## 5 Results
### Quality Assessment of the Extracted DSMs  
In view of the results attained in Section 5.1, the sensor model finally applied to both Deimos-2 stereo pairs was the RPC1 model using 12 GCPs (GCPs (1) and GCPs (2) in Figure 1) evenly distributed over the work area. For the WV2 stereo pair, and according to [PERSON] et al. [7], the RPC0 model and the same 12 GCPs were used for the orientation phase. The completeness results obtained from the different DSMs computed in this work are presented in Table 5. From the global statistical analysis of the completeness values using the Kruskal-Wallis H test, it can be concluded that only the land cover factor turned out to be significant (\(p<0.05\)). In this sense, the land cover factor presented a partial eta-squared statistic (\(\text{n}_{\text{p}}\)\({}^{2}\)) of 70.98%, meaning that 70.98% of the completeness variance was statistically explained by this source of variation. The best completeness was achieved for bare soil, followed by plastic covered greenhouse and, finally, urban areas. As can be seen in Table 5, no significant differences (\(p<0.05\)) were found for plastic covered greenhouse areas between the three stereo pairs used. In the case of urban areas, WV2 yielded the best completeness value, presenting significant differences (\(p<0.05\)) with the second stereo pair of Deimos 2 (August 2019) but not with the first one (July 2019). Finally, and regarding bare soil land cover, we found similar results to those observed in urban areas, but only with applying a lower significance level of \(p<0.10\) (Table 5). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Land Cover** & **Stereo Pair** & **Completeness (\%)** & **Min. (\%)–Max. (\%)** \\ \hline \multirow{6}{*}{Plastic covered greenhouse} & Deimos-2 & 90.98 & 83.61–95.62 \\  & (30 July 2019) & & \\ \cline{1-1}  & Deimos-2 & 91.88 & 89.31–94.11 \\ \cline{1-1}  & (5 August 2019) & & \\ \cline{1-1}  & WV2 & 92.00 & 89.10–93.75 \\ \cline{1-1}  & (5 July 2015) & & \\ \hline \multirow{6}{*}{Urban} & Deimos-2 & \multirow{2}{*}{79.14 \({}^{\text{a,b}}\)} & \multirow{2}{*}{76.50–80.76} \\  & (30 July 2019) & & \\ \cline{1-1}  & Deimos-2 & & \\ \cline{1-1}  & (5 August 2019) & & \\ \cline{1-1}  & WV2 & 99.76 \({}^{\text{b,*}}\) & \\ \cline{1-1}  & (5 July 2015) & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Mean and range of completeness values (maximum and minimum) attained from the three samples per land cover. For each land cover, different superscript letters between data along the completeness column indicate significant differences at a significance level \(p<0.05\) (\({}^{\circ}\) indicates differences at a significance level \(p<0.10\)). In Figures 3-5, we can visually compare the DSMs derived from the two Deimos-2 and WV2 stereo pairs corresponding to plastic covered greenhouse, urban, and bare soil areas, respectively. In each figure, the three subareas per land cover are depicted, together with their corresponding reference LiDAR. Overall, these figures show that DSM completeness was quite similar for Deimos-2 and WV2 in plastic covered greenhouse areas (Figure 3), being slightly better in the case of WV2 in bare soil (Figure 5) and, especially, in urban areas (Figure 4). It can also be observed that Deimos-2's DSMs were rougher in appearance than WV2's DSMs (Figures 3 and 5). Table 6 shows the vertical accuracy results, in terms of mean, SD, RMSE\({}_{\rm Z}\), LE95 and NMAD, attained for the different DSMs produced in this work. The influence of two factors such as land cover and stereo pair on the descriptive statistics of DSM vertical accuracy is statistically analysed. From a global statistical analysis of the RMSE\({}_{\rm Z}\) values using the Kruskal-Wallis H test, it can be concluded that the land cover factor turned out to be significant (\(p<0.05\)), while the stereo pair source of variation only showed significant differences at a significance level of \(p<0.10\).