Abstract
The main objective of this study was to monitor wet snow conditions from Sentinel-1 over a season, to examine its variation over time by cross-checking wet snow with independent snow and weather estimates, and to study its distribution taking into account terrain characteristics such as elevation, orientation, and slope. One of our motivations was to derive useful representations of daily or seasonal snow changes that would help to easily identify wet snow elevations and determine melt-out days in an area of interest. In this work, a well-known approach in the literature is used to estimate the extent of wet snow cover continuously over a season and an analysis of the influence of complex mountain topography on snow distribution is proposed taking into account altitude, slope, and aspect of the terrain. The Sentinel-1 wet snow extent product was compared with Sentinel-2 snow products for cloud free scenes. We show that while there are good agreements between the two satellite products, differences exist, especially in areas of forests and glaciers where snow is underestimated. This underestimation must be considered alongside the areas of geometric distortion that were excluded from our study. We analysed retrievals at the scale of our study area by examining wet snow Altitude–Orientation diagrams for different classes of slopes and also wet snow Altitude–Time diagrams for different classes of orientations. We have shown that this type of representation is very useful to get an overview of the snow distribution as it allows to identify very easily wet snow lines for different orientations. For an orientation of interest, the Altitude–Time diagrams can be used to track the evolution of snow to locate altitudes and dates of snow loss. We also show that ascending/descending Sentinel-1 image time series are complementary to monitor wet snow over the French alpine areas to highlight wet snow altitude ranges and identify melt-out days. Links have also been made between Sentinel-1 responses (wet snow) and snow/meteorological events carefully listed over the entire 2017–2018 season.
Highlights
Licensee MDPI, Basel, Switzerland.In alpine regions, monitoring the spatial and temporal variations of snow conditions is a key element for many applications such as hydrology, mountain ecosystems, meteorological, and avalanche forecasting
A Hamming distance was calculated between Sentinel-1 and Sentinel-2 binary snow products to quantify the difference between the binary matrices by associating the number of positions where the two sequences differ
Very high elevation areas and some northern slopes at low elevations are associated with snow in Sentinel-2 product and not in Sentinel-1 wet snow product. This could be due on the one hand to the presence of dry snow at very high elevations and to glaciers signature and on the other hand, as far as low elevations and north slopes are concerned, by the fact that for early morning or late evening tracks, on those kinds of slopes, the snow cover was quite thin and totally refrozen and transparent to Sentinel-1. This effect could partly be explained by the effect of snow volume scattering, increasing cross-polarization backscatter in winter, for bedrock pixels
Summary
Licensee MDPI, Basel, Switzerland.In alpine regions, monitoring the spatial and temporal variations of snow conditions is a key element for many applications such as hydrology, mountain ecosystems, meteorological, and avalanche forecasting. The number of used Sentinel-1 pixels is shown in solid line contours for the ascending orbit and dashed line contours for the descending orbit. If 100% of used data (i.e., excluding geometric distortion pixels) are associated with wet snow means that for a given class of orientation and elevation the snowpack can be assumed to be completely wet. One can notice that the percentage of snow-covered pixels varies according to the slopes and orbit direction. A larger percentage of snow pixels is noticed for western and eastern orientations for the ascending and descending orbits, respectively, especially for areas with large slopes
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