Estimation of flood inundation and depth during Hurricane Florence using
Sentinel-1 and UAVSAR data
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.