Abstract
Following over 20 years of manned airborne LiDAR in the remote sensing of geomorphological change in coastal environments, rapid advancements in unmanned aerial vehicle (UAV) technologies have expanded the possibilities of acquiring very high-resolution data efficiently over spatial-temporal scales not previously feasible. This study employed a new Simultaneous Localisation and Mapping (SLAM)–based LiDAR system (“Hovermap”) across a segment of coastal sand dune of Bribie Island, Queensland, Australia. The study area was identified by the local council as an area of interest over concern that continued erosion at an existing blowout could result in cutting off northern Bribie Island and adversely affect hydrodynamic processes of Pumicestone Passage, its shoreline, and its associated infrastructure. Here, we employed the Hovermap within a multi-temporal design in which four, quarterly, surveys undertaken over a 9-month period from July 2017 to April 2018. On the first survey, a Leica P40 (P40) terrestrial laser scanner (TLS) was also deployed across the study area to facilitate a performance comparison. Hovermap reported a mean point cloud density of 2532 ± 170 pts.·m-2, ground sample distance (GSD) of 0.02 ± 0.001 m, and RMSE of 0.050 ± 0.31 m relative to ground control points (GCPs). Three-dimensional mesh objects were derived from all point clouds obtained and evaluated in terms of elevation and slope with mesh-to-mesh deviations and volumetric change (cubature) analysis examined over consecutive surveys. The Hovermap closely matched results of the P40 with measures of elevation and slope differing by approximately 2% and 7%, respectively. Mean vertical deviation (0.01 ± 0.03 m) and cubature (~ 2.5 m3 net difference) results also showed close agreement. Due to stable wave conditions between the first three surveys, minimal changes in beach topography were observed, whilst pronounced erosion and scarping of the foredune were measured during the final survey. This erosion was evidenced from changes in mean elevation (− 16%), slope (+ 25%), and deviation (+ 86%) relative to the mean measurements over the first three survey dates. In addition, a net loss of approximately -1295 m3 of sand was measured between the final two survey dates (January–April 2018). This is supported by local marine weather data in which a significant increase in local wind speeds (ANOVA, F(1,180) = 6.257, p = 0.013) and wave heights (ANOVA F(1,180) = 41.769, p ≤ 0.001) were recorded over the same interval. The results presented here are first to demonstrate that UAV LiDAR performance was robust in a typical, moderate-energy, sandy beach and is suited for the detection and evaluation of coastal morphologic change at microspatial and temporal scales.
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