article · Springer Link (Chiba Institute of Technology)
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.
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DOI: 10.1051/e3sconf/202670803001/pdf
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