EO4EU Platform

AI-enabled easy access to Earth observation data

The EO4EU platform is a next-generation platform for Earth Observation (EO) data processing and analysis that is being developed by a consortium of European partners.

It is based on several innovative technologies, including machine learning, knowledge graphs, and extended reality, and is designed to address two important challenges of EO data processing platforms: platform intelligence and systems support.

A ccess the EO4EU Platform

EO4EU for Users

Policy makers | Research & Academia | NGOs, Citizen scientists, Public | Private Sector

EO4EU for Policy Makers

You know that EO data can help make your policies more effective by being more data-driven, but EO tools until today need technical knowledge to use and access.

Access EO data in your area without the need for technical EO knowledge!

Through the EO4EU Platform, you can consult EO data and implement policies that are guided by real-world data about your area of concern.

EO4EU for Research and Academia and Citizen Scientists

Europe produces some of the highest-quality EO data that can provide significant insights not only for environmental or agricultural applications but also for archaeology or social sciences. However, the high technical knowledge needed to use and access EO data presents a significant barrier.

Access EO data for your research more easily than before!

EO4EU for NGOs and the public

Whether it’s advocacy for the climate, or for economic or urban development, insights from Earth Observation data can make your proposals more compelling.

Benefit from available EO data more easily now!

EO4EU for the Private Sector

Competitive advantage largely rely on innovation and added value. The wealth of Earth observation data has thus far been unreachable to the private sector except for companies with dedicated EO expertise.

Empower your business with new applications or improved offerings through more readily available EO data!

Top features for you

Through the EO4EU Platform, you can access some of the largest and most trusted EO data sources in one place and use added value features such as:

Personalised dashboards
Smart search engine
Real-time and historical data visualisation, analysis and interpretations
Interactive mapping
Rich and diverse EO data sources
Readily available AI and ML resources
Virtual reality interface powered via augmented/extended reality technology

Apply for early access now!

Tools in the platform

Data Analytics Visualization: Decision-making and policymaking are at the heart of our data analytics and visualization tools. We offer real-time data analysis, interpretation of environmental observations, and interactive mapping. Our smart search engine is text and annotation-based, and we provide personalized dashboards, all fuelled by data analytics based on statistical metrics.
Knowledge Graph-based Decision Making: Our approach to decision-making and analysis is unique. We're introducing a Graph-Based Text Representation, enabling us to extract informative features from the entire knowledge graph. This encompasses structural and textual aspects, providing you with a more comprehensive understanding of the data.
XR System (early): We're taking data visualization to a whole new level with our extended reality (XR) system. This immersive experience includes an augmented reality (AR) interface that lets you visualize and analyse EO data in the real-world using geolocation technology. Furthermore, our virtual reality (VR) interface brings EO data to life in 3D virtual environments, compatible with various VR devices.
AI/ML Marketplace: Our AI and ML Marketplace is your one-stop destination for artificial intelligence and machine learning resources. The EO4EU Platform offers a comprehensive selection of AI and ML models, algorithms, techniques, metadata, and data models for processing and communication, programming code, and documentation.
Generic Machine Learning pipeline for semantic annotation: We understand that labelled data can be a limitation. Our Generic Machine Learning Pipeline is designed to minimise the need for use-case-specific labelled data. It empowers you to learn a robust and transferable representation of input data in a latent space, all in an unsupervised manner. We employ approaches like SimCLR, which is a simple framework for contrastive learning of visual representations. We also keep an eye on emerging techniques in this rapidly evolving field.
Fusion engine: Our Fusion Engine is the heart of context awareness. It combines data readings from different sources selected by you, the user, and processes them through various algorithmic pipelines. These pipelines refine the data and even create new products. All this is done with the utmost efficiency, utilising high-performance computing (HPC) and GPU environments. Each pipeline runs in the Kubeflow environment, ensuring seamless communication through the EO4EU message bus.
Serverless FaaS capabilities: Our serverless Function as a Service (FaaS) capabilities provide you with a cloud computing service that lets you run code in response to events without the complexity of managing infrastructure. This means you can focus on your tasks, and we handle the rest.

Use cases

To be insert Use Cases Carousel

Improving Civil Protection activities using EO acquired datasets

This use case will deal with a better exploitation and use of EO observed datasets to be adopted in the prevention and response activities of Civil Protection services. It builds on the cloud based service provided by IES Solutions - now Webgenesys - to Regione Sicilia, Italy, and extends to the West Attica and Evros regions of Greece for the end-to-end management of operations, ranging from risk nowcasting, short-time prevention planning and daily service activities, to the coordination of response to major emergencies. Based on a proven, geographic, Civil Protection Decision Support System this UC#7 aims at showcasing EO-driven improvements in the real-time management of natural and Man-made risks.

Environmental Pests

The use case proposed for this project is an information service of locust plague impact assessment and prediction that SIS is providing to an NGO currently operating in Yemen. Desert Locust plague is strongly influenced by climate conditions and vegetation status. So far, all the studies aimed at describing and monitoring this phenomenon have approached separately the Earth Observation techniques and Climate predictions analysis.

Soil erosion

Soil Erosion Use Case proposes to integrate rainfall datasets, driving estimates of rainfall erosivity, and non-climate datasets to assess soil susceptibility to water erosion, leveraging empirical approaches, such as the Revised Universal Soil Loss Equation (RUSLE) and similar equations.

Forest ecosystems

The Forest ecosystems use case will identify information on ecosystem services produced in a managed forest, in particular provisioning services (wood and timber), and regulating services, for hydrology and climate through the water and carbon cycle, respectively.

Food Security

The Food Security case study concerns various aspects of food security and natural systems safety, climate change, mitigation and adaptation, as well as the sustainable management of agricultural systems. The related development activities consist of the determination of specific climate indicators for the evaluation of the impact of extreme climate events and adverse phenomena such as the spread of destructive species on crops, risk estimation, forecasts, and alerts for potential production losses as climate mitigation services.

Ocean monitoring

DANAOS Shipping is one of the largest managers of modern, large-size containerships voyaging through the open seas, planning trips that last many weeks. EO4EU aims to limit the solution space and increase the throughput reducing the computational time. Such an approach will have a positive impact on ships travelling, towards their destination, as it will limit the time of the optimised route.

EO for Personalized Health care Services

The Personal Allergy Symptom Forecast System (PASYFO) was developed to assist allergy sufferers. Personalised information allows users to track pollen allergy symptoms. Europeans will be able to monitor their exposure to pollen allergens and receive allergy symptom forecasts for the next three days. PASYFO enables users to plan their outdoor activities more effectively during the vegetation season. With the information provided by PASYFO, users can improve their quality of life and rationalise their healthcare costs.