Creation of river terrain data using region growing method based on point cloud data from UAV photography

The geo-spatial information in the river area is essential for river management such as river planning, flood analysis, and sediment load analysis. Recently, unmanned aerial vehicle (UAV) technology has been actively studied to acquire three-dimensional terrain data. However, the UAV acquired river terrain data is a digital surface model (DSM) that includes the height of a tree or grass in a river. It is different from the digital elevation model (DEM) required by river surveys. In this study, the ground point was extracted by using point cloud point obtained from UAV with Terra Scan software, and the DEM were constructed using the region growth algorithm. In order to evaluate the accuracy of the DEM data, the TRUE value of 100 test points was obtained by using virtual reference station (VRS) and total station survey equipment. As a result, the standard deviation of DSM and DEM were +/- 3.84 m and +/- 0.12 m, respectively. Furthermore, the cross section of DEM showed similar elevation values with cross section in the report of basic plan for Gap River. Therefore, DEM can be secured by applying the UAV point cloud based on region growth algorithm, and it can be effectively used for the river management tasks.