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Your
query was:
an="H13J-05"
HR: 14:45h
AN: H13J-05 INVITED
TI: Characteristics
of Snow Cover in the Sierra Nevada from MODIS and Landsat
AU: * Dozier, J
EM: dozier@bren.ucsb.edu
AF: University of California, Donald Bren School of
Environmental Science and Management, Santa Barbara, CA 93106-5131 United
States
AU: Painter, T H
EM: tpainter@nsidc.org
AF: University of Colorado, National Snow and Ice
Data Center, Boulder, CO 80309 United States
AU: Frew, J E
EM: frew@bren.ucsb.edu
AF: University of California, Donald Bren School of
Environmental Science and Management, Santa Barbara, CA 93106-5131 United
States
AB: Optical sensors, such as Landsat and MODIS,
provide maps of snow cover and its albedo. From Landsat, the spatial
resolution is 30m at 16d intervals, whereas the information from MODIS is at
500m spatial resolution but at daily intervals. Particularly in the case of
MODIS, an algorithm must use the spectral information to estimate the
subpixel snow properties to avoid systematic errors in mountain ranges where
snow cover increases with elevation. The albedo measurements are necessary if
a distributed energy-balance model is to use the snow properties as input.
Optical sensors cannot estimate snow depth or water equivalence, but their
the images' textures correlate with ground measurements from snow courses or
snow pillows. Finally, a database system is necessary to manage the wealth of
satellite and in situ data, and to manage the use of the data in distributed
snowmelt models.
UR: http://www.snow.ucsb.edu/
DE: 0736 Snow (1827, 1863)
DE: 0758 Remote sensing
DE: 1855 Remote sensing (1640)
DE: 1863 Snow and ice (0736, 0738, 0776, 1827)
SC: Hydrology [H]
MN: Fall Meeting 2005
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