Drone-Based Monitoring to Remotely Assess a Beach Nourishment Program on Lord Howe Island

Author:

Kelaher Brendan P.1ORCID,Pappagallo Tommaso1,Litchfield Sebastian1,Fellowes Thomas E.2ORCID

Affiliation:

1. National Marine Science Centre, Southern Cross University, P.O. Box 4321, Coffs Harbour, NSW 2450, Australia

2. Geocoastal Research Group, Marine Studies Institute, The University of Sydney, Camperdown, NSW 2006, Australia

Abstract

Beach nourishment is a soft engineering technique that is used to combat coastal erosion. To assess the efficacy of a beach nourishment program on the northwest coast of Lord Howe Island, remotely coordinated drone-based monitoring was undertaken at Lagoon Beach. Specifically, hypotheses were tested that beach nourishment could increase the dune height and the width of the beach where the sand was translocated but would not have any long-term impacts on other parts of the beach. During the beach nourishment program, sand was translocated from the north end to the south end of Lagoon Beach, where it was deposited over 2800 m2. Lagoon Beach was monitored using a time series of 3D orthomosaics (2019–2021) based on orthorectified drone imagery. The data were then analysed using a robust before-after-control-impact (BACI) experimental design. Initially, a fully automated drone mapping program and permanent ground control points were set up. After this, a local drone pilot facilitated automated drone mapping for the subsequent times of sampling and transferred data to mainland researchers. As well as being more cost-effective, this approach allowed data collection to continue during Island closures due to the COVID-19 pandemic. After sand translocation, the south end of Lagoon Beach had a lower dune with more vegetation and a more expansive beach with a gentler slope than the prior arrangement. Overall, drone monitoring demonstrated the efficacy of the beach nourishment program on Lord Howe Island and highlighted the capacity for drones to deliver cost-effective data in locations that were difficult for researchers to access.

Funder

SCU DVCR Industry Seed

Publisher

MDPI AG

Subject

Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering

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