## 5 Discussion
### Effect of Snow Surface Type, Light Conditions, and Image Quality
We can treat the minimal set-up as the \"worst-case\" scenario from a SfM and available equipment perspective. With the proposed image pre-processing, the set-up was nevertheless able to provide results in overcast conditions and/or over featureless snow. Such set-ups are extremely low-cost, lightweight, and easy to use. They are also capable of acquiring images in a dynamic manner characteristic of small action cameras. These are very useful assets for small surveys in remote Arctic areas where carrying volume, weight, and overall logistics are constraints. In addition, their low weight reduces regulation concerns (Appendix A). However, their inferior sensor size and fore-optics are limiting, requiring a lower altitude flight to achieve the same resolution as the advanced set-ups, and thus are not suited for mapping larger areas. They also involve a higher degree of digital noise, which in certain circumstances affects the fine-scale quality of the reconstructions and the application of the image pre-processing workflow (Appendix C). The advanced set-up is capable of flying at higher altitudes and mapping larger areas with improved cameras that provide better mapping outcomes through the photogrammetric formulas (Appendix B). However, one disadvantage is that the advanced set-up camera parameters need to be manually set accordingly to the survey circumstances (Appendix B). They are also considerably heavier, have reduced flight time, are more challenging to operate, and are subject to more regulations. The effect of the image pre-processing workflow was not as critical to the advanced set-up as for the minimal set-up (Appendix C). However, the extra matched points have an impact on the resolution of the final SDEM produced. The number of matching points is directly linked to point cloud densities and thus affects the spatial resolution of the DEMs and consequently the estimated snow depth. The spatial resolution might affect the uncertainty of the volume estimations, especially for complex underlying topographies where the snow depth can significantly vary at the micro-scale level. The spatial resolution results are even more important in a snow-sampling context, as observed in some other studies [19; 42]. To achieve high-quality reconstruction quality, it is important that the UAS set-up (image quality) and flying parameters are optimized for the required areal coverage, the snow surface type and light conditions. In addition, the scale of features of interest that assists the surface reconstruction (e.g., sastrugi, ripples, and relief) should be higher than the expected digital noise. Otherwise, it will decrease the number of proper matches and produce noisy surfaces. As shown in the image pre-processing results (Appendix C), it is important to find a balance between the pre-processing enhancement intensity and Photoscan's reconstruction quality, so that the effect of noise is minimized compared to the scale of the matched features. Future work is needed to investigate the further advantages of using RAW imagery by testing different sharpening and content enhancement approaches or the use of infrared photography to enhance snow features, as explored in other studies [26; 43]. Although various surveying conditions were investigated in this study, extreme cases such as long-lasting polar nights experienced in higher-latitude Arctic locations might impede this methodology due to a lack of luminance. The period after the snow peak season is of great interest,since its characterized by increased snow depth variability that continues through the subsequent melting season [11]. Nevertheless, low luminance winter measurements are increasingly required [1] and should be considered for future work. It is important to note that these conceptual tests were performed over relatively small areas (1386 to 38,410 m\({}^{2}\)) and flying at relatively low altitudes above ground (7 to 26 m), thus achieving very high GSDs (0.001 to 0.004 m pixel\({}^{-1}\)).