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Development of a near-infrared band derived water indices algorithm for rapid flash flood inundation mapping from sentinel-2 remote sensing datasets

Author

Listed:
  • Md. Monirul Islam

    (University of Tsukuba
    Bangladesh Agricultural University
    CSIRO)

  • Tofael Ahamed

    (University of Tsukuba)

Abstract

Rapid satellite-based flash flood inundation mapping and the delivery of flash flood inundation maps during a flash flood event for wetland communities can provide valuable information for decision-makers to put relief measures and emergency responses in place without delay. With remote sensing techniques, flash flood mapping of large areas, basically wetlands, can be done quickly with a high level of precision through different water indices. This study developed an algorithm for rapid flash flood inundation mapping for crisis management through the demarcation of the most flash flood-inundated areas in the Haor Basin (wetlands) of Bangladesh by utilizing high-resolution Sentinel-2 remotely sensed data. The algorithm applied here involves near-infrared (NIR) spectral band-derived indices, namely, a normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) to develop a rapid flash flood water detection technique integrating three year (2017–2019) datasets before and after flash floods. A simple threshold method was created to cluster the data and identify the flash flood pixels in the imagery using a density slicing technique followed by natural break analysis. Calculations were then made to estimate the flash flood (inundated), mixed pixels and non-inundated pixels for each year and three combinations. NDVI and NDWI, as well as their combinations (NDVI-NDWI), were remarkably effective for extracting inundation, non-inundation and mixed pixels. Additionally, highly consistent results were obtained for all inundation classes in the studied areas, confirming that NIR-derived indices can effectively detect water pixels. However, a higher inundation pixel value was observed in the Tahirpur Subdistrict compared with the other two study areas (Gowainghat and Kulaura). The developed NIR band-derived water indices algorithm produced more than 80.0% accuracy to detect water-related pixels when verified with ground reference points. As shown by these results, the developed NIR band-derived water indices were capable of effectively detecting flash flood water turbidity in wetland areas. Therefore, these NIR band-derived water indices can be applied for rapid flash flood inundation mapping just after a flash flood occurrence for immediate decisions to support affected farmers.

Suggested Citation

  • Md. Monirul Islam & Tofael Ahamed, 2023. "Development of a near-infrared band derived water indices algorithm for rapid flash flood inundation mapping from sentinel-2 remote sensing datasets," Asia-Pacific Journal of Regional Science, Springer, vol. 7(2), pages 615-640, June.
    • Handle: RePEc:spr:apjors:v:7:y:2023:i:2:d:10.1007_s41685-023-00288-5
    DOI: 10.1007/s41685-023-00288-5
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    References listed on IDEAS

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    1. Md. Shahinoor Rahman & Liping Di, 2017. "The state of the art of spaceborne remote sensing in flood management," 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. 85(2), pages 1223-1248, January.
    2. Ehsan H. Chowdhury & Quazi K. Hassan, 2017. "Use of remote sensing data in comprehending an extremely unusual flooding event over southwest 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. 88(3), pages 1805-1823, September.
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    Cited by:

    1. Tofael Ahamed, 2023. "Special issue on the assessment of climate change impacts on regional economics in South Asia," Asia-Pacific Journal of Regional Science, Springer, vol. 7(2), pages 323-328, June.

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