## 5 Discussion
### Best Practices for Generating DEMs in Ames for SPOT6/7
However, the coarser resolution output by the point2 dem tool has no effect on the stereo correlation, which is always performed for every overlapping pixel at the input PAN image resolution (cf. ASP manual; [25]). Rather, these different output resolutions represent different averaging of the triangulated values at every pixel. In essence, naively outputting the DEM at a coarser resolution (e.g., here 6 m, or 4\(\times\) the input resolution), has the effect of smoothing results and reducing artifacts [23], but this can also be achieved using larger CK sizes and outputting a finer DEM (e.g., here 3 m, or 2\(\times\) the input resolution). Larger CKs have been suggested by previous studies in areas of low image texture (i.e., glaciers and ice-sheets; [34; 35]), and we find quantitative evidence for this through our solar analysis (Figure 8). Further, we found that for our study area with low texture (i.e., \(\lessapprox\)10\({}^{3}\)) on many hillslopes (Figure 11E), larger CK sizes in the MGM algorithm led to smoother DEMs that better represented high curvatures in valley bottoms compared to smooth hillslopes (Figure 13F). An ASP parameter that we have not yet mentioned is the xcorr-threshold, which allows stereo correlation to proceed for the left image as reference and then again for the right image as reference, doubling processing time. Similar to previous work [23; 34], we found significant improvements from allowing both correlation directions to refine the disparity map, and this is recommended for the highest quality results. Finally, similar to previous work (e.g., [35; 59]), we found that the highest quality correlation and triangulation results can be achieved from image pairs with a larger convergence angle (e.g., AC). Utilizing neighboring pairs of tristereo imagery (e.g., AB) may improve coverage in steep canyons (Figure S4) or urban areas with tall buildings that cause occlusions, but blending these results into final DEMs is not recommended in other locations. This is in contrast to the ASP manual [25], which suggests using the pc_merge and/or dem_mosaic tools to blend results from different image pairs. We note that the nadir scene was used in our previous work [21] in an area with very steep mountains and incised gorges, but blending outside of these gorges may have reduced the final quality. This may benefit future research in mountain environments where there are limited steep bedrock gorges, since the nadir tristereo image does not need to be acquired (i.e., purchased), and just the forward and backward pointing scenes may be sufficient. In agreement with other work [59], this demonstrates that the optimal image pairs with a larger difference in viewing angle will lead to better quality elevation measurements, and stacking many optimal image pairs with good geometry (even if the images are from different dates) may lead to further improved results. We found that the overall flexibility of the ASP, including its incorporation and refinement of many stereo-correlation algorithms and their parameters, make this open-source software a suitable tool for optical DEM generation. We note that other recently presented techniques offer somewhat less flexibility and more specific applications, e.g., MicMac [14], SETSM [56; 57], and Metashape software [60]. Continued development of structure-from-motion multiview stereo (SfM-MVS) methods may lead to satellite DEMs generated from vastly different pipelines compared to traditional stereogrammetry [22]; but, SfM-MVS results for satellite stereo imagery are still nascent and of generally lower quality compared to using carefully selected image pairs for stereo correlation [35; 59; 61]. Indeed, we found that initial tests of DEM generation using Agisoft Metashape [62] led to poor results, albeit in much faster processing times and with fewer parameters to tune compared to the ASP.