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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

  • Climate Change Impacts On Regional Economics In South Asia
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Asia-Pacific Journal of Regional Science Aims and scope Submit manuscript

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.

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Source: Author’s creation from HDX 2021

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Correspondence to Tofael Ahamed.

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Appendix

Appendix

See Figs. 5, 6, 7.

Fig. 5
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Projected precipitation anomaly for a Bangladesh and b Sylhet division (study area) for 2020–2039 in different shared socioeconomic pathways (SSPs) (Reference period 1994–2014) (IPCC, 2020) Source: World Bank 2022

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The geographical locations of the selected subdistricts from the north-eastern region of Bangladesh

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Sentinel-2 false color composite scenarios of three study areas: a Tahirpur, b Gowainghat, and c Kulaura from 2017–2019

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Islam, M.M., Ahamed, T. Development of a near-infrared band derived water indices algorithm for rapid flash flood inundation mapping from sentinel-2 remote sensing datasets. Asia-Pac J Reg Sci 7, 615–640 (2023). https://doi.org/10.1007/s41685-023-00288-5

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  • DOI: https://doi.org/10.1007/s41685-023-00288-5

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