September 12, 2025PLOS WaterOpen Access

A comparative analysis of urban and peri-urban flood identification using SAR imagery

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This research compares flood detection methods using SAR imagery in urban and peri-urban areas, highlighting performance metrics.

Analysis shows the cloud-based platform enhances flood detection efficacy through diverse methodologies.
Using Sentinel-1 SAR images, the study evaluates precision, recall, and accuracy across urban and peri-urban settings.
The constant threshold Change Detection Approach achieved the highest accuracy in peri-urban regions among tested methods.
Machine learning classifiers outperformed traditional methods in urban settings, indicating significant advances in flood mapping.

Mehedi et al. (2025) studied this question.

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