Performance of Large-Scale Particle Image Velocimetry Method for Surface Velocity Identification Based on Drone Height Variation

Abstract Information on flows is essential for coastal management and adaptation to climate change. The traditionally used methods for observing flows require contact with the surface water. The Large-Scale Particle Image Velocimetry (LSPIV) method can complement this measurement strategy to measure surface velocities in various environments, including rivers and estuations, and is based on image techniques. The aim of this study was to identify surface currents at various drone heights and then validate the results generated from the LSPIV method by comparing them with observation data. Field data were collected at Cimanis Estuary, Cirebon, over two periods: August 19–22 and September 27–28, 2023. The field data observation included surface velocity, drone videos, and ground control points. Drone height measurements were taken at 20, 30, 40, 50, and 70 meters. To verify the accuracy of the LSPIV, several methods were used, including the RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and MAPE (Mean Absolute Percentage Error). The drone height of 20 meters yielded the lowest RMSE, MAE, and MAPE, which were 0.08 m/s, 0.06 m/s, and 5.6% for velocity magnitude and 10.74 degree, 10.69 degree, and 3.7% for velocity direction, respectively. This suggests that the most precise LSPIV data were collected during the drone survey at an elevation of 20 meters.