###### Abstract
**(2)** The \"reflectance reference target\"--methods, where object(s) with known reflectance factor present in the image, are used for image calibration. For the highest accuracy, the target's BRF should also be known to correctly take the view and illumination angle into account [11; 12]. These targets can be either purpose-prepared reference panels e.g., in references [13; 14; 15; 16] or other targets present in images [17; 18; 19], for which the reflectance factor has been measured. The empirical line method is a variation of this method, where more than one reference target is used [20]. If done properly, and imaging is done in perfectly stable illumination conditions, this can be considered one of the most accurate ways to perform the reflectance factor conversion, as many of the errors in the camera calibration and atmospheric transmission are canceled out in the mathematics. The downside of these methods is that they are not capable of handling varying illumination conditions during the flight campaign, since they work only locally near the reference panels, and thus also require the presence of a ground team to place targets in the area of interest. This is typically not a big problem in the visual line of sight (VLOS) UAV flights but makes these methods less practical for satellite, airplane, and beyond visual line of sight (BVLOS) UAV operations. This method is also compromised in areas such as forests, where it is not easy to avoid placing the targets far from the reflections and shadows from the objects. **(3)** The \"on-ground irradiance sensor\"--method uses a device on the ground to measure the irradiance. This method has been used e.g., in reference [21]. Most commonly the irradiance measurements are synchronized to the camera exposures by GPS time tags in a post-processing phase. Similar to the reflectance reference target method, this method can be very accurate, but again it works only locally, requires the presence of a ground team, and has challenges in e.g., forested areas. **(4)** The \"on-board irradiance sensor\"--method takes a similar sensor as previously but places it onboard a UAV. This method has been used by the authors in references [3; 22; 23]. In a way, this is the ideal method as it can provide the irradiance measured in the camera location in real time. As the irradiance reading is highly tilt-sensitive, in practice on UAVs, the sensor must be placed on a stabilized gimbal or be otherwise corrected for effects of tilt. Radiometric block adjustment is an image-based approach to model and compensates for various radiometric disturbances in image DNs to calculate reflectance images. A model between the object reflectance and image DNs is selected and its parameters are solved using optimization techniques. The model implemented in the RadBA software of the FGI [6] includes BRF parameters, a relative multiplicative parameter for irradiance differences, and a linear model for transforming image DNs to reflectance factors. The model parameters are determined on the basis of radiometric tie points, and optional \"on-ground\" [24] or \"on-board\" [25] irradiance observations and reflectance reference observations. The outputs of the process are the parameters of the radiometric model, which are used in the following processes to produce radiometrically corrected image products, such as reflectance mosaics, reflectance point clouds, or reflectance observations of objects of interest. Several studies in different environments and illumination conditions have shown that the methods have significantly compensated for radiometric disturbances in images and improved subsequent interpretation processes [24; 25; 26; 27; 28]. As the irradiance is a spectral quantity, and its spectral shape varies in natural illumination, the irradiance should be known on the same spectral bands as the camera uses. Datawise, a spectrometer, is the most versatile instrument for irradiance measurement as it allows mathematical resampling of data to any virtual spectral band within its spectral range and resolution.