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Article

Estimating Fractional Snow Cover in Open Terrain from Sentinel-2 Using the Normalized Difference Snow Index

1
CESBIO, Université de Toulouse, CNES/CNRS/INRA/IRD/UPS, 31400 Toulouse, France
2
Centre d’Etudes de la Neige, Université Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, 38400 Saint Martin d’Hères, France
3
Magellium, 31400 Toulouse, France
4
Pyrenean Institute of Ecology, CSIC, 50820 Zaragoza, Spain
5
Tenevia, 38240 Meylan, France
6
alpS Research, Institute of Geography, University of Innsbruck, A-6020 Innsbruck, Austria
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(18), 2904; https://doi.org/10.3390/rs12182904
Received: 8 July 2020 / Revised: 27 August 2020 / Accepted: 4 September 2020 / Published: 8 September 2020
(This article belongs to the Special Issue Recent Advances in Cryospheric Sciences)
Sentinel-2 provides the opportunity to map the snow cover at unprecedented spatial and temporal resolutions on a global scale. Here we calibrate and evaluate a simple empirical function to estimate the fractional snow cover (FSC) in open terrains using the normalized difference snow index (NDSI) from 20 m resolution Sentinel-2 images. The NDSI is computed from flat surface reflectance after masking cloud and snow-free areas. The NDSI–FSC function is calibrated using Pléiades very high-resolution images and evaluated using independent datasets including SPOT 6/7 satellite images, time lapse camera photographs, terrestrial lidar scans and crowd-sourced in situ measurements. The calibration results show that the FSC can be represented with a sigmoid-shaped function 0.5 × tanh(a × NDSI + b) + 0.5, where a = 2.65 and b = −1.42, yielding a root mean square error (RMSE) of 25%. Similar RMSE are obtained with different evaluation datasets with a high topographic variability. With this function, we estimate that the confidence interval on the FSC retrievals is 38% at the 95% confidence level. View Full-Text
Keywords: snow; snow cover area; fractional snow cover; Sentinel-2 snow; snow cover area; fractional snow cover; Sentinel-2
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MDPI and ACS Style

Gascoin, S.; Barrou Dumont, Z.; Deschamps-Berger, C.; Marti, F.; Salgues, G.; López-Moreno, J.I.; Revuelto, J.; Michon, T.; Schattan, P.; Hagolle, O. Estimating Fractional Snow Cover in Open Terrain from Sentinel-2 Using the Normalized Difference Snow Index. Remote Sens. 2020, 12, 2904. https://doi.org/10.3390/rs12182904

AMA Style

Gascoin S, Barrou Dumont Z, Deschamps-Berger C, Marti F, Salgues G, López-Moreno JI, Revuelto J, Michon T, Schattan P, Hagolle O. Estimating Fractional Snow Cover in Open Terrain from Sentinel-2 Using the Normalized Difference Snow Index. Remote Sensing. 2020; 12(18):2904. https://doi.org/10.3390/rs12182904

Chicago/Turabian Style

Gascoin, Simon, Zacharie Barrou Dumont, César Deschamps-Berger, Florence Marti, Germain Salgues, Juan I. López-Moreno, Jesús Revuelto, Timothée Michon, Paul Schattan, and Olivier Hagolle. 2020. "Estimating Fractional Snow Cover in Open Terrain from Sentinel-2 Using the Normalized Difference Snow Index" Remote Sensing 12, no. 18: 2904. https://doi.org/10.3390/rs12182904

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