New Product Feature: Snow Depth Map
Looking for safe trips in the snow? Preferably with a lot of snow for a successful ski tour or as little snow as possible for a wintry but safe route on foot? Introducing our latest feature: the snow depth map for the Alpine region.
If you enjoy snow, the snow depth and snow cover maps provide information about where and how much of it you will currently find on your trip. Using high-resolution satellite images and ground measurements, we show you what to expect when planning your trips.
Snow Depth Map
As a Pro+ user, you will find the ‘Snow Depth’ as a ‘Style’ option for both the Outdooractive map and the OpenStreetMap as part of your “Weather & Climate” information, which is accessed by selecting the ‘Maps and trails’ button at the bottom right of the map panel. You can activate the snow depth map in almost all map views and use it when planning your routes and trips. The information can also be used in combination with the Outdooractive Avalanche Report which you can activate under the ‘Additional layers’ section and run at the same same time. Now you have all the information you need to plan and safely enjoy your trip.
Current Snow Cover
Snow can be a huge source of fun, but it can also bring many dangers, and while some might be on the lookout for the best snow conditions, such as ski tourers, others will prefer to avoid it altogether, like mountain bikers. In order to gain a comprehensive overview of snow conditions, ExoLabs has developed an innovative solution based on satellite data and ground measurements.
Satellite data enables up-to-date mapping of snow cover across an entire mountain range. ExoLabs uses data provided by satellites from both NASA and the ESA that is then converted to create a high temporal and spatial resolution of the snow layer. This map is updated daily and allows is accurate to within 20 meters (with individual image pixels corresponding to an area of 20 x 20 meters).
Note: Currently the snow maps are only available on the web, but not on the App.
As transmission, processing, and analysis of satellite images can take up to 24 hours, our daily snow layer most closely matches the conditions of the previous day, and cloud cover is a critical limitation to the unobstructed view of the satellites. To fill these data gaps, ExoLabs uses information from the most recent cloud-free satellite imagery as well as imagery of the immediate neighborhood to best model the spatial snow distribution. It should be emphasized here that prolonged periods of overcast weather can lead to larger uncertainties in snow cover. The last direct observation may vary in age depending on the geographic area. In very densely forested regions, snow on the ground may be masked by a snow-free canopy.
Current Snow Depth
For many users, the height of the snowpack is of great importance, as it determines the choice of activity and the equipment needed. To model the snow depth in the best possible way, ExoLabs uses the measured snow depths from measuring stations. With the help of geostatistical methods, which take into account local as well as regional differences in snow distribution, the spatial snow distribution can then be modeled. Topographic influences on snow distribution are also taken into account such as a steep slope which can carry a lower snow load than a topographic depression.
The resulting daily snow depth thus takes into account the main influences on snow distribution and represents them at a 20 m areal resolution. When interpreting the data, it is important to understand that these figures represent an average value for the immediate area. There can be a great deal of local variation in the snowpack which cannot be captured in detail at the 20 m resolution. This means that the depth given given uses an approximate average value for this area.
Linked to the University of Zurich, ExoLabs specializes in environmental monitoring. Using satellite data as well as weather and climate models, and modern machine learning techniques, ExoLabs is able to gain a comprehensive insight into the condition of our environment. This valuable information is then presented in a user-friendly format in order to facilitate informed and sustainable decision-making.