## 6 Discussion
### Quality Assessment of the Extracted DSMs  
Regarding completeness, an interesting comparison can be made between Qin's RSP software [23] and OrthoEngine v. 2018 in the case of the WV2 stereo pair. The completeness values, in the same subareas and using the same methodology as in the current work, were reported for the WV2 data by [PERSON] et al. [19]. Both software packages used a SGM matching algorithm, but slightly better completeness values were provided by RSP in each land cover. The completeness values attained using OrthoEngine in this work (Table 5) were 92.00%, 86.04% and 99.76% for plastic covered greenhouse, urban, and bare soil, respectively, while values of 97.92% (greenhouse), 94.83% (urban) and 99.97% (bare soil) were reported by [PERSON] et al. [19] using RSP. These results are consistent with those reported by [PERSON] et al. [21]. Moreover, the SGM approach used in this work achieved much better completeness values than other algorithms such as FORSAT [21] or the algorithm included in OrthEngine v. 2013 (it is also available in OrthoEngine v. 2018) based on the cross-correlation area-based matching procedure [19].  
The vertical accuracy results of the DMS produced from WV2 data were always better than those computed on the DSMs derived from Deimos-2 imagery for all the three land covers tested. This was mainly because of the higher spatial resolution of PAN WV2 imagery (0.5 m GSD) as compared to Deimos-2 (1 m GSD). If the RMSE\({}_{\rm Z}\) values for plastic covered greenhouse areas are presented in relation to their corresponding sensor ground sample distance (i.e., RMSE\({}_{\rm Z}\)/sensor GSD), vertical errors of 1.94, 1.76 and 1.48 times the GSD are attained for WV2, Deimos-2 July, and Deimos-2 August, respectively. If the same exercise is applied to bare soil land cover, values of 1.43 for WV2, 1.32 for Deimos-2 July, and 1.41 for Deimos-2 August are obtained. Finally, RMSE\({}_{\rm Z}\) values of 4.41 times the GSD for WV2, 3.55 for Deimos-2 July, and 3.96 for Deimos-2 August are achieved in urban areas. All these values are in accordance with what is reported in the literature for those different land covers [19].  
The use of the robust scale estimator NMAD yielded clearer significant differences in the statistical analysis. According to [PERSON] and [PERSON] [44], the removal of outliers by a threshold (e.g., three-sigma rule) could not eliminate all of the outliers. In this sense, these kind of robust accuracy measures can help to improve the understanding of DEM errors. Therefore, they should be integrated in DSM validation reports [47]. In our work, all the SD values were quite a lot higher than NMAD even though a small percentage of outliers ranging from 1% to 3% was detected.  
Finally, if we compare the SD values computed on the DSM produced from the WV2 stereo pair by using OrthoEngine (Table 3) and RSP software (see [PERSON] et al. [19]), worse vertical accuracies are always attained from RSP software. Summing up, 0.86 m for OrthoEngine against 1.10 m for RSP in plastic covered greenhouse areas, 0.21 m for OrthoEngine against 0.28 m for RSP in bare soil areas, and 2.16 m for OrthoEngine against 2.92 m for RSP in urban areas. This trend can also be seen in other land covers such as impervious objects, industrial buildings, residential buildings, and roads [21].