Adaptive thermal image velocimetry of spatial wind movement on landscapes using near-target infrared cameras

Abstract

Thermal image velocimetry (TIV) is a near-target remote sensing technique for estimating two-dimensional (2D) near-surface wind velocity based on spatio-temporal displacement of fluctuations in surface brightness temperature captured by an infrared camera. The addition of an automated parameterization and the combination of ensemble TIV results into one output made the method more suitable to changing meteorological conditions and less sensitive to noise stemming from the airborne sensor platform. Three field campaigns were carried out to evaluate the algorithm over turf, dry grass, and wheat stubble. The derived velocities were validated with independently acquired observations from fine-wire thermocouples and sonic anemometers. It was found that the TIV technique correctly derives atmospheric flow patterns close to the ground. Moreover, the modified method resolves wind speed statistics close to the surface at a higher resolution than the traditional measurement methods. Adaptive thermal image velocimetry (A-TIV) is capable of providing contactless spatial information about near-surface atmospheric motion and can help to be a useful tool in researching turbulent transport processes close to the ground.