A multi-source remote sensing-based geocommunication tool for global flood monitoring and management
Document Type
Article
Publication Date
8-2025
Keywords
Fast global flood monitoring, Multi-source remote sensing, Sentinel-1 and Sentinel-2 data, Google Earth Engine platform, Multi-disciplinary information
Abstract
Global warming is expected to increase the frequency of extreme flooding, making rapid and accurate flood mapping crucial for effective risk assessment. Many governmental agencies and organizations are developing flood risk assessment tools; however, due to the lack of observational records, some rely on probabilistic generated data, uncalibrated simulations, or terrain-based methods, all of which are subject to various types of uncertainty. Although remote sensing provides valuable flood data with global coverage, single-source reliance is constrained by satellite revisit rates, resolution, weather conditions, and sensor limitations. To address these challenges, this study introduces a user-friendly application on the Google Earth Engine (GEE) platform that enables near-real-time global flood mapping using a multi-source remote sensing approach. By leveraging optical and SAR imagery, the App ensures improved water detection accuracy and supports all-weather and day/night monitoring. Our results show SAR and optical flood inundation maps agree up to 80 %. Beyond flood mapping, the tool leverages GEE datasets to extract multi-disciplinary information, such as population exposure and affected residential, urban, and cropland areas, to support timely decision-making. For example, during the Sylhet, Bangladesh flood, the tool identified over 300,000 people potentially affected and approximately 600 km2 of cropland inundated. This research presents one of the first global-scale, rapid, multi-source flood mapping tools tailored to both expert users and non-expert decision-makers. It offers a practical solution to current data limitations and supports more informed emergency response, planning, and climate resilience efforts to foster communication across scientific, policy, management, and operational communities.
Citation
Ebrahim Hamidi, Brad G. Peter, Hamed Moftakhari, Hamid Moradkhani, A multi-source remote sensing-based geocommunication tool for global flood monitoring and management, International Journal of Applied Earth Observation and Geoinformation, Volume 142, 2025, 104701, ISSN 1569-8432, https://doi.org/10.1016/j.jag.2025.104701.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Web of Science
Elsevier