Quantifying Flash Flood Inundation and Assessing Damage Using Satellite Earth Observations: The Case of 2022 Flash Flood in Bangladesh
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TGNH_A_2614729_O.pdf
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4.15 MB
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Adobe PDF
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Author(s)
Sariful, Md
Mitra, Juthi Rani
Rahman, Munshi Khaledur
Date Issued
January 2, 2026
Journal
Geomatics, Natural Hazards and Risk
Publisher
Taylor & Francis
Citation
Islam, M. S., Mitra, J. R., & Rahman, M. K. (2026). Quantifying flash flood inundation and assessing damage using satellite earth observations: the case of 2022 flash flood in Bangladesh. Geomatics, Natural Hazards and Risk, 17(1).
Version
Final published version
Abstract
Floods pose significant threats to Bangladesh, frequently causing the loss of lives, properties, infrastructure, and livelihoods. This study examines the spatial and temporal dynamics of the 2022 Sylhet flood by integrating Sentinel-1 Synthetic Aperture Radar (SAR) imagery with socioeconomic datasets. Otsu thresholding method was used to estimate water extent before, during, and after the 2022 flood event in the Sylhet region. Results suggest that over 1,600 km² of land in Sylhet division was inundated, with Habiganj district experiencing the highest surge. More than half a million people were directly impacted, alongside significant damage to cropland and urban areas. Furthermore, the study highlighted substantial impacts on urban built-up areas and cropland across districts. Cumulative cropland damage increased from 3376.30 km² in June to 4701.30 km² in July, indicating severe consequences for agricultural productivity. Concurrently, the affected built-up areas were found to be 40.9 km², emphasizing the impact on human settlements. By providing a detailed assessment of flood extent and damage, this study provides valuable insights for policymakers, planners, and disaster management authorities. The findings support the development of targeted strategies for flood risk reduction, agricultural resilience, and the mitigation of future disaster impacts in vulnerable regions of Bangladesh.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1080/19475705.2026.2614729
