# Estimation of the Block Adjustment Error in UAV Photogrammetric Flights in Flat Areas
## 5 Conclusions  
This article has analysed the accuracy that can be obtained on flat terrains from UAV-DAP. In addition to the classic aerial flight planning setup with near-parallel imaging directions in forwarding strips, three additional scenarios are analysed using only four GCPs, one at each end, plus one additional GCP in the centre (see Supplementary Material). The research conducted on four blocks confirms that the error achieved in the adjustment of the photogrammetric block is heavily dependent on flight planning. In this case, it is confirmed that the best results are obtained by adding lower flying heights cross strips at both ends, an aspect that is not included in the current flight planning programs (for example, DroneDeploy, PIX4D).  
Reinforcing the conventional flights with lower cross strips achieves greater accuracy in the UAV-DAP. A single cross strip at each end, with the GCPs located at the corners of the block, is sufficient to improve the accuracy. When three flight strips are used, together with perimeter strips, as in Scenario D, the error increases significantly by 28.9%, considering the ChPs. Therefore, scenarios with extremely short baselengths, with multiple cross strips, are highly discouraged, even with lower flying heights.  
If Scenario C is applied, instead of the one proposed by the DroneDeploy software [39] (Scenario B), the precision increases by 9.2%, thus guaranteeing better results for the products obtained, namely the DTMs and orthomosaics, with four GCPs and with lower battery consumption on flat terrains. The classic implementation of flight planning, Solution A, is the least advisable, as the RMSE in the ChPs is up to 23% larger than in Scenario C.  
Future analyses will study the effect of including oblique flight strips (equivalent to convergent imagery in terrestrial photogrammetry), scenarios with mountainous terrains or larger areas, and different numbers of GCPs under other flying options (e.g., double grid acquisition for urban areas.  
**Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs14122877/s1](https://www.mdpi.com/article/10.3390/rs14122877/s1)]([https://www.mdpi.com/article/10.3390/rs14122877/s1](https://www.mdpi.com/article/10.3390/rs14122877/s1)), Figure S1: Distribution of the mean RMSE of the GCPs and ChPs of the four blocks for the scenarios studied, with four GCPs at the corners and one in the middle; Table S1: Mean RMSE of the GCP and ChP for the four Block 1 scenarios; Table S2: Mean RMSE of the GCP and ChP for the four Block 2 scenarios; Table S3: Mean RMSE of the GCP and ChP for the four Block 3 scenarios; Table S4: Mean RMSE of the GCP and ChP for the four Block 4 scenarios.  
**Author Contributions:** Conceptualisation, J.L.L.; Data acquisition, J.P.C.-R., A.N.A.-V., J.F.P. and J.L.L.; Formal analysis, J.F.; Funding acquisition, J.L.L. and J.F.; Investigation, A.N.A.-V., J.P.C.-R. and J.L.L.; Methodology, J.L.L.; Software, A.N.A.-V., J.F.P. and J.P.C.-R.; Supervision, J.L.L. and J.F.; Validation, J.F.P.; Writing--original draft, A.N.A.-V.; Writing--review & editing, J.L.L., J.F.P., J.P.C.-R. and J.F. All authors have read and agreed to the published version of the manuscript.  
**Funding:** The work has been partly supported by Spanish Agencia Estatal de Investigacion (10.13039/ 501100011033) grant RTI2018-093874-B-I00 (DEEP-MAPS). This work represents a contribution to CSIC Thematic Interdisciplinary Platform PTI TELEDETECT.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.