UAV Lidar vs. Structure-from-Motion (SfM) Photogrammetry for Coastal Dune Monitoring: A Two-Year Multi-Temporal Case Study from the Southern Baltic Sea

Unmanned aerial vehicles (UAVs) are increasingly used for high-resolution coastal monitoring. This study compares two widely used approaches for deriving digital elevation models (DEMs) from eight repeat UAV surveys (coacquired lidar + red–green–blue [RGB] in the same flight): (1) UAV lidar and (2) structure-from-motion photogrammetry (SfM) based on RGB imagery. A total of 16 DEMs (8 field campaigns in both 2022 and 2023) acquired with a DJI Matrice 300 real-time kinematic drone equipped with a Zenmuse L1 sensor over a 1-km dune–beach system in Mrzeżyno, southern Baltic coast (Poland). Using an automated transect-based workflow (895 cross-shore profiles), shoreline position, beach and dune widths, elevations, slopes, and volumetric change were extracted and related to tide-gauge–based hydrometeorological conditions using deep neural networks and complementary driver-consistency analyses. Both approaches captured consistent temporal trends and converged on the same dominant environmental drivers, with storm activity (event count and duration) together with wave and sea-level conditions explaining most of the observed variability. Differences were largest over water surfaces and locally within vegetation-affected dune areas, where lidar produced fewer artifacts. Despite these local deviations, the net beach + dune volume change between the first and last survey differed by only 0.48% between lidar and SfM, indicating that SfM can provide comparable coastal-change information for many monitoring tasks when survey geometry and quality control are carefully managed.