Articles | Volume 15, issue 19
https://doi.org/10.5194/amt-15-5681-2022
https://doi.org/10.5194/amt-15-5681-2022
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

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Cited articles

Adrian, R., Meinhart, C., and Tomkins, C.: Vortex organization in the outer region of the turbulent boundary layer, J. Fluid Mech., 422, 1–54, https://doi.org/10.1017/S0022112000001580, 2000. a
Alekseychik, P., Katul, G., Korpela, I., and Launiainen, S.: Eddies in motion: visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videos, Atmos. Meas. Tech., 14, 3501–3521, https://doi.org/10.5194/amt-14-3501-2021, 2021. a
Barthlott, C., Drobinski, P., Fesquet, C., Dubos, T., and Pietras, C.: Long-term study of coherent structures in the atmospheric surface layer, Bound.-Lay. Meteorol., 125, 1–24, https://doi.org/10.1007/s10546-007-9190-9, 2007. a
Bastiaanssen, W., Menenti, M., Feddes, R., and Holtslag, A.: A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation, J. Hydrol., 212–213, 198–212, https://doi.org/10.1016/s0022-1694(98)00253-4, 1998. a
Blender Online Community: Blender – a 3D modelling and rendering package, Blender Foundation, Blender Institute, Amsterdam, http://www.blender.org (last access: 24 June 2022), 2019. a
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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.