Monitoring the snow cover in ski resorts using Sentinel-2



We are preparing the distribution of maps of the snow cover extent made from the Sentinel-2 data for Theia. If the method used to detect the snow is based on well-proven concepts, spatial and temporal resolution of the snow maps will however quite unprecedented. Until now, maps of the snow cover extent were usually produced from MODIS observations at 500 m resolution, which is adapted to hydro-climatic studies to rather regional scales. Landsat data were actually little exploited by snow scientists because of their low repeatability. The deployment of Sentinel-2 mission (global coverage at 20 m resolution every 5 days) opens new perspectives for monitoring snow cover.
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Sentinel-2A (and Landsat-8) capture a giant ice avalanche in Tibet

After reading my previous post about the Rutog ice avalanche, my distinguished colleagues Antoine R. and Olivier H. challenged me to look for a pre-event image to better highlight the avalanche area. The closest clear-sky image that I could find is a Landsat-8 image that was acquired on June 24 (23 days before the slide).


Sequence of two Landsat-8 and Sentinel-2A images. Both images are level 1 product displayed as natural color composites. Click to enlarge.

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Sentinel-2A captures a giant ice avalanche in Tibet

The Nature News website reported yesterday on a massive ice avalanche that happened in Rutog, Tibet, on 17 July 2016. This ice avalanche killed 9 people and may be one the largest ever observed. The ice and rock mixture spread over 6 km from the collapse point up to the Aru Co lake shoreline.

Sentinel-2A image of the Rutog ice avalanche acquired on 21-Jul-2016 (4 days after the event). Click on the image to see at full resolution (1 pixel = 10m).

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Snow and Fire in the Dragon mountains

NASA's blog "Image of the Day" recently featured two beautiful MODIS images of the snow cover in Lesotho. In late July Lesotho experienced its heaviest snowfall in two decades. The snow is not uncommon in Lesotho given that over 80% of the country lies above 1800 m (wikipedia). However the frequency of such snow events has been reducing over the past decades due to the ongoing climate change. As a result the shepherds are less accustomed to the snow conditions so that "a severe storm like the one in July 2016 has greater potential to kill sheep and shepherds" [1]. Continue reading

Kittens time series


Optical remote sensing is great to map the snow cover extent in mountain regions as long as there is no cloud above the land surface. Radar remote sensing of the snow cover is not operational yet mainly because the backscatter from the snow surface is strongly dependent on the snowpack liquid water content. On the ground, however, thousands of people are observing the snow cover in the mountains, everyday. Some of them take photographs and kindly upload them to photo-sharing websites with a public license. Many of these photos are geotagged, either because the cameras have built-in GPS, or because the users added geographical coordinates when publishing their album.
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First Sentinel-2 snow map



In the framework of the THEIA land data center, we have developed a simple but robust method to map the snow cover from Sentinel-2-like level 2A products. This code was tested with SPOT-4 Take-5 and Landsat-8 series, but it remained to adapt it so that it can run on real Sentinel-2 images! This is now done thanks to Manuel Grizonnet, which allowed us to process the Sentinel-2A image acquired on 06-July-2015 in the Pyrenees as a first example. This image was produced at level 2A by Olivier Hagolle using the MACCS processor. The snow mask from Sentinel-2 images is calculated at 20 m resolution after resampling the green and red bands that are originally at 10 m resolution while the NIR band is at 20 m.

How to make sure everything went well? We can control the snow mask by superposing the mask boundaries on a false color composite:


The Sentinel-2A image of 06-July-2015 (level 2A, tile 30TYN) and its snow mask. The snow mask is in magenta and the background image is a color composite RGB NIR/Red/Green. We also show a zoom in the Vignemale area.

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The snow cover area of the Canigou mountain in January since 1985


Franck Roux told this sentence in his lecture "Should we be afraid of climate change?" given at the University Paul Sabatier on December 10, 2015 (I quote from memory):

"The human being is a very good weather sensor, but it is a poor climate sensor."


Since our memory can play tricks on us, satellite images are valuable data. As we have seen in a previous article, the snow cover area in the Pyrenees was rather small in January 2016. We can reconstruct the snow extent across the whole mountain range since 2000 with MODIS or even 1998 with SPOT-VGT. However if you want to zoom in on a specific region, the spatial resolution offered by these sensors quickly becomes insufficient so we must turn to the Landsat archive. Continue reading

Ice breaker

=>  Among the sites observed by SPOT5 (Take5), there was the Baffin Island, in the North of Canada. The cloud cover was very high on that site, but it still let us observe the snow melt over land, and the sea ice disappear. As you will see below, it is fascinating to see how the ice cover breaks into pieces. I guess specialits could tell us lots of things on this time series, but I am not a specialist.  If you happen to be a specialist, your comments will be welcome !


Summer is short at this lattitude, and as early as the first of September, the snow is back in the mountains, and ten days later, one of the inlets starts to freeze. A large Iceberg did not have time to melt during that summer, and if you look closely at the first images, it seems the iceberg was already stuck there all winter.


During summer, the slopes oriented towards South have taken a greenish tint, sign that a few mosses or weeds had time to grow.

Take5 goes to the movies


How to go from 1 image every 5 days to 24 images per second ?

It was possible, thanks to CNES funding, thanks to an imaginative producer, Gérard Dedieu (who does not smoke cigars yet), thanks to a talented film director and scenarist, Thierry Gentet (the only film director who understands space mechanics), and thanks to his team, Mira Production, who are even able to shoot beautiful images in our  ... splendid CESBIO offices, and thanks to a series of promising actors and actresses Anne Jacquin, Valérie Demarez, Virginie Lafon, Valery Gond, Jean-Pierre Dedieu, and another one, the last one, who cannot say a full sentence before the 5th take.


We hope this little film will help you understand or explain the possibilites and opportunities offered by multi-temporal images at a high resolution, and that it will give you ideas to use the new SPOT5 (Take5) data.