While planning your Himalayan hike you need to take into account several aspects:
- Static factors (shown on the map)
- Terrain: type of terrain you ll hike across: forest, meadows, glaciers
- Topography: represented as contours
- Vegetation: understanding the eco regions you pass through (GIS chapter 8)
- Dynamic factors (not on the map)
- Weather: precipitation (rain and snowfall) and temperature (day and night). You can check the forecast for a region and timespan through sites like windy.com. Seasonal planning can be done using historical average data (GIS chapter 9)
- Water flow: when crossing streams you need to understand the water flow which depends on several factors: season (snow, glacial melt), recent precipitation, temperature and watersheds (GIS chapter 10)
- Snow cover: is very dynamic: changes as per seasons, recent precipitation and temperature. The snowline can change hundreds of meters in a matter of days. Snow freezes in the morning (slippery) and melts / gets soft in the afternoon (you sink inside). Snow, Temperature and Topography define how challenging a hike will be – e.g. climbing steep frozen snow in the morning near a pass
- Vegetation: forest cover and barren areas are fixed on the map. However scrub / meadows can change significantly depending on the season: open meadow in Spring vs. 2m high bushes post monsoon making it difficult to navigate
In this post we will take a closer look at assessing snow cover for an immediate planned hike based on real-time weather data and a future planned hike based on historical seasonal averages. We use data from Copernicus, European Space Agency’s (ESA) Earth observation program. Copernicus aims to provide accurate and timely information to improve environmental management, understand climate change, and deliver services for citizens and organizations
- Copernicus Browser
- Sentinel-2 2LA
- Snow Cover (NDSI Band)
- Analyzing Snow Cover in QGIS
- Historical Snow Cover (SCE)
Copernicus Browser
Say we wish to go for a hike across the Kaliheni pass (4800m) connecting Manali and Bara Bhangal across the Dhauladar. One important thing to assess for a high altitude pass is the current snow cover. Steep high altitude terrain combined with (frozen) snow can be very challenging. Most popular satellite maps (Google, Bing, ESRI…) show data which is usually several months old. Snow cover can change significantly within a few days. There are a few commercial real-time satellite providers which can be costly. One freely available near-time provider is Copernicus from ESA.
Open up the Copernicus browser. Initially the site will feel a bit overwhelming but once you get to know it, it will become a powerful tool to check recent and historical satellite data. Left shows the date (range) and satellite configuration you are looking at, right shows the map.
I first suggest you Login / Register an account by entering basic details and confirming your email ID. You will need to login in order to use all features and export data to QGIS. Once you have created a login let’s first identify the exact location of the Kaliheni pass. Search “Sagor Jot” in osm.org and copy the coordinates:
Paste the coordinates of Sagor Jot in the Copernicus browser search box and put a marker at the exact location for easy reference:
Sentinel-2 2LA
Click “Show latest date” to get the most recent available data with max 30% cloud cover from the default satellite “Sentinel-2 L2A”. In this case we get data from 29 November, just 5 days old. We see that the pass is covered in snow, less on the East facing slope and more on the West facing slope. You can zoom in as the satellite map resolution is pretty detailed.
Snow Cover NDSI
Sentinel-2 L2A has several specialized bands for enhanced visualization of natural features like vegetation, water, snow, etc. Choose the NDSI band (Normalized Difference Snow Index) which will show the snow cover in bright blue distinguishing it from possible cloud cover. You can click the layers icon in the top-right corner to switch back to a plain OSM base map anytime.
Analyzing in QGIS
Use the “Select Area of Interest” icon on the toolbar to draw the region which you would like to export.
Choose the “Download Image” tool to export the marked area. Choose “Analytical”, “TIFF” (geo-referenced format which can be imported in QGIS) and click “Download”:
Drag n drop the TIFF file in QGIS to open it as a raster layer.
Now to get a better view of the current snow cover let’s visualize this layer with 20% transparency on a OpenTopoMap base layer. We can now clearly see the snowline on the shaded topo map:
Zoom in to identify the exact snow line on the East side of the pass at around 4600m:
On the West facing slope (less solar exposure, less snow melt) the snow line is much lower at around 4200m:
Historical Snow Cover
Best way to predict the future is using historical averages. Copernicus has Snow Cover Extent (SCE) with a 1km resolution for the Northern Hemisphere daily since 2018. An annual average gives for a given date or month gives a good prediction for the future (assuming no major changes are introduced by recent climate change). Here we see the snow cover mid April 2025 over the Eastern Dhauladar at 1km resolution:
We can download the SCE layer in GeoTIFF format and overlay in QGIS with 50% transparency on top of a grayscale topo base map overlaid with Waymarked Hiking Trails. This clearly shows us % snow cover on the major hiking routes mid April. Kaliheni (KP) and Thamsar (TP) are mostly snow free on their East / South facing approach and 100% snow cover below the pass and for a good amount on the West / North facing descends.
You can download data for your region of interest for 2018 till now, filter on a given date and use the QGIS raster calculator to get an average over the same period. Right now Copernicus browser is giving an error while trying to download a range instead of one single date.
Alternatively we could also make a more informed decision by checking the snow over of the previous year around the same date. Say we wish to attempt the Thamsar pass early June in 2026. To get an estimated idea we can look at the previous year snow cover. Copy the Thamsar coordinates (32.2259259, 76.7777470) in the Copernicus browser to mark the pass and load data for June 2025.
As clouds seem to partly block the view, use the NDSI layer and mark select your area of interest and download as GeoTIFF:
Import the GeoTIFF file as a raster in QGIS with 20% transparency above a topographic base map:
We can clearly see that on 5th June the Thamsar pass (4700m) was mostly snow free on the South slope except for a small patch at 4510-4560m below the pass. On the North slope, except nearto the pass, the approach is covered in snow all the way till 4280m (400m snow descent).