## 2 Materials and Methods
### Methodology  
The aim of the current study was to examine whether the geometry of UAV acquisition plays a key role in the accuracy of derived photographic products that are subsequently used as high-precision data for landslide mapping and monitoring. A schematic illustration of the applied methodology is displayed in Figure 4.  
In more detail, UAV surveys were conducted over five study areas, presenting different characteristics (topography, land cover, etc.). Three UAV flights, consisting of: (a) nadir-only acquisitions, (b) oblique-only acquisitions, and (c) an integration of nadir and oblique acquisitions, were executed for each case study. The different UAV acquisition trajectories of nadir- and oblique-viewing campaigns over the landslide of Messarista (case study) are depicted in the Figure 5. It is worth mentioning that the collection of the oblique-viewing imagery was implemented as the UAV moved forward and backward, following line paths  
Figure 4: A flowchart showing the processing steps of the research methodology.  
Figure 3: Aluminum targets, as captured in orthophotos during UAV campaigns over the landslide of Zachlorou.  
that were perpendicular to the slope of each study area. Furthermore, photogrammetric GCPs were collected during the UAV surveys.  
The processing of the collected UAV imagery was carried out through SfM photogrammetry. The specific technique contributes to the three-dimensional reconstruction of the topography, using the basic principles of photogrammetry along with computer vision algorithms [36; 37; 38; 39]. The main advantage of this functional and low-cost method is that it allows the automatic and simultaneous determination of scene geometry, camera positions, and orientation, without requiring pre-existing known points. Thus, multiple, overlapped and shifted 2D images are transformed into 3D representations using an automatic, feature-matching algorithm.  
The photogrammetric processing of UAV imagery took place in Agisoft Metashape software. The calibration and optimization of the camera took place in accordance with Agisoft's default values, as set for the DJI Phantom 4 camera. Internal orientation parameters were estimated automatically, due to the ability of the software to recognize the model of the camera and to specify the appropriate settings.  
The high-quality option was selected for the alignment of the images, aiming at a more precise estimation of the camera positions [40]. At the same time, the processing of UAV imagery was implemented using the original image size. The quality option was closely linked to the quality of the topographic reconstruction. Moreover the, ultra-high setting was defined as the parameter during \"build dense cloud\" and \"build mesh\" procedures.  
Orthophotos and DSMs emerged from the processing of the collected UAV imagery. These products were projected into the Hellenic Geodetic Reference System 1987. Specifically, three orthophotos and three DSMs were created for each study area, corresponding to the three different acquisition geometries (i.e., nadir-viewing images, oblique-viewing images, and an integration of nadir and oblique imagery). The evaluation of the accuracy of the generated orthophotos and DSMs was based on qualitative and quantitative comparative approaches, including RMSE calculation, length comparison, and mean center estimation.