SNOWTOOLS--A European Project for Research and Development
of Remote Sensing Methods for Snow Hydrology
Rune Solberg1, Tore Guneriussen2, Martti Hallikainen3,
Jarkko Koskinen3, and Daniel Hiltbrunner4
SNOWTOOLS is a European Commission Environment & Climate Program research and develop-
ment project. The main objective is to develop methods for the extraction of snow parameters from
optical and microwave remote sensing data. Based on interviews of various user groups, ranging
from hydropower industry and water management to climatology, a set of snow products has been
defined. The products include snow-cover area, snow water equivalent, albedo, snow wetness, snow
surface temperature, and snow depth. The spatial resolution of the products is 250 and 500 m, and the
required delivery time is between 2 and 24 hours for most products. The product specification is used
as a "driving force" for development of algorithms.
A comparison between the products defined and the state of the art of snow mapping has resulted in
recommendations for further research. For optical remote sensing of snow, research is mainly rec-
ommended for subpixel classification of SCA; modeling and compensation for temporal, topo-
graphic, and anisotropic reflectance effects; and compensation for vegetation/forest. For SAR, more
research is needed on capability to measure snow-covered ground and melting snow, effects of vege-
tation, use of polarimetry, combined use of various frequencies, and use of SAR interferometry.
Similarly, for PMR: Algorithms for multitemporal and low and high frequency data; effects of mixed
signatures, vegetation, atmosphere and rugged terrain; investigation of error sources; development
of new algorithms for the water equivalent retrieval; and assessment of interpolation techniques.
Two dedicated remote sensing experiments, one for mountainous basins and one for boreal basins,
are carried out for both the development and validation. The mountain basin field campaigns in 1997
and 1998 have established a multitemporal/multisensor data set for algorithm development, includ-
ing ERS, RADARSAT, Landsat TM, and DAIS airborne spectrometer data.
SAR data from the EMAC `95 campaign is also analyzed in the project. Three combined remote
sensing and ground data acquisition campaigns were conducted in March, May, and July 1995. Sev-
eral ERS-1 and EMISAR C- and L-band full polarimetric scenes were obtained from the test site.
The extent of a wet snow cover observed by EMISAR C-VV corresponds to optical airborne meas-
urements. Results show that C-band polarimetric data from March, when the content of free water in
the snow was in the range 13%, are affected by the underlying vegetation. Discrimination between
bare ground and snow is exceptionally good for wet snow.
Norwegian Computing Center, P.O. Box 114 Blindern, N-0314 Oslo, Norway; Telephone: +47 2285 2500;
Fax: +47 2269 7660; E-mail: email@example.com
2 NORUT IT Ltd., N-9005 Troms, Norway
3 Helsinki University of Technology, Finland
4 University of Bern, Switzerland