Assessment of drone-based surface flow observations

Abstract

Remote surface flow observations are crucial for improving the comprehension of hydrological phenomena. A recent advancement in remote hydrological measurements involves the use of drones for generating surface flow-velocity field maps through large-scale particle image velocimetry (LSPIV). In this work, we perform a comparative analysis of drone-based LSPIV with fixed implementations. Quantitative indices are introduced to test the efficiency of the techniques with regards to measurement accuracy, sensitivity to the transit of tracers, and platform mobility. Experimental findings support drone-based observations in outdoor settings. Specifically, measurements from the aerial platform are more sensitive to the transit of tracers and closer to benchmark values than traditional LSPIV implementations. Future work should aim at improving the stability of the aerial platform and mitigating the effects of tracer scarcity.