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https://hdl.handle.net/20.500.14279/35015| Title: | Artificial intelligence and Earth observation towards disaster risk reduction: the AI-OBSERVER’s research exploratory project | Authors: | Tzouvaras, Marios Votsis, Renos Fotiou, Kyriaki Prodromou, Maria Panagiotou, Constantinos F. Kalogirou, Eleftheria Christofi, Demetris A.D. Reis, Gerd Del Frate, Fabio Zacharatos, Haris Hadjimitsis, Diofantos G. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | Artificial Intelligence;Earth Observation;Disaster Risk Reduction;Environmental Hazards;Risk Assessment;GeoAI | Issue Date: | 19-Sep-2025 | Source: | Proceedings Volume 13816, Eleventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2025) | Project: | AI-OBSERVER: Enhancing Earth Observation capabilities of the Eratosthenes Centre of Excellence on Disaster Risk Reduction through Artificial Intelligence | Conference: | Eleventh International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2025) | Abstract: | The AI-OBSERVER project has received funding from the European Union’s Horizon Europe Framework Programme HORIZON-WIDERA-2021-ACCESS-03 (Twinning) under the Grant Agreement No. 101079468. The project started in October 2022 and has a duration of 36 months. The ERATOSTHENES Centre of Excellence (CoE) for Earth Observation, Space Technology and Geoinformation is the project coordinator, and the consortium also consists of two internationally leading research institutions, the German Research Centre for Artificial Intelligence (DFKI) from Germany and the University of Rome Tor Vergata (UNITOV) from Italy, and an industrial partner CELLOCK Ltd from Cyprus. With AI-OBSERVER project being currently in its last year, the efforts of ERATOSTHENES CoE are focused on the development of six risk assessment models for multi-hazard monitoring and assessment in Cyprus on i) Earthquakes, (ii) Landslides, (iii) Coastal erosion, (iv) Forest fires, (v) Floods and (vi) Marine Pollution. These are being developed by applying the enhanced skills and scientific background ERATOSTHENES CoE’s researchers acquired on the application of advanced Artificial Intelligence (AI)-based techniques on Earth Observation (EO) and geospatial datasets, via the various capacity building activities carried out during the 3 years of the project by the advanced partners, i.e., the German Research Centre for Artificial Intelligence (DFKI) from Germany, and the University of Rome Tor Vergata (UNITOV) from Italy. The overall methodology for these six models and some initial results are presented in this study. | URI: | https://hdl.handle.net/20.500.14279/35015 | ISBN: | 9781510695306 9781510695313 |
DOI: | 10.1117/12.3075493 | Rights: | Attribution 4.0 International | Type: | Conference Proceedings | Affiliation : | ERATOSTHENES Centre of Excellence German Research Center for Artificial Intelligence Università degli Studi di Roma "Tor Vergata" Cellock LTD Cyprus University of Technology |
Funding: | This study was carried out in the framework of AI-OBSERVER Twinning project (https://ai-observer.eu/) titled “Enhancing Earth Observation capabilities of the Eratosthenes Centre of Excellence on Disaster Risk Reduction through Artificial Intelligence” that is funded by the European Union with Grant Agreement No. 101079468. The authors also acknowledge ‘EXCELSIOR’: ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu) in which the Eratosthenes Centre of Excellence has been established. The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology. | Publication Type: | Peer Reviewed |
| Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
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| File | Description | Size | Format | |
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| Artificial Intelligence and Earth Observation.pdf | 561.6 kB | Adobe PDF | View/Open |
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