부산대학교 도서관

An automatic workflow to measure surface flow velocities in rivers is introduced, including a Python tool. The method is based on particle-tracking velocimetry (PTV) and comprises an automatic definition of the search area for particles to track. Tracking is performed in the original images. Only the final tracks are geo-referenced, intersecting the image observations with water surface in object space. Detected particles and corresponding feature tracks are filtered considering particle and flow characteristics to mitigate the impact of sun glare and outliers. The method can be applied to different perspectives, including terrestrial and aerial (i.e. unmanned-aerial-vehicle; UAV) imagery. To account for camera movements images can be co-registered in an automatic approach. In addition to velocity estimates, discharge is calculated using the surface velocities and wetted cross section derived from surface models computed with structure-from-motion (SfM) and multi-media photogrammetry. The workflow is tested at two river reaches (paved and natural) in Germany. Reference data are provided by acoustic Doppler current profiler (ADCP) measurements. At the paved river reach, the highest deviations of flow velocity and discharge reach 4 % and 5 %, respectively. At the natural river highest deviations are larger (up to 31 %) due to the irregular cross-section shapes hindering the accurate contrasting of ADCP- and image-based results. The provided tool enables the measurement of surface flow velocities independently of the perspective from which images are acquired. With the contactless measurement, spatially distributed velocity fields can be estimated and river discharge in previously ungauged and unmeasured regions can be calculated, solely requiring some scaling information.