## Materials and Methods
### UAV Mapping Experiment
During the whole flight, there was a moderate wind blowing from the south-west. As the UAV had to lean against the wind, the on-board irradiance sensor had an average tilt of 4.6\({}^{\circ}\) towards the sun over the whole flight. To evaluate the performance of AIRS orientation and position data, both the RTK and PPK coordinates were calculated. The RTK solution was processed using differential GNSS correction data from the FinnREF service, while the PPK was processed relative to a local GNSS ground station (uBlox NEO-MSP, Thalwil, Switzerland). To produce reference data to these GNSS positions, a photogrammetric image orientation process was performed on the RGB and hyperspectral images using the PhotoScan Pro (v1.2.5; AgiSoft LLC, St. Petersburg, Russia) software. The processing was done separately using both RTK and PPK positions as initial image orientations. The GCPs were marked manually. The position accuracy of GCPs was set to 5 mm, while for initial camera positions this was set to 1m, to ensure that the positions were mostly derived from GCPs. The RGB images and three bands of the hyperspectral datacubes as individual images were extracted and processed simultaneously in PhotoScan. The camera exterior orientation parameters (EOPs) were estimated using the \"Align\"-method with \"high\" quality. The tie point outlier removal step was performed using the automatic tools based on re-projection residuals and the standard deviations of the tie point 3D coordinates. Some outlier tie points were further removed manually. The camera geometric calibration was performed with image orientation (self-calibration). Once images were aligned, the image EOPs were exported out of PhotoScan for analysis. To evaluate the performance of AIRS irradiance data in image processing, three traditional reflectance factor conversion methods were tested against the AIRS method. Firstly, reflectance reference panels of a size of 1 m by 1 m, with nominal reflectance of 0.03, 0.1, and 0.5, were placed on-ground near the take-off position and imaged from the air at the beginning of the flight. Secondly, the irradiance spectra acquired by the ASD FieldSpec Pro spectrometer was used in conversion. Thirdly, the raw AIRS spectrometer data was used as an unstabilized irradiance sensor on-board UAV. Each irradiance determination method was used separately to convert the hyperspectral raw radiance images to reflectance factor images. With the on-board AIRS data and on-ground FieldSpec data, it was possible to detect and filter out images which were taken temporally near cloud edge events potentially having varying illumination within the image. The reflectance reference panel did not have any irradiance data available and the unstabilized onboard irradiance data had natively larger variations too great that such automated filtering was not feasible for those. Manual filtering was deemed too subjective for this study; thus, no filtering was applied to the images of these two methods. The usable images of each method were then processed in Photoscan to produce the orthomosaics. For each ground pixel on the mosaic, the source image with view angle closest to nadir was used without border blending.