# Insights into Segmentation Methods Applied to Remote Sensing SAR Images for Wet Snow Detection
## 3 Results
### Further Evaluations
The figure also shows the obtained snow probability curves from the segmentation methods studied in the paper using Sentinel-1 ascending scenes observed on 16, 22 and 28 April 2018. Now, we consider the other scores calculated over the entire season to evaluate the sensitivity of the methods to variations in weather and snow conditions. Figure 15 shows the time evolution of correlations, hamming distance and Heidke Skill scores for different segmentation methods. Figure 15a shows that the correlation rates for all the methods varied significantly over the season. The correlation rate was best during periods of generalized melting due to the abundance of wet snow in the domain. Let us recall that the optical snow mask did not discriminate the presence of wet or dry snow, making comparing data over the winter season more difficult. The segmented surface was generally smaller than the surface of the observed snow mask due to dry snow. We had a few cases of negative correlation in winter, which corresponded to situations where areas with wet snow corresponded mostly to areas without snow in the optical mask. One possible explanation was the gap in dates between the optical and SAR images. During the melt period, one could see that the methods with low noise filtering had lower correlation rates. The Random Forest method, with edge zones taken into account, gave good results on 22 April 2018, but presented more fluctuating correlation rates, due to its sensitivity to irrigated agricultural areas. Against expectations, the Otsu method with filtering, which used an adaptive threshold, ultimately never achieved better scores than the fixed thresholding with filtering. Given these scores, finding a suitable threshold for the whole image was not a determining factor. Figure 13: RMS errors computed using probability curves shown in Figure 12 at different dates of Sentinel-2 and Sentinel-1 observations: 16 April 2018 (diamond symbol), 22 April 2018 (square symbol) and 28 April 2018 (cross symbol). Results are given by altitude range: (**top**) 0–2000 m, (**bottom**) 2000–2500 m.  
Figure 14: Same as the Figure 13 but for altitude ranges: (**top**) 2500–3000 m and (**bottom**) all altitudes. Figure 15: _Cont_. Figure 16 shows the distribution of wet snow as a function of altitude for the Belle-donne massif, northern orientation, and the segmentation methods 2 dBF, RF, MF and RW, respectively, according to the method introduced in [26]. Figure 17 is similar to Figure 16 but for the northern orientations. Melt lines generated in this way at the scale of the massif of Belledonne could be compared with the information from the BERA of this massif. Over the melt period, we can see that the continuous snow line aligned with the altitude of the maximum snow gradient for the four methods. The presence of some noise for the MF segmentation method did not interfere with the estimation of the altitude of the wet snow zone. For methods that best filtered the noise, the wet snow gradient was much sharper, and there were few false detections at low elevations, even in summer. We also noted that the warmer rainy episodes in January were well associated with wet snow. The diagrams calculated from the different methods were very comparable, despite some differences (presence or absence of snow at low altitudes, and over-detection of snow at the end of the season for some methods). In some classes, the number of pixels associated with wet snow was slightly more significant for the MF and RW methods. Figure 15: (**a**) Correlation scores between wet snow segmentations and target snow products (Sentinel-2 as close in time as 5 days) over the 31 TGL tile and the entire season. Results are given for 7 segmentation methods. (**b**) same as (**a**) but for Hamming distance, (**c**) same as (**a**) but for Heidke Skill Score. These diagrams highlight the case of 27 February, which was characterized by very low temperatures over the entire area, with no melting observed during the day and no rain over recent days.