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

Schumacher, Benjamin; Katurji, Marwan; Zhang, Jiawei; Zawar-Reza, Peyman; Adams, Benjamin; Zeeman, Matthias

doi:https://doi.org/10.5194/amt-15-5681-2022

Articles | Volume 15, issue 19

https://doi.org/10.5194/amt-15-5681-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-15-5681-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 19

Research article

|

12 Oct 2022

Research article |

| 12 Oct 2022

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

Benjamin Schumacher, Marwan Katurji, Jiawei Zhang, Peyman Zawar-Reza, Benjamin Adams, and Matthias Zeeman

Data sets

Time seqUential theRmal inFrared – Turbulence campaign 1 – TURF-T1 Experiment data Benjamin Schumacher and Marwan Katurji https://doi.org/10.5281/zenodo.6961047

Model code and software

Adaptive Thermal Image Velocimetry Benjamin Schumacher https://doi.org/10.5281/ZENODO.4741550

Short summary

This investigation presents adaptive thermal image velocimetry (A-TIV), a newly developed algorithm to spatially measure near-surface atmospheric velocities using an infrared camera mounted on uncrewed aerial vehicles. A validation and accuracy assessment of the retrieved velocity fields shows the successful application of the algorithm over short-cut grass and turf surfaces in dry conditions. This provides new opportunities for atmospheric scientists to study surface–atmosphere interactions.