Vitenskapelig artikkel   2017

Solberg, Rune; Salberg, Arnt-Børre; Trier, Øivind Due; Rudjord, Øystein; Stancalie, Gheorghe; Diamandi, Andrei; Irimescu, Anisoara; Craciunescu, Vasile

Publikasjonsdetaljer

Tidsskrift:

Romanian Journal of Physics, vol. 62, 2017

Utgave:

821

Internasjonale standardnumre:

Trykt: 1221-146X

Lenker:

OMTALE: http://publications.nr.no/1517844374/Snow_wetness_2017_Solberg.pdf
FULLTEKST: http://www.nipne.ro/rjp/2017_62_9-10/RomJPhys.62.821.pdf

Snow monitoring is essential for prediction of flooding due to rapid snowmelt, to provide snow avalanche risk forecasts and for water resource management – including hydropower production, agriculture, groundwater and drinking water. Sentinel-1 C-band SAR is sensitive to presence of wet snow and can be used to binary snow-wetness classification. Wet-snow mapping into more categories has been demonstrated in the past by using MODIS data. The combination of surface temperature and the temporal development of the effective snow grain size are used to infer approximately how wet the snow is.