EO4EU Platform tools: Advancing Access to Earth Observation Data
The EO4EU Project has released a comprehensive set of tools within the EO4EU Platform to facilitate the understanding of Earth Observation (EO) data. These tools are designed to improve data accessibility, processing, and interpretation for research, policy, and innovation purposes.
Data Analytics and Visualisation
The platform provides real-time data analysis, interpretation of environmental observations, and interactive mapping. Features include a text and annotation-based search engine and personalised dashboards supported by statistical metrics.
Knowledge Graph-Based Decision Making
A graph-based text representation enables the extraction of structural and textual features from the Knowledge Graph. This supports querying and analysis of datasets integrated from sources such as ADAM, ADS, CDS, EUMETSAT, and Sentinel missions.
The XR system introduces augmented reality (AR) and virtual reality (VR) interfaces for EO data. These allow users to explore geolocated datasets in real-world contexts or in 3D virtual environments.
The platform includes a marketplace that provides access to artificial intelligence and machine learning models, algorithms, techniques, metadata, data models, code, and documentation.
Generic Machine Learning Pipeline for Semantic Annotation
To reduce reliance on labelled datasets, the pipeline applies unsupervised learning methods, such as SimCLR, to develop transferable representations of EO data.
The Fusion Engine combines data from multiple sources and processes it through algorithmic pipelines, with the capacity to refine datasets and generate new products. High-performance computing (HPC) and GPU environments are used within Kubeflow to ensure efficiency.
The Function-as-a-Service (FaaS) component enables users to execute code in response to events without managing the underlying infrastructure, streamlining cloud-based operations.
A Unified Platform for EO Data
Through these tools, the EO4EU Platform provides a framework for analysing, visualising, and applying Earth Observation data in a variety of contexts. This integration supports evidence-based decision-making and research by offering streamlined access to heterogeneous data sources.
