We outline a methodology to derive local bed roughness from detailed 3D point cloud data, acquired using a terrestrial laser scanner (TLS) in a 1 km long study reach of the River Feshie. Unlike hand-held scanners, a TLS can be tripod mounted and acquire data over ranges exceeding 100 m and achieve data densities well above 1000 points/m2. In this study, a Leica ScanStation was deployed to acquire a point cloud comprising over 200 million points, with total RMS errors of 2-11 mm. An experimental design using a combination of grain-size counts and TLS data was developed to test a range of algorithms designed to retrieve patch-scale roughness metrics from the 3D point cloud. Results indicate that after local detrending, the standard deviation of elevations can be successfully correlated to ground mapping and offer potential for improved parameterization of hydraulic models.
- grava mediante,
- laser terrestre