The UAV Research Center (URC) at the Faculty of Bioscience engineering – est. 2019 – focuses on sensing technologies with drones through interdisciplinary collaboration. It undertakes research on the automation of drone flights, remote sensing using drones and data processing, with particular interest in precision agriculture and industrial inspection applications.
One of their recent projects deals with how to optimise the processing of thermal imagery taken with drones and influenced by changing meteorological conditions during the flight. A paper on this research is available at https://doi.org/10.3390/rs9050476
Figure: The effect of initial estimate of thermal image position on the image alignment of the agricultural dataset. The sparse point cloud is shown. (a) No initial image position; (b) GPS-based initial image position; (c) RGB image-based initial image position.
Top: Top view (nadir), middle and bottom: side views. The yellow markers indicate gaps in the data alignment, the red markers indicate errors in the image alignment. In the top views, dashed red lines indicate the position of the misaligned areas shown in the middle and bottom views. (source: https://doi.org/10.3390/rs9050476)