## 4 Results
### Snow Depth Retrieval  
Snow depth maps produced for each of the studied areas are presented in Figure 4 along with the difference between probed (\(HS_{m}\)) and estimated snow depth (\(HS_{UAS}\)) at the VPs locations. The mapping resolutions achieved together with the snow depth validation statistics are presented in Table 4. Validation statistics include the average difference (or mean bias) and the RMSE between \(HS_{m}\) and \(HS_{UAS}\). The results indicate an overall good performance for all the surveyed areas with results agreeing with relevant literature [27]. These results confirm the overall feasibility of the proposed low-cost method capture snow depth variability over different types of snow covers in the Arctic as compared to traditional methodologies. The outcomes of the additional validation method using snow free areas are shown in Figure 5 as distribution histograms. The \(HS_{UAS}\) estimates are expected to be mostly distributed around the zero values over the tracked dark pixels (_normal_ distribution). Although not overly representative of the snow-covered areas, this test assists on quantifying the performance of the method further away from the GCPs and exposes the nature of the DEM bias (translated, rotated, or deformed) through comparison with the underlying topography. The sample size for each snow-free validation point corresponds to the snow surface DEM resolution for that area (Table 3). The number of samples for each study area is dependent on the resolution of the orthophoto, the number of snow-free areas, and orthophoto contrast characteristics. Centimeter-scale average difference was achieved at the VPs at Sval1 and Sval2 (Table 4). The snow-free validation is in agreement with these observations for both areas with an evident _normal_ distribution (Figure 5). The snow-free control areas are positively characterized by a well-distributed network (Figure 1). Greenland areas provided centimeter to decimeter average difference and RMSE in the VPs (Table 4). However, the average difference increased slightly in comparison to the Svalbard areas. This is attributed to the land-based surveys of the underlying topography, which provided coarser and less accurate TDEMs for snow depth calculation. The snow-free VPs distributions for areas Green1, Green3 and Green4 (Figure 5) also presented a _normal_ distribution centered near zero, although a skewed histogram is clearly observed with a slight \(HS_{UAS}\) overestimation. This was attributed in part to the wrong surface interpolation around boulders edges surrounded by snow (example in Figure 2e). Vegetation cover was usually present in areas where an underestimation of \(HS_{UAS}\) was observed (slightly negative, blue values in Figure 4). Green1, Green3, and Green4 presented zones associated with negative \(HS_{UAS}\), which coincide with the rise of grass vegetation. This resulted in an underestimation of approximately the observed grass height (5-15 cm). For area Green2, control trough VPs resulted particularly affected around areas with thick vegetation such as the slope. This is observable by comparing its error map (Figure 4) and the visible vegetation in Figure 1 orthomosaic