## 4 Methods  
### Sensor Orientation  
The four Deimos-2 L1B images of the two stereo pairs were processed individually in the context of the sensor orientation phase. The photogrammetric module of PCI Geomatica v. 2018 (PCI Geomatics, Richmond Hill, Ontario, Canada) called OrthoEngine(r) was the software used at this stage. Three strategies were studied: (i) direct geopositioning, (ii) all GPs are considered GCPs, and (iii) operational approach by only including a few GCPs. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Product** & \multicolumn{2}{c}{**Deimos-2 Stereo Pair**} & \multicolumn{2}{c}{**Deimos-2 Stereo Pair**} \\ \hline Acquisition date & 30 July 2019 & 30 July 2019 & 5 August 2019 & 5 August 2019 \\ Image Code & 1\_1 & 1\_2 & 2\_1 & 2\_2 \\ Acquisition time (GTM) & 11:01:58 & 11:03:43 & 11:00:11 & 11:01:56 \\ Cloud cover & 0\% & 0\% & 0\% & 0\% \\ Sun elevation & 65.43\({}^{\circ}\) & 65.66\({}^{\circ}\) & 64.06\({}^{\circ}\) & 64.27\({}^{\circ}\) \\ Sun azimuth & 132.90\({}^{\circ}\) & 133.71\({}^{\circ}\) & 134.43\({}^{\circ}\) & 135.23\({}^{\circ}\) \\ Collection elevation & 54.75\({}^{\circ}\) & 53.54\({}^{\circ}\) & 55.67\({}^{\circ}\) & 54.69\({}^{\circ}\) \\ Collection azimuth & 192.86\({}^{\circ}\) & 324.82\({}^{\circ}\) & 187.37\({}^{\circ}\) & 329.46\({}^{\circ}\) \\ Product pixel size & 1 m & 1 m & 1 m & 1 m \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Characteristics of panchromatic (PAN) images from Deimos-2 acquired at the study site. * Direct geopositioning was performed without using GCPs, thus taking the 102 GPs as ICPs in the corresponding four independent projects created in OrthoEngine. In this way, the images were orientated only using the supplied RPCs. Geometric accuracies were computed from the residuals attained at the 102 ICPs and presented as mean error (bias), standard deviation (SD) and RMSE, computed both through \(X\) and \(Y\) axes, and as planimetric values (2D). * The all GPs as GCPs strategy meant using all 102 GPs as GCPs (i.e., without ICPs). Transformations of zero (RPC0), first (RPC1) and second (RPC2) order polynomial adjustments were applied. Geometric accuracies were calculated using the residuals from those 102 GCPs. * Regarding the operational approach with a few GCPs, three sets of GCPs were chosen to carry out the georeferencing: 6 GCPs (set GCP 1 in Figure 1), 12 GCPs (set GCP 1 plus set 2 in Figure 1), and 18 GCPs (set GCP 1 plus set 2 plus set 3 in Figure 1). Each of these variations of the number of GCPs were tested with the three sensor models mentioned above (i.e., RPC0, RPC1 and RPC2). In total, 36 RMSE\({}_{\text{2D}}\) values were computed (i.e., four single Deimos-2 images \(\times\) three sets of GCPs (6, 12 and 18) \(\times\) three sensor models (RPC0, RPC1 and RPC2)). In each case, the remaining GPs were considered ICPs (i.e., 96 ICPs when using 6 GCPs, 90 ICPs when using 12 GCPs, and 84 ICPs when using 18 GCPs) to calculate the corresponding geometric accuracies (bias, SD and RMSE). All the residual populations through \(X\) and \(Y\) axes were tested for normality. The Kolmogorov-Smirnov test was used as an indicator of goodness of fit to a standard normal distribution. Furthermore, no outliers were identified in the residual populations by applying the widely known three-sigma rule [41]. In order to study the influence of the two studied factors (sensor model (i.e., RPC0, RPC1, RPC2) and number of GCPs (no. GCPs)), together with their cross-interactions during the bundle adjustment phase regarding sensor orientation accuracy, an analysis of variance (ANOVA) test was carried out. The observed variable for the designed factorial model with four repetitions [42] was the planimetric RMSE\({}_{\text{2D}}\) computed at ICPs. Regarding this point, it is worth noting that, given such a high number of ICPs, the estimated error (reliability) for RMSE\({}_{\text{2D}}\) calculation could reach values lower than 10% [43].