Research Project
EO4EU: an Earth Observation data ecosystem
Innovative tools, methodologies and approaches to assist a wide spectrum of users to benefit from Earth Observation (EO) data.
Where: international
Where: international
Challenge
A significant amount of Earth Observation data is generated daily and accessible through various online services and repositories. This data can be utilized to enhance existing applications and foster innovation, ultimately benefiting the lives of EU citizens. However, an undersized audience follows this activity, leaving huge volumes of valuable information unexploited.
Approach
The purpose of the EO4EU project is to offer innovative tools, services, methodologies, and approaches with the aim of assisting a broad range of users who may not be familiar with the abundance of data and capabilities provided by EU services. The goal is to enable these users to access and process the data effectively, incorporating it into existing services and future developments. By doing so, the project aims to bridge the gap between potential users and the vast Earth Observation data available, facilitating its utilization and maximizing its benefits.
Digital Ecosystem
Solution
Digital Ecosystem
EO4EU connects already existing major EO data sources. In addition, the platform offers several tools and services to help users find and access the data they are interested in, as well as analyze and visualize them.
The platform leverages machine learning to support handling the characteristically large volume of EO data, along with a combination of Cloud computing infrastructure and high-performance computing to manage processing workloads.
Engineering efforts are focused on the readaptation of AI algorithms and integration tasks.
The project has received co-funding from the European Union's Horizon Europe programme - Contract No. 101060784.
Financing Framework
Results
Data fusion techniques for distributed systems
AR and VR for interactive user experience
Advanced data analytics visualizations for environmental observations
Impacts
Technologies
AI & Data
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