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Título: | Spatial Downscaling of MODIS Snow Cover Observations Using Sentinel-2 Snow Products |
Autor: | Revuelto, Jesús CSIC ORCID; Alonso-González, Esteban CSIC ORCID; Gascoin, Simon; Rodríguez-López, Guillermo; López-Moreno, Juan I. CSIC ORCID | Palabras clave: | Snow distribution Mountain areas Optical satellite sensors High resolution Downscaling Snow cover area MODIS Sentinel-2 |
Fecha de publicación: | 10-nov-2021 | Editor: | Multidisciplinary Digital Publishing Institute | Citación: | Remote Sensing 13(22): 4513 (2021) | Resumen: | Understanding those processes in which snow dynamics has a significant influence requires long-term and high spatio-temporal resolution observations. While new optical space-borne sensors overcome many previous snow cover monitoring limitations, their short temporal length limits their application in climatological studies. This work describes and evaluates a probabilistic spatial downscaling of MODIS snow cover observations in mountain areas. The approach takes advantage of the already available high spatial resolution Sentinel-2 snow observations to obtain a snow probability occurrence, which is then used to determine the snow-covered areas inside partially snow-covered MODIS pixels. The methodology is supported by one main hypothesis: the snow distribution is strongly controlled by the topographic characteristics and this control has a high interannual persistence. Two approaches are proposed to increase the 500 m resolution MODIS snow cover observations to the 20 m grid resolution of Sentinel-2. The first of these computes the probability inside partially snow-covered MODIS pixels by determining the snow occurrence frequency for the 20 m Sentinel-2 pixels when clear-sky conditions occurred for both platforms. The second approach determines the snow probability occurrence for each Sentinel-2 pixel by computing the number of days in which snow was observed on each grid cell and then dividing it by the total number of clear-sky days per grid cell. The methodology was evaluated in three mountain areas in the Iberian Peninsula from 2015 to 2021. The 20 m resolution snow cover maps derived from the two probabilistic methods provide better results than those obtained with MODIS images downscaled to 20 m with a nearest-neighbor method in the three test sites, but the first provides superior performance. The evaluation showed that mean kappa values were at least 10% better for the two probabilistic methods, improving the scores in one of these sites by 25%. In addition, as the Sentinel-2 dataset becomes longer in time, the probabilistic approaches will become more robust, especially in areas where frequent cloud cover resulted in lower accuracy estimates. | Versión del editor: | https://doi.org/10.3390/rs13224513 | URI: | http://hdl.handle.net/10261/255341 | DOI: | 10.3390/rs13224513 | E-ISSN: | 2072-4292 |
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