Moving Aircraft River Velocimetry (MARV): Framework and Proof‐of‐Concept on the Tanana River

Abstract

Information on velocity fields in rivers is critical for designing infrastructure, modeling contaminant transport, and assessing habitat. Although non‐contact approaches to measuring flow velocity are well established, these methods assume a stationary imaging platform. This study eliminates this constraint by introducing a framework for moving aircraft river velocimetry (MARV). The workflow takes as input images acquired from an airplane and involves orthorectification, frame overlap analysis, image enhancement, particle image velocimetry (PIV), and aggregation of the resulting velocity vectors onto a prediction grid. We also use new metrics to quantify the agreement between image‐derived and field‐measured velocity vectors in terms of both orientation and magnitude. The potential of MARV was evaluated using data from two Alaskan rivers: a large, highly turbid channel and its smaller, clearer tributary. Sediment boil vortices on the mainstem provided natural features trackable via PIV and estimated velocities corresponded closely with field measurements (R2 up to 0.911). We compared an exhaustive approach that evaluates overlap for all frame combinations to a simpler rolling window implementation and found that the more efficient algorithm did not compromise accuracy. Sensitivity analysis suggested that the method was robust to window parameterization. Comparing PIV output from different flying heights and imaging systems indicated that larger pixels led to higher accuracy and that a more advanced dual‐camera system provided superior performance. Results from the tributary were less encouraging, presumably due to a lack of trackable features in visible images. Testing across a range of rivers is needed to assess the generality of MARV.

The Toolbox for River Velocimetry using Images from Aircraft (TRiVIA)

“…As development proceeds, incorporating the following refinements and additions could enhance its utility: (1) Optimizing the core PIV algorithm, and possibly other aspects of the workflow, by taking advantage of the multiprocessing and threading capabilities of modern processors. (2) Expanding the types of data that can be provided as input to include images acquired from a moving aircraft (Legleiter et al, 2023). (3) Enabling estimation of river discharge by integrating the PIV output with bathymetric information.…”

“…The field measurements and remotely sensed data from the Tanana River used as an example application are available in Legleiter and Kinzel (2020b, 2021a, 2021b). The TRiVIA software is freely available from the repository at https://code.usgs.gov/wma/osd/trivia/, which includes a tutorial based on the Tanana River data set.…”

“…The program provides an end-to-end workflow that encompasses import, resampling, and visualization of videos or images; stabilization and geo-referencing; region of interest (ROI) definition and masking; image filtering and enhancement; PIV analysis and post-processing; and accuracy assessment and export. TRiVIA is a Windows application freely available from the US Geological Survey at https://code.usgs.gov/wma/osd/trivia/ (Legleiter, 2023), which also includes a tutorial that illustrates the workflow shown in Figure 1 using data from the Tanana River in Alaska.…”

“…The purpose of this paper is to introduce TRiVIA and provide an example of its application using an RGB (red, green, blue) video acquired from a helicopter; this video is available from Legleiter and Kinzel (2020b, 2021a, 2021b). The following sections (1) briefly describe TRiVIA's core PIV algorithm; (2) illustrate various modules accessible through the program's graphical user interface (GUI); and (3) discuss TRiVIA's limitations and potential for further enhancement.…”

A framework to facilitate development and testing of image‐based river velocimetry algorithms

“…Several factors have contributed to the ongoing proliferation of image-based river velocimetry. For example, the number of platforms from which suitable images can be acquired now encompasses bridge-or bank-mounted cameras (Muste et al2008), uncrewed aircraft systems (UAS; Duan et al, 2023;Eltner et al, 2021), helicopters (Fujita & Hino, 2003), fixed-wing aircraft (Legleiter et al, 2023), and satellites (Legleiter & Kinzel, 2021). Similarly, in addition to standard video, thermal cameras can capture the motion of water surface features expressed as subtle differences in temperature (Schweitzer & Cowen, 2021).…”