Creation of rwaar: rapid water analysis algorithm for response & recovery, a rapid method for detection and mapping of flooding from hurricane ian using sentinel-2 multispectral imagery

Sherry Young,Chaowei Yang

IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM(2023)

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摘要
This study introduces a water index coined RWAAR: Rapid Water Analysis Algorithm for Response and Recovery for rapid flood detection using only freely available Sentinel-2 imagery. RWAAR exploits differences in spectral signatures of water, clouds, soil, concrete, asphalt, and vegetation in the following Sentinel-2 bands: band 2 (blue), band 8a (NIR), and band 11 (SWIR) to automatically extract pixels containing surface water. RWAAR was used to map flood inundation from Hurricane Ian using Sentinel-2 Level-2A imagery that was collected on September 30th, 2022. When compared to manually classified NOAA very high-resolution aerial imagery there was a 94.4% match. Current indices, NDWI and MNDWI were also tested and then compared to the NOAA imagery. For this location, NDWI had only a 61.3% match while MNDWI had a match of only 53.2%; however, more testing is needed and ongoing.
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关键词
NDWI,MNDWI,Ian,flooding
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