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Modelling cyclone-induced flood impact assessment and quantifying the effect on biophysical dynamics employing geospatial techniques in South–West of Bangladesh

Author

Listed:
  • Md Tanvir Miah

    (Khulna University)

  • Md. Rakibul Hasan

    (Khulna University)

  • Jannatun Nahar Fariha

    (Khulna University)

  • Jarin Jannati Tammi

    (RMIT University)

  • Raiyan Raiyan

    (Khulna University)

  • Pankaj Kanti Jodder

    (University of North Carolina, Charlotte)

  • Remon Ahmed Mishu

    (Khulna University)

  • Salima Ahamed Usha

    (Khulna University)

  • Md Zakir Hossain

    (Khulna University)

  • Khan Rubayet Rahaman

    (St. Mary’s University)

Abstract

This article investigates the influence of climatic and geographical characteristics in south-western region of Bangladesh on the temporal dynamics of post-cyclone impacts, with a critical focus on biophysical contexts. By quantitatively assessing the environmental consequences of cyclones Amphan (2020), Yaas (2021), Mocha (2023) and Remal (2024), the study offers a nuanced understanding of flood damage extent and vegetation health, measured through advanced remote sensing and geospatial techniques. Using Sentinel-1 (GRD) and Sentinel-2 (MSI) satellite imageries from 2020 to 2024, the study has examined post-cyclone changes of vegetation health and flood damage extent using available indices such as Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI). The results exhibit substantial spatial disparities occurred due to the cyclone events, with NDVI variations ranging from − 0.124 to 0.546 (Amphan), − 0.033 to 0.498 (Mocha), − 0.086 to 0.458 (Yaas), and − 0.061 to 0.362 (Remal), indicating significant ecological stress. Corresponding SAVI changes ranged from − 0.001 to 0.396 (Amphan), − 0.029 to 0.338 (Mocha), − 0.002 to 0.345 (Yaas), and − 0.0524 to 0.269 (Remal). Negative indices underscore potential vegetation degradation, while positive values indicate resilience or post-cyclone recovery. Furthermore, flood damage analysis indicates to a more severe and unevenly distributed impact than previously recognized, particularly in areas with pre-existing vulnerabilities with the damage extent variations between − 35.918 to − 2.0093 (Amphan), − 35.334 to − 4.4059 (Mocha), − 34.806 to − 0.94921 (Yaas), and − 48.469 to 0.00255 (Remal). The Geographically Weighted Regression (GWR), model demonstrates a robust relationship, with r2 values of 0.894, 0.889, 0.899, and 0.95, indicating that approximately 85% of the ecological changes are driven by fluctuations of vegetation due to flood. The insight from this research provides a foundation of flood damage assessment technique occurred by cyclones in a short span of time to aid immediate policy recommendations to enhance resilience in remote areas of the coastal regions of Bangladesh.

Suggested Citation

  • Md Tanvir Miah & Md. Rakibul Hasan & Jannatun Nahar Fariha & Jarin Jannati Tammi & Raiyan Raiyan & Pankaj Kanti Jodder & Remon Ahmed Mishu & Salima Ahamed Usha & Md Zakir Hossain & Khan Rubayet Rahama, 2025. "Modelling cyclone-induced flood impact assessment and quantifying the effect on biophysical dynamics employing geospatial techniques in South–West of Bangladesh," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(10), pages 11731-11771, June.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:10:d:10.1007_s11069-025-07259-3
    DOI: 10.1007/s11069-025-07259-3
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    References listed on IDEAS

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