## 5 Conclusions  
Even though producers and developers have made great efforts to enhance them, radiometric corrections leave significant radiometric distortions in orthomosaics obtained by Sequoia and Pix4D systems, which can result in biased absolute values. This study shows that relevant differences are found depending on flight geometry and block processing choices, with differences that can reach 20% of pixel values for single reflectance bands or VIs, thus reducing the effective use in PA. Moreover, available radiometric corrections do not guarantee uniform accuracy and consistency of results, and this can cause difficulties in comparing surveys carried on out different lightening conditions. Careful planning of the survey, together with proper choices of image processing, can enhance the results. Very high image overlap yields uniformity over a single block, and edge distortions can be reduced by surveying a wider area that includes the study area. Nevertheless, for large surveys that imply the acquisition and processing of separated sub-blocks, the merge option suggested by Pix4D is effective in reducing radiometric inconsistencies in adjacent areas. This fact, together with the high correlation found with S2 products, proves that Sequoia is suitable for agronomic purposes, but great attention must be paid to the planning of the survey and to the data processing. Therefore, it is necessary to increase the awareness in the use of sensors and semi-automatic data processing to deeply understand the strengths and weaknesses of UAV usage for PA. In this study, the choice to process the dataset following the proposed scenarios (Section 2.3) instead of a standard workflow was driven by the apparently impossibility of attributing the corresponding calibration set of images to each block. The new Sequoia+ sensor should bypass this issue because no calibration target is needed; imagery processing exploits a new fully automatic calibration pipeline in Pix4D. The authors do not have experience with this new camera release, however, they consider the proposed processing method an interesting and simple way to assess the performance of new sensors. Finally, the applicability of the proposed method can be extended. In this paper, geometric and radiometric consistency was evaluated comparing results obtained from two almost contemporaneous flights, processed following a single-block approach. The same method can be used to evaluate consistency between two or more blocks acquired days or month apart; in other words, the method can be used to assess time-series. The following are available online at [[http://www.mdpi.com/2076-3417/9/24/5314/s1](http://www.mdpi.com/2076-3417/9/24/5314/s1)]([http://www.mdpi.com/2076-3417/9/24/5314/s1](http://www.mdpi.com/2076-3417/9/24/5314/s1)). Figure S1: Spatial distribution of differences in the overlapping area for scenario Ig/lr with respect to block 3: red (**a**), red-edge (**b**), GNDVI (**c**), NDRE (**d**), NDVIire (**e**), NGRDI (**f**). Figure S2: Spatial distribution of differences in the overlapping area for scenario Ig/lr with respect to block 4: red (**a**), red-edge (**b**), GNDVI (**c**), NDRE (**d**), NDVIr (**e**), NGRDI (**f**). Figure S3: Spatial distribution of differences in the overlapping area. Scenario Ig/lr: green (**a**), red (**b**), red-edge (**c**), NIR (**d**), NDVI (**e**), GNDVI (**f**), NDRE (**g**), NDVIire (**h**), NGRDI (**i**). **Author Contributions:** Conceptualization, M.F. and V.C. ; formal analysis, M.F., G.R., G.S., and V.C. ; methodology, G.S. and V.C. ; project administration, M.F. ; software, M.F. and G.R. ; supervision, G.S. and V.C. ; visualization, M.F. and G.R. ; writing--original draft, M.F., G.R., G.S., and V.C. ; writing--review and editing, M.F., G.R., G.S., and V.C. **Acknowledgments:** [PERSON] is a technician of the Laboratory of Geomatics of the University of Pavia. He is the pilot of the UAV, plans the flight missions, carries out maintenance, and performs sensor integration; he is gratefully acknowledged here.