Estimación de área cubierta de nieve húmeda con datos SAR en la cuenca del río Tupungato, Mendoza, Argentina
Teverovsky Korsic SA
Gaston Pascual I
Salinas de Salmuni G
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The data coming from remote sensing, in particular Synthetic Aperture Radars (SAR), have great potential in the study of snow since they provide information regardless of the prevailing weather condition. In this work, the capacity of the C band in wet snow detection is investigated, in the Tupungato river basin, province of Mendoza, Argentina. To this end, Sentinel 1 images were used, processed following the methodology developed by Nagler and Rott (2000), which uses the technique of change detection respect to an image taken as a reference, in a snow-free condition. This algorithm requires the adaptation of parameters according to the particular characteristics of the study area. At the methodological level, the selection of the threshold (-2dB) to separate snow coverings was decisive. The results were validated indirectly from data on surface temperature and snow cover area, obtained with Landsat 8 optical images. In this way, was verified the correct classification with SAR of pixels corresponding to wet snow. Nival fusion area maps generated with SAR data are very useful to nourish hydrological models for the forecast of flow in mountain areas with nival regime.