION OF THE COPERNICUS LAND SERVICE PORTFOLIO INTEGRATING NOVEL EO DATA AND LATEST MACHINE LEARNING ALGORITHMS TO CONTINUOUSLY MONITOR THE STATUS, DYNAMICS AND BIOMASS OF THE LAND SURFACE

Informazioni relative al progetto

EVOLAND

ID dell’accordo di sovvenzione: 101082130

DOI 10.3030/101082130

Data della firma CE 10 Ottobre 2022

Data di avvio 1 Gennaio 2023

Data di completamento 31 Dicembre 2025

Finanziato da

• Digital, Industry and Space

Costo totale € 4 999 531,26

Contributo UE € 4 999 531,25

Coordinato da

VLAAMSE INSTELLING VOOR TECHNOLOGISCH ONDERZOEK N.V.
Belgio

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Piano di gestione dei dati (1)

Data management plan - interim version

Document describing how to implement the FAIR data principles, as well as data types, licenses and formats used within the project.

Documenti, relazioni (3)

Best practices for running large scale EO processes in the cloud - final version

Report with best practices on algorithm and code design for cloud processing.

Infrastructure requirements report - final version

Report with an inventory of the infrastructure required for operational implementation/ of the next-generation CLMS services, and for the project’s methodological developments and prototypic implementations.

EO missions catalogue relevant for EvoLand - final version

Inventory of available relevant EO data over EvoLand test and prototype sites. D2.1 is complementary to D1.2, but is viewed from the supplier side, while D1.2 covers the demand side.

Siti web, brevetti, video ecc. (1)

Visual identity, project branding and website

Report describing visual elements used in the project as well as the branding materials and website.

Pubblicazioni

Atti di conferenza (1)

DeCUR: decoupling common & unique representations for multimodal self-supervision

Autori: Yi Wang, Conrad M Albrecht, Nassim Ait Ali Braham, Chenying Liu, Zhitong Xiong, Xiao Xiang Zhu
Pubblicato in: 2023
Editore: Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionComputer Vision and P
DOI: 10.48550/arXiv.2309.05300