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\begin{document}

\title{Evaluating the recovery of beach-dune systems from the 2016 El Ni\selectlanguage{ngerman}ño
using unmanned aerial systems (UAS) and terrestrial laser scanning (TLS)\selectlanguage{english}}



\author[1]{Michael Grilliot}%
\author[2]{Ian Walker}%
\author[1]{Derek Heathfield}%
\affil[1]{Affiliation not available}%
\affil[2]{Arizona State University}%


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  \date{May 24, 2024}


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\begin{abstract}
This paper compares and contrasts UAS-based Structure from Motion (SfM)
and TLS survey methods as applied to evaluate the impacts of, and
recovery from, the extreme El Ni\selectlanguage{ngerman}ño 2015-16 on the seasonal geomorphic
and sediment budget responses of an embayed, high-energy beach-dune
system on the central coast of British Columbia, Canada. TLS and UAS
mapping campaigns over a two-year period provided seasonal bare-earth
digital terrain models (DTMs) and orthophoto mosaics. Spatial-temporal
change detection methods were used to quantify volumes of significant
erosion and deposition within the beach-dune system. The frequency and
magnitude of erosive events and aeolian activity were also estimated
from oblique, time-lapse photography. During the 2015-16 El Niño season,
elevated water levels and storm waves eroded the foredune and lowered
the beach surface by \textasciitilde{} 1m. Erosion was greatest in the
middle of the beach with dune scarping of over 2m where wave energy was
focused. Minor accretion occurred during the summer of 2016 on the upper
beach, and ramp rebuilding was observed mostly from slumping and
avalanching of existing dune sands. The following winter 2017 storm
season led to minor erosion on the beach and extensive incipient dune
development and sand ramp recovery fronting the foredune to an extent
close to pre-El Niño elevations. Comparison of change surfaces between
methods revealed limitations in the SfM method, namely due to vegetation
effects on DTM generation, which limit its ability to detect change in
the coastal environment. The costs, time, logistics, and accuracy for
both SfM and TLS survey methodologies for coastal geomorphic change
detection analysis is also evaluated. Combined, the UAS and SfM workflow
provides a competitive solution to more expensive and time-consuming
survey methods, such as TLS and aerial LiDAR, but its utility and
accuracy is highly dependent on research objectives and post-processing
techniques.%
\end{abstract}\selectlanguage{ngerman}%



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