Dai, W.Q.; Li, H.; Zhou, Z.; Cybele, S.; Lu, C.Z.; Zhao, K.; Zhang, X.Y.; Yang, H.T., and Li, D.Y., 2018. UAV Photogrammetry for Elevation Monitoring of Intertidal Mudflats. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 236–240. Coconut Creek (Florida), ISSN 0749-0208.

Elevation is a significant factor in analyzing the topographical evolution of intertidal mudflats. However, the difficult access to the site due to the muddy sediment and the tidal creeks make the traditional observations more arduous. Unmanned aerial vehicle (UAV) platforms are nowadays a low-cost source of data for surveillance, mapping and 3D modeling. A multi-rotary UAV was set up with a camera to acquire multi-view images of mudflats in the Yancheng Rare Birds Nature Reserve, China. The procedure for deriving 3-D model was based on the Structure from Motion (SfM) algorithm for Multiview Stereophotogrammetry. Ground control points (GCPs), measured by Real Time Kinematic (RTK), were utilized as reference coordinates to generate the 3-D model and Digital Elevation Model (DEM). Ground references were applied to validate the accuracy of the DEM. However, due to the inhomogeneity and complexity of the ground, representing overall height with a single point would lead to uncertainty. In order to make the accuracy evaluation tend to reality, we employed circular ground references (CGRs) to validate the DEM. The CGRs were measured by a Rod Surface Elevation Table (Rod-SET) system within a circular area of radius 1.4 meter. For each survey, a DEM are computed by SfM photogrammetry, providing a surface representation of the study area. The spatial resolution for DEM is 7.5cm. With reference to the CGRs data, the DEM has a high vertical accuracy with a root mean square error (RMSE) of 10 cm. Repeated acquisitions of high-resolution DEMs enable monitoring of erosion and deposition, computing volumetric changes through time, and assessing sediment budgets. The results demonstrated that UAV can be used for regular mudflats monitoring activities and provide accurate insights into geomorphological processes.