Integration of Different Density UAV Lidar and Single Beam Echo Sounder (SBES) for River and Riparian Area Digital Terrain Model (DTM) Construction

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Rivers and riparian areas are vital components of ecosystems, but accurately modeling their terrain presents challenges, especially in detecting the river surface. This paper proposes an integrated approach that combines UAV LiDAR and Single Beam Echo Sounder (SBES) data to construct a Digital Terrain Model (DTM) of river and riparian areas. The objective is to overcome the limitations posed by water, which absorbs near-infrared laser energy, resulting in weak or absent LiDAR returns. Different UAV LiDAR densities were examined to determine the optimal configuration for capturing riparian areas. Evaluation of the results utilized various metrics, including root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), mean bias error (MBE), and correlation coefficient (CC). Three ground filtering methods were implemented and assessed: morphological filters, adaptive triangulated irregular network (ATIN) filtering, and above-ground level (AGL) filtering. Among the evaluated methods, the DTM constructed using ATIN with an 80-meter flight configuration yielded the most accurate results. It achieved an RMSE of 0.18m, an MSE of 0.03m, an MAE of 0.17m, an MBE of 9.08m, and a CC of 1.00. Comparatively, other methods exhibited higher error values and lower correlation coefficients. The findings highlight the efficacy of ATIN filtering in conjunction with an 80-meter UAV LiDAR flight for obtaining reliable DTMs of river and riparian areas. This approach demonstrates significant improvement in accuracy, particularly in terms of RMSE and MSE. The derived DTM can be a valuable tool for safeguarding and managing these critical ecosystems. In summary, this paper successfully addresses the challenge of modeling river and riparian terrains by integrating UAV LiDAR and SBES data. By employing ATIN filtering with an 80-meter flight configuration, the study achieves a highly accurate DTM. By employing ATIN filtering with an 80-meter flight configuration, the study achieves a precise, high DTM with minimal error. The developed model contributes to protecting and preserving river and riparian ecosystems.