## 5 Discussion and Best Practice
### Radiometric Processing
In this case, the radiometric block adjustment can be beneficial for carrying the calibration obtained from panels placed in an open area to the area of interest, as long as the datasets are connected and preferably using an irradiance sensor on-board the UAV [72; 74]. Radiometric block adjustment has been applied in studies with different settings to produce uniform image mosaics [163; 177; 178; 179; 180; 201]. Principally, the method can compensate for illumination changes during the flight campaign based on the information contained in the images. Thus, no further equipment is needed on-board the UAV for the irradiance measurement, but the irradiance recordings can also be integrated to the same adjustment process. In several studies, the method has provided the best uniformity over the entire image dataset when compared with approaches based on ground irradiance spectra measurement and on-board irradiance measurement [44; 201]. In [PERSON] et al. [44] and [PERSON] et al. [202], datasets were captured in illumination conditions varying from cloudy to sunny. The performances of approaches based on the irradiance radiometer on-board the UAV, irradiance spectrometer on the ground, and the radiometric block adjustment were compared, and the radiometric block adjustment provided the best results. Similar conclusions were drawn by [PERSON] et al. [201]. The radiometric block adjustment also provides the uniform mosaics of a dataset with different flights with varying solar azimuth and elevation [163]. Although the radiometric block adjustment can compensate for illumination fluctuations, it is important to note that the radiometric resolution might be decreased when the sensor is underexposed, and thus, differences in reflectance may not be sufficiently resolved for certain analysis [43]. The BRDF correction has mostly been carried out by means of empirical modeling. However, different surfaces (e.g., vegetation types) have different anisotropic behaviors, which makes empirical modeling challenging. With multiple overlapping images provided by 2D imagers, it is now possible to retrieve the BRDF of different surfaces and use it to normalize the data. Additionally, incorporating structural information is seen as a way forward [166]. As noted by [PERSON] et al. [42; 43], the combination of 3D and spectral information derived by 2D imagers is potentially suited for this purpose. In addition, the anisotropy can also be used as a source of information [71; 187]. New radiometric correction tools have been implemented in software packages for UAV image data processing. For example, Pix4D and Agisoft Photoscan offer options for radiometric correction, including sensor calibration-related corrections, irradiance-related correction utilizing irradiance information stored in the image EXIF-file, and sun direction-related correction for some cameras. Moreover, there is the option for radiometric calibration using reflectance panels. Additionally, some cameras, such as the Parrot Sequoia, have an integrated irradiance sensor and GNSS receiver. These are much-needed developments, since they ease the use of spectral sensors and help exploit the potential of UAVs to fly below the clouds.