Environmental Engineering Reference
In-Depth Information
Clouds present the major problem for snow cover mapping from satellite
observations in the optical spectral range. Estimates of Simic et al. ( 2004 ) show
that in daily MODIS-based snow maps, clouds occupy about 40% of the area in the
middle and high latitudes. Inability to distinguish between snow-free and snow-
covered land beneath the clouds cause discontinuity both in the time series and in
the derived spatial distribution of snow cover and therefore reduce the value of
these products for model applications. Because of cloud gaps, optical snow maps do
not allow for accurate estimation of the continental or hemispherical snow extent on
a daily basis. Partial improvement in the map area coverage can be achieved with
geostationary satellites which provide multiple observations per day and hence
increase the chance to see the land surface clearly without cloud (Romanov and
Tarpley 2006 ; de Wildt et al. 2007 ). With geostationary satellites, however, the map
coverage is only regional and is limited to the area within ~ 65 N and S.
Snow maps derived from satellite observations in the visible and infrared
generally demonstrate higher accuracy than corresponding microwave products.
MODIS snow maps were found to correspond to surface observations of snow
cover in 90-100% of cases over non-forested locations, deciduous forests, and in
80-90% over dense coniferous forests (Simic et al. 2004 ). Hall and Riggs ( 2007 )
estimated the average rate of agreement between MODIS 500 m resolution snow
maps and in situ data equal to 93%. A slightly lower, 88%, agreement was reported
by Romanov et al. ( 2000 ) for snow maps derived from observations of Geostation-
ary Operational Environmental Satellite (GOES). All of the above estimates pertain
to North America; however, there is no reason to expect substantially different
accuracies of snow retrievals in Eurasia.
Continuous observations from AVHRR onboard different NOAA satellites have
been available since the late 1970s. The Canadian Center for Remote Sensing
(CCRS) has applied an automated technique to consistently reprocess historical
AVHRR data for the time period from 1982 to 2005 and to establish the snow cover
climatology over Canada at 1 km resolution (Khlopenkov and Trishchenko 2007 ).
Expanding these efforts to the whole globe would lead to the development of a
consistent long-term dataset suitable for snow climatology and climate change
studies.
References
Armstrong RL, Brodzik MJ (2001) Recent Northern Hemisphere snow extent: a comparison of
data derived from visible and microwave satellite sensors. Geophys Res Lett 28:3673-3676
Baum BA, Trepte Q (1999) A grouped threshold approach for scene identification in AVHRR
imagery. J Atmos Ocean Technol 16:793-800
de Wildt MD, Gabriela S, Gruen A (2007) Operational snow mapping using multitemporal
Meteosat SEVIRI imagery. Remote Sens Environ 109:29-41
Derksen C, Walker A, Goodison B (2003) A comparison of 18 winter seasons of in situ and passive
microwave-derived snow water equivalent estimates in Western Canada. Remote Sens Environ
88:271-282
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