AUTHOR=Schweitzer Seth A. , Cowen Edwin A. 

TITLE=A Method for Analysis of Spatial Uncertainty in Image Based Surface Velocimetry

JOURNAL=Frontiers in Water

VOLUME=Volume 4 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2022.744278

DOI=10.3389/frwa.2022.744278

ISSN=2624-9375

ABSTRACT=The use of image-based velocimetry methods for field-scale measurements of river flow and
discharge has become increasingly widespread in recent years. These methods are
able to measure over large areas with high spatial and temporal resolution,
without requiring contact with the water. However, there is a lack of tools to
understand the spatial uncertainty in these methods and, particularly, its
sensitivity to parameters that can be controlled. We present a tool specifically
developed to assess spatial uncertainty in remotely sensed images used in
surface velocimetry techniques, and results from measurements that illustrate
the tool’s capabilities. The software tool is freely available
online. Uncertainty exists in the coordinate transformation between pixel array
coordinates (2D) and physical coordinates (3D) because of the uncertainty of
each input to the transformation, and since the transformation itself is
calculated in a least-squares sense from an overdetermined system of
equations. We perform a Monte Carlo simulation, perturbing the inputs to the
algorithm used to find the coordinate transformation, and observe the effect on
transformations between pixel- and physical- coordinates. This perturbation is
performed independently a large number of times with values selected from the
input parameter space, creating a set of inputs which are used to calculate a
coordinate transformation, and predict the physical coordinates of each pixel in
the image. We analyze the variance of the physical position corresponding to
each pixel location across the set of perturbed transformations, and quantify
the sensitivity of the transformation to changes in each of the inputs. We also
investigate the impact on uncertainty of ground control point (GCP) location and
number, and quantify spatial change in uncertainty, which is the key parameter
for calculating uncertainty in velocity measurements. This tool may be used to
plan field deployments, allowing the user to optimize the number and
distribution of GCPs, the accuracy with which their position must be determined,
and the camera placement required to achieve a target level of spatial
uncertainty. It can also be used to estimate the uncertainty in image-based
velocimetry measurements, including how this uncertainty varies over space
within the field of view.