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Persistent Identifier
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perma:LIST.DTOEHB |
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Publication Date
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2026-07-06 |
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Title
| The fully-automatic Sentinel-1 Global Flood Monitoring service: Scientific challenges and future directions [* Cross-Reference *] |
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Other Identifier
| https://doi.org/10.1016/j.rse.2025.115108
SCOPUS_ID:105023680087 |
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Author
| Wagner, Wolfgang (TU Wien, EODC Earth Observation Data Centre GmbH) - ORCID: 0000-0001-7704-6857
Bauer-Marschallinger, Bernhard (TU Wien) - ORCID: 0000-0001-7356-7516
Roth, Florian (TU Wien) - ORCID: 0000-0002-8589-0182
Raiger-Stachl, Tobias (EODC Earth Observation Data Centre GmbH)
Reimer, Christoph (EODC Earth Observation Data Centre GmbH) - ORCID: 0000-0003-3554-7332
McCormick, Niall (European Commission Joint Research Centre) - ORCID: 0000-0003-1761-7771
Matgen, Patrick (Luxembourg Institute of Science and Technology) - ORCID: 0000-0001-6668-4693
Chini, Marco (Luxembourg Institute of Science and Technology) - ORCID: 0000-0002-9094-0367
Li, Yu (Luxembourg Institute of Science and Technology) - ORCID: 0000-0003-1818-6643
Martinis, Sandro (Deutsches Zentrum für Luft- und Raumfahrt (DLR)) - ORCID: 0000-0002-6400-361X
Wieland, Marc (Deutsches Zentrum für Luft- und Raumfahrt (DLR)) - ORCID: 0000-0002-1155-723X
Kraft, Franziska (Deutsches Zentrum für Luft- und Raumfahrt (DLR))
Festa, Davide (TU Wien) - ORCID: 0000-0001-8398-863X
Hassaan, Muhammed (TU Wien)
Tupas, Mark Edwin (TU Wien, University of the Philippines Diliman) - ORCID: 0000-0002-8227-5299
Zhao, Jie (TU Wien, Technische Universität München) - ORCID: 0000-0002-9638-3792
Seewald, Michaela (GeoVille GmbH)
Riffler, Michael (GeoVille GmbH)
Molini, Luca (CENTRO INTERNAZIONALE IN MONITORAGGIO AMBIENTALE - FONDAZIONE CIMA)
Kidd, Richard (EODC Earth Observation Data Centre GmbH)
Briese, Christian (EODC Earth Observation Data Centre GmbH) - ORCID: 0000-0001-5424-1609
Salamon, Peter (European Commission Joint Research Centre) - ORCID: 0000-0002-5419-5398 |
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Point of Contact
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LIST RDS (LIST) |
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Description
| Sentinel-1 is a unique resource for global flood monitoring, providing systematic, weather-independent Synthetic Aperture Radar (SAR) imagery with unprecedented coverage. To overcome limitations of on-demand flood mapping services that depend on human operators to collect and interpret satellite images, a fundamentally new approach was adopted by the Global Flood Monitoring (GFM) service. This service, which was launched in 2021 as part of the Copernicus Emergency Management Service (CEMS), processes all Sentinel-1 land images acquired in VV polarisation fully automatically in near-real time. This article presents the first comprehensive analysis of GFM’s scientific achievements and challenges during its initial years of operation. To map floods reliably under diverse environmental conditions, GFM combines three complementary flood-mapping algorithms with reference water datasets to differentiate flooded areas from permanent and seasonal water bodies. The service also offers a novel flood-likelihood layer and contextual information to highlight areas where flood mapping is unreliable or not feasible. These data layers were derived from a global 20 m backscatter datacube containing approximately 379 billion land surface pixels. This datacube also made it possible to generate the first global Sentinel-1 flood archive (2015 to present). Our performance analysis shows that GFM typically delivers flood maps within five hours of image acquisition. However, a significant percentage of floods may go undetected due to coverage gaps. Initial evaluation results show that good accuracies are achieved for larger-scale floods and regions in the temperate and tropical zones, while accuracies are lower for smaller-scale floods and arid environments. The GFM service will continue to improve service quality by enhancing flood detection capabilities using improved algorithms and additional data, such as the VH channel from Sentinel-1 or L-band data from the upcoming ROSE-L mission. (2026-01-15)
***This entry has been automatically imported via Infodoc(ASO) CSV by LIST harvest scripts. Please refer to https://doi.org/10.1016/j.rse.2025.115108 for the original and latest version of the dataset and data downloads*** (2026-06-04) |
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Subject
| Earth and Environmental Sciences |
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Keyword
| Copernicus
Datacube
Flood monitoring
Inland water
SAR
Sentinel-1 |
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Funding Information
| Bundesministerium für Wirtschaft und Energie: 939866-IPR-2020 |
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Deposit Date
| 2026-01-15 |
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Data Type
| Article |
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Data Source
| Remote Sensing of Environment; ISSN: 00344257, vol. 333, 2026 |