| Issue |
E3S Web Conf.
Volume 708, 2026
7th International Conference on Smart Applications and Water Information Systems: “Intelligent Systems, Geospatial Technologies and Modeling for the Sustainable Management of Water Resources” (SAWIS 2025)
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 7 | |
| Section | GIS, AI Applications, and Risk Assessment | |
| DOI | https://doi.org/10.1051/e3sconf/202670803001 | |
| Published online | 30 April 2026 | |
Flood prevention based on geographic information systems, big data, and artificial intelligence: A systematic review
LaRSI Laboratory, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco
Abstract
This systematic review analyzez how emerging technologies like (GIS, Big Data, AI) improve flood prevention. Following the PRISMA protocol, we selected and analyzed 12 studies from Scopus, Science Direct, and IEE (2014-2024) focusing on remote sensing, real time data processing, and machine learning algorithms (Random Forest, SVM, CNN) for flood susceptibility mapping. Results demonstrate that integrated approaches significantly enhance prediction accuracy, with models achieving 80-99% precision in delineating risk zones. Despite challenges related to data quality, the of high-resolution satellite imagery and AI offers promising pathways for anticipatory flood risk management.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.