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Discussion papers
https://doi.org/10.5194/essd-2018-144
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2018-144
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  29 Nov 2018

29 Nov 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

Theia Snow collection: high resolution operational snow cover maps from Sentinel-2 and Landsat-8 data

Simon Gascoin1, Manuel Grizonnet2, Marine Bouchet1,2, Germain Salgues2,3, and Olivier Hagolle1,2 Simon Gascoin et al.
  • 1CESBIO, Université de Toulouse, CNRS/CNES/IRD/INRA/UPS, Toulouse, France
  • 2CNES, Toulouse, France
  • 3Magellium, Toulouse, France

Abstract. The Theia Snow collection routinely provides high resolution maps of the snow cover area from Sentinel-2 and Landsat-8 observations. The collection covers selected areas worldwide including the main mountain regions in Western Europe (e.g. Alps, Pyrenees) and the High Atlas in Morocco. Each product of the Snow collection contains four classes: snow, no-snow, cloud and no-data. We present the algorithm to generate the snow products and provide an evaluation of their accuracy using in situ snow depth measurements, higher resolution snow maps, and visual control. The results suggest that the snow is accurately detected in the Theia snow collection, and that the snow detection is more accurate than the sen2cor outputs (ESA level 2 product). An issue that should be addressed in a future release is the occurrence of false snow detection in some large clouds. The snow maps are currently produced and freely distributed in average 5 days after the image acquisition as raster and vector files via the Theia portal (http://doi.org/10.24400/329360/F7Q52MNK).

Simon Gascoin et al.
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Simon Gascoin et al.
Data sets

Theia Snow collection S. Gascoin, M. Grizonnet, O. Hagolle, and G. Salgues https://doi.org/10.24400/329360/f7q52mnk

Model code and software

Let-it-snow M. Grizonnet, G. Salgues, T. Klempka, and S. Gascoin https://doi.org/10.5281/zenodo.1689897

Simon Gascoin et al.
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Short summary
The Sentinel-2 satellite mission allows the observation of the land surface at unprecedented resolutions (20 m every 5 days). The frequency of observations can be further increased with Landsat-8. Here we describe a new collection of snow maps made from Sentinel-2 and Landsat-8 and evaluate their accuracy. The data are routinely produced over several mountain areas and freely distributed via http://theia.cnes.fr. These new data could unlock advances in our understanding of mountain ecosystems.
The Sentinel-2 satellite mission allows the observation of the land surface at unprecedented...
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