CALLISTO aims to bridge the gap between Copernicus Data and Information Access Services (DIAS) providers and application end users through dedicated Artificial Intelligence (AI) solutions. It will provide an interoperable Big Data platform integrating Earth Observation (EO) data with crowdsourced and geo-referenced data and observations from Unmanned Aerial Vehicles. CALLISTO will be pilot-tested in real environments, providing geolocation-based services in applications relevant to agricultural policymaking, water management, journalism and border security.

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Artificial Intelligence

Machine Learning, Deep Learning, etc

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Distributed computing

High Performance Computing
for the application of AI-based techniques
Νeural network-based methods
for detecting & predicting behavior patterns

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Unmanned Aerial Vehicles (UAVs)

Computer vision using UAVs and alert-driven UAVs path planning

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Data Fusion

Using satellite data, Galileo/GNSS data, Web and social media data, and in-situ hyperspectral measurements

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Semantic Image Segmentation & Ontologies

Formal representation of interlinked data in the form of self-descriptive, machine-readable data resources in graph structure




EU contribution


Pilot implementations

The services of CALLISTO will be tested in four real-life cases that are driven by the needs of:

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CAP monitoring

Virtual monitoring of the implementation of the Common Agricultural Policy (CAP) obligations

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Water quality assessment

Virtual presence in water resources for water quality assessment using EO and in-situ data

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Satellite journalism

Expanding the use of satellite imagery and data from sensors for journalistic research and verification

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Land border change detection

Improving the existing approaches and increasing the value of the current Border Surveillance Services