资源环境科技发展态势分析平台

This paper describes a novel velocimetry method we call infrared quantitative image ve1ocimetry (IR-QIV), that uses infrared (IR) images of thermal patterns advecting on water surfaces to calculate time-resolved, instantaneous, two-dimensional surface velocity fields. The method works day or night, and under most weather conditions, by tracking subtle thermal patterns on the water surface itself, which are present under most environmental conditions. No particle ’seeding’, external light sources, or contact with the water are required. A form of remote sensing, IR-QIV has significant advantages over visible-light surface velocimetry methods such as particle image velocimetry (PIV). IR-QIV allows calculation of instantaneous velocity at high spatial (centimeter scale) and temporal (1 Hz) resolutions over large areas (thousands of square meters), allowing metrics of turbulence to be calculated. Results from field measurements are presented, showing excellent agreement with nearby acoustic velocity measurements. We discuss best practices for IR image acquisition and processing based on our experience developing and working with IR-QIV. Additionally, we discuss uncertainty analysis in velocimetry techniques using images collected at oblique viewing angles and pattern tracking in images containing gradients of intensity rather than discrete particles, as well as the deleterious effects of, and post-processing ways to remove, camera fixed pattern noise, considerations relevant to all types of image-based velocimetry. This approach can improve measurements from both fixed and mobile platforms such as unoccupied aerial systems(UASs).