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Global Earth Monitor

Project description

Improved models for interpreting Earth observation data

The EU-funded GEM project will address the challenge of continuous monitoring of large Earth areas on regional and global scales in a sustainable and cost-effective way. The goal is to establish a new disruptive Earth observation data model that should significantly enhance the exploitation of Copernicus data. The project will further develop a proprietary concept of adjustable data cubes – a combination of static and dynamic data cubes, powered by Sentinel Hub – and integrate them with Earth observation data from the open-source machine learning framework eo-learn. Modern machine learning techniques will be combined to construct global, scale-independent interpretation models, with a special focus on causality and change detection.

Objective

Global Earth Monitor project (GEM) is addressing the challenge of continuous monitoring of large areas in a sustainable cost effective way. The goal of the project is to establish a new disruptive Earth Observation (EO) DATA-EXPLOITATION MODEL which will dramatically enhance the exploitation of Copernicus data. For the first time a continuous monitoring of the planet on the global/regional scale will be enabled for a sustainable price.

Disruptive innovations are planned in the technology and in the methodology domain, where a proprietary concept of Adjustable Data Cubes (a combination of static and dynamic data cubes) will be developed and integrated with EO-oriented open source Machine Learning (ML) framework EO-LEARN. During the project EO-LEARN will be upgraded to consume ML technologies from widely accepted ML frameworks and to adapt/evolve them to specifics of EO-data interpretation. Modern ML technologies and approaches (GAN, RNN, LSTM, Attention & Bayesian Deep Learning, Curriculum Learning, Incremental learning, Meta-learning, Hybrid modelling) will be combined to construct GLOBAL, SCALE-INDEPENDENT interpretation models with the special focus on CAUSALITY and CHANGE DETECTION.

Technological and Methodological innovations will be combined into a unique CONTINUOUS MONITORING PROCESS. The process, based on seamless combination of data interpreted with sub-resolution, native resolution and super-resolution methods, will deliver optimal combination of Processing/Storage costs – enabling continuous monitoring of large areas for just a FRACTION OF CURRENT COSTS.

The concept of continuous monitoring will be validated through the development of five specific use-cases and through their employment in a 10-month demonstration - operational continuous monitoring of 10 MIO square km area.

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Keywords

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Topic(s)

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Funding Scheme

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RIA - Research and Innovation action

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Call for proposal

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(opens in new window) H2020-SPACE-2018-2020

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Coordinator

SINERGISE SOLUTIONS, LABORATORIJ ZAGEOGRAFSKE INFORMACIJSKE SISTEME,DOO
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 0,00
Address
CVETKOVA ULICA 29
1000 Ljubljana
Slovenia

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Region
Slovenija Zahodna Slovenija Osrednjeslovenska
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
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Total cost

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Participants (8)

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