Project

H2020-EOPEN Open interoperable platform for unified access and analysis of Earth Observation data

Goal: The project relies on (α) the infrastructures and research developed in BEYOND Center of Excellence, (β) the roadmap resulted from GEO-CRADLE in regards to the priorities concerning the gathering and channeling of information over extended geographic areas in the agriculture sector, and (c) the Copernicus DataHubs operated by the BEYOND Center of Excellence (e.g. Hellenic Mirror Site, DIASHub).
The EOPEN project studies the needs of users wanting to use or include EO data in in their big data analysis problems. The EOPEN concept is directed towards making EO data easy to use by the involved stakeholders. To achieve this, the EOPEN develops an exploitation platform that supports Big Data analysis by offering: 1. A library of commonly needed EO data processing capabilities and modules for data preparation; 2. Services and the capabilities to make optimal use of existing EO data sources and processing capabilities; 3. A framework supporting the Big Data Use Case lifecycle; 4. An infrastructure to perform Big Data processing and analytics. The contribution of the NOA is to engage the stakeholder community, and provide unhindered access to the Copernicus big satellite data so as to meet requirements concerning agricultural sector and food security over vast geographic areas. NOA leverages on high resolution of Sentinel 1-2 data together with crowd data and crowdsourcing techniques. The process demonstrates innovative EO information products easily used on a world basis in EU and non-EU countries (South Korea & China) for ensuring food insecurity. The innovation here generates reliable, accurate, timely and sustained crop monitoring and yield forecasts, supporting to the local/regional agriculture. This has a direct impact on food policies and security; reducing food poverty; boosting local business and investment opportunities. A web-application is built on a user centric approach transforming needs and requirements.

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Project log

Stelios Andreadis
added 2 research items
Artificial Intelligence (AI) technologies are getting deeper and deeper into remote sensing and satellite image processing offering value-added products and services in a real-time manner. Deep learning techniques applied on visual content are able to infer accurate decisions about concepts and events in an automatic way, based on Deep Convolutional Neural Networks which are trained on very large external image collections in order to transfer knowledge from them to the considered task. Existing emergency management services focus on the detection of flooded areas, without the possibility to infer if a road from point A to a point B is passable or not. To that end, we propose an automatic road passability service that is able to deliver the parts of the road network which are not passable, using satellite image patches. Experiments and fine-tuning on an annotated benchmark collection indicates the most suitable model among several Deep Convolutional Neural Networks.
EOPEN (https://eopen-project.eu/) is a project which has received funding from the European Union’s Horizon 2020 research and innovation programme under the topic EO Big Data Shift in 2017 and has a duration of 3 years, starting from November 2017. In this work, we present the concept of the project, its objectives and the lessons learnt after almost one year of project lifetime, as a follow-up to our previous project presentation at ESA BiDS’17 in Toulouse, France.
Ilias Gialampoukidis
added a research item
The poster presents an overview of the EOPEN project (H2020-776019) funded by the European Commission. Details can be found on the project website: http://eopen-project.eu/
Ilias Gialampoukidis
added a project goal
The project relies on (α) the infrastructures and research developed in BEYOND Center of Excellence, (β) the roadmap resulted from GEO-CRADLE in regards to the priorities concerning the gathering and channeling of information over extended geographic areas in the agriculture sector, and (c) the Copernicus DataHubs operated by the BEYOND Center of Excellence (e.g. Hellenic Mirror Site, DIASHub).
The EOPEN project studies the needs of users wanting to use or include EO data in in their big data analysis problems. The EOPEN concept is directed towards making EO data easy to use by the involved stakeholders. To achieve this, the EOPEN develops an exploitation platform that supports Big Data analysis by offering: 1. A library of commonly needed EO data processing capabilities and modules for data preparation; 2. Services and the capabilities to make optimal use of existing EO data sources and processing capabilities; 3. A framework supporting the Big Data Use Case lifecycle; 4. An infrastructure to perform Big Data processing and analytics. The contribution of the NOA is to engage the stakeholder community, and provide unhindered access to the Copernicus big satellite data so as to meet requirements concerning agricultural sector and food security over vast geographic areas. NOA leverages on high resolution of Sentinel 1-2 data together with crowd data and crowdsourcing techniques. The process demonstrates innovative EO information products easily used on a world basis in EU and non-EU countries (South Korea & China) for ensuring food insecurity. The innovation here generates reliable, accurate, timely and sustained crop monitoring and yield forecasts, supporting to the local/regional agriculture. This has a direct impact on food policies and security; reducing food poverty; boosting local business and investment opportunities. A web-application is built on a user centric approach transforming needs and requirements.