Developing a Guideline of Unmanned Aerial Vehicle's Acquisition Geometry for Landslide Mapping and Monitoring  
[PERSON]  
1 Department of Geology, University of Patras, 265 04 Patras, Greece; [EMAIL_ADDRESS] (A.K. ); [EMAIL_ADDRESS] (I.K.K.) Footnote 1: [[https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci)]([https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci))  
[PERSON]  
1 Department of Geology, University of Patras, 265 04 Patras, Greece; [EMAIL_ADDRESS] (A.K. ); [EMAIL_ADDRESS] (I.K.K.) Footnote 2: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
[PERSON]  
1 Department of Geology, University of Patras, 265 04 Patras, Greece; [EMAIL_ADDRESS] (A.K. ); [EMAIL_ADDRESS] (I.K.K.) Footnote 3: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
Footnote 4: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
Footnote 5: [[https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci)]([https://www.mdpi.com/journals/applsci](https://www.mdpi.com/journals/applsci))  
error (RMSE) values extracted from the respective DSMs [11; 12; 13]. The results demonstrated a clear influence of the number of GCPs on the accuracy of UAV photogrammetry. Although the selection of about 20 GCPs (defined according to the study area) managed to reduce the RSME by 50%, it was proved that a higher number of GCPs slightly improved the accuracy. Moreover, other studies dealt with analyzing the distribution of GCPs within the study area and the effect of such distribution on the accuracy of the derived DSMs, which decreases as the distance to the nearest GCP increases [14; 15]. In general, the accuracy of photogrammetric products increases asymptotically as the number of GCPs increase, until an optimal GCP density is reached. The collection of GCPs is a time-consuming task. Thus, the development of UAVs with onboard Global Navigation Satellite System Real Time Kinematic (GNSS RTK) positioning--in which the georeferencing of the images does not require GCPs--constitutes a promising solution [16; 17]. The main disadvantage of the specific approach is the presence of systematic elevation errors, which emerge from the incorrect determination of the interior orientation parameters estimated during bundle adjustment [18]. A recent study proposed that a combination of two UAV flights at the same altitude, consisting of nadir and oblique imagery, was able to reduce the systematic elevation error to less than 0.03 m [19]. Other approaches focused on evaluating the effect of different scenarios, consisting of multi-view camera combinations, on the accuracy of UAV photogrammetry. Specifically, the combination of non-metric oblique and vertical views, along with an appropriate collection of GCPs, has significantly enhanced the accuracy of the photogrammetric procedure, extracting DSMs comparable to those derived by Light Detection and Ranging (LiDAR) [20]. Indeed, this integration of nadir and oblique imagery has proven its effectiveness in numerous studies, including the reconstruction of the surfaces and the determination of the main geometries in a quarry environment, the geomorphological mapping of landslides, and geotechnical/ hazard mapping [21; 22; 23]. In addition, it has been proven that the reconstruction of a topographically complex terrain requires the synergy of oblique and facade images to complement nadir views [24]. This synergistic use significantly improved the geometric accuracy of topographic reconstruction, by approximately 35%.