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Sentinel-1-Based Water and Flood Mapping: Benchmarking Convolutional Neural Networks Against an Operational Rule-Based Processing Chain., , , , и . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2022)Time-series analysis of Sentinel-1/2 data for flood detection using a discrete global grid system and seasonal decomposition., , , , , и . Int. J. Appl. Earth Obs. Geoinformation, (мая 2023)Using UAV Data to Improve the Situational Awareness for First Responders in Disaster Management: The Example of Flooding in the AHR Valley, Germany., , , , и . IGARSS, стр. 934-937. IEEE, (2023)Enabling Global Processing of Reference Water Products for Flood Mapping using Kubernetes and STAC., , , , , и . IGARSS, стр. 414-417. IEEE, (2023)Using Sentinel-1/2 Time Series Data to Investigate Surface Water Changes after the Nova Kakhovka Dam Destruction in Ukraine., , , , и . IGARSS, стр. 2659-2662. IEEE, (2024)A Multi-Sensor System for Surface Water Extraction: Application Examples in the Context of Disaster Management., , и . IGARSS, стр. 1354-1357. IEEE, (2024)AD-HOC Situational Awareness During Floods Using Remote Sensing Data and Machine Learning Methods., , , , , , , , и . IGARSS, стр. 1166-1169. IEEE, (2023)Toward Scalable Damage Assessment for Rapid Disaster Response., , , , и . IGARSS, стр. 3902-3905. IEEE, (2024)Estimating Ensemble Likelihoods for the Sentinel-1-Based Global Flood Monitoring Product of the Copernicus Emergency Management Service., , , , , , , , , и 1 other автор(ы). IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2023)Automatic Near-Real Time Flood Extent and Duration Mapping based On Multi-Sensor Earth Observation Data., , , , и . IGARSS, стр. 3243-3246. IEEE, (2020)