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Estimation of flood inundation and depth during Hurricane Florence using Sentinel-1 and UAVSAR data
  • Sananda Kundu,
  • Venkataraman Lakshmi,
  • Raymond Torres
Sananda Kundu
University of South Carolina

Corresponding Author:[email protected]

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Venkataraman Lakshmi
University of Virginia
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Raymond Torres
University of South Carolina
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Abstract

We studied the temporal and spatial changes in the flood water elevation and variation in the surface extent due to the flooding resulting from Hurricane Florence (September 2018) using the observation from an Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) and Sentinel-1. The novelty of this study lies in the estimation of changes in the flood depth during the hurricane, and investigating the best method. Overall, flood depths from SAR were observed to be well-correlated with the spatially distributed ground-based observations (R2 = 0.79 to 0.96). The corresponding change in water level (∂h/∂t) compared well between the remote sensing approach and the ground observations (R2 = 0.90). This study highlights the potential use of SAR remote sensing for inundated landscapes (and locations with scarce ground observations), and it emphasizes the need for more frequent SAR observations during flood to provide spatially distributed and high temporal repeat observations of inundation.
2022Published in IEEE Geoscience and Remote Sensing Letters volume 19 on pages 1-5. 10.1109/LGRS.2022.3165444