258
A. Rango, A.E. Walker and B.E. Goodison
With technological advances in data processing and transmission, data and derived
snow and ice products from many of the current sensors are available to the hydrological community in near real-time (e.g. within 6-24 hours of satellite overpass). The
development of the Internet and World Wide Web has facilitated the availability of
many remote sensing derived snow and ice products to users right from their computers. As the technology related to data access continues to advance, the hydrological
community can expect to see an expanded variety of satellite data products available
to them for use in hydrological monitoring and modeling. When both the AM-I and
PM-I EOS platforms are launched, NASA will make a variety of snow products
available to users from MODIS (daily snow cover and 8-day composite maximum
snow cover at 500m resolution; daily climate modeling grid (CMG) snow cover and
8-day composite CMG maximum snow cover at ~o x ~o resolution) and AMSR (daily
global snow-storage index map; pentab (5-day) composite snow-storage index map).
The cost associated with satellite-derived snow and ice products will vary depending
on the data policy associated with the satellite sensor. For commercial satellite
platforms, such as Radarsat-l and 2 SAR, derived products may come with a price tag
in the thousands of dollar range, whereas products from federally funded satellite
platforms (e.g. NOAA AVHRR, DMSP SSMII) are generally available at no cost via
the Internet.
References
Adam, S., Pietroniro, A. and Brugman, M.M.: Glacier snowline mapping using ERS-\ SAR imageI)'.
Remote Sensing of Environment, 61, 46-54 (1997)
Andersen, T.: SNOWSAT-Operational snow mapping in Norway. Proc. First Moderate Resolution
Imaging Spectroradiometer (MODIS) Snow and Ice Workshop, NASA Conf. Pub!. CP-3318,
NASA/Goddard Space Flight Center, Greenbelt, MD 1995, pp. 101-102
Andersen, T.: A VHRR data for snow mapping in Norway. Proc. 5th A VHRR Data Users Meeting,
Tromsoe, Norway 1991
Armstrong, R.L. and Brodzik, M.1.: An earth-gridded SSM/I data set for cl)'ospheric studies and
global change monitoring. Advances in Space Research, 16(10), 155-163 (1995)
Armstrong, R. L., Chang, A., Rango, A., and Josberger, E.: Snow depths and grain-size relationships
with relevance for passive microwave studies. Annals of Glaciology, 17, 171-176 (1993)
Baumgartner, M. F. and Rango, A.: A microcomputer-based alpine snowcover and analysis system
(ASCAS). Photogrammetric Engineering & Remote Sensing, 61 (12), 1475-1486 (1995)
Baumgartner, M. F., Seidel, K., and Martinec, J.: Toward snowmelt runoff forecast based on multi sensor remote-sensing information, IEEE Trans. Geosci. Remote Sens. 25, 746-750 (1987)
Baumgartner, M.F., Seidel, K., Haefner, H., Itten, K.I., and Martinec, J.: Snow cover mapping for
runoff simulations based on Landsat-MSS data in an alpine basin. Proc. Hydrological Applications
of Space Technology, Cocoa Beach Workshop, IAHS Pub!. No. 160, 1986, pp. 191-199
Borodulin, V. V. and Prokacheva, V. G.: Studying lake ice regimes by remote sensing methods. In:
Hydrological Applications of Remote Sensing and Remote Data Transmission. Proc. Hamburg
Symp., IAHS Pub!. No. 145, 1985, pp. 445-450
Bowley, C. J., Barnes, J. c., and Rango, A.: Satellite snow mapping and runoff prediction handbook,
NASA Technical Paper 1829, National Aeronautics and Space Administration, Washington, D.
C. 1981, 87 pp.
Braslau, D. and Bussom, D. E.: Landsat sensing of glaciers with application to mass-balance and
runoff. In: Proc. Modeling Snow Cover Runoff, S. C. Colbeck and M. Ray (eds.), Hanover, New
Hampshire: U.S. Army Cold Regions Res. and Eng. Lab 1979, pp. 77-82
A. Rango, A.E. Walker and B.E. Goodison
With technological advances in data processing and transmission, data and derived
snow and ice products from many of the current sensors are available to the hydrological community in near real-time (e.g. within 6-24 hours of satellite overpass). The
development of the Internet and World Wide Web has facilitated the availability of
many remote sensing derived snow and ice products to users right from their computers. As the technology related to data access continues to advance, the hydrological
community can expect to see an expanded variety of satellite data products available
to them for use in hydrological monitoring and modeling. When both the AM-I and
PM-I EOS platforms are launched, NASA will make a variety of snow products
available to users from MODIS (daily snow cover and 8-day composite maximum
snow cover at 500m resolution; daily climate modeling grid (CMG) snow cover and
8-day composite CMG maximum snow cover at ~o x ~o resolution) and AMSR (daily
global snow-storage index map; pentab (5-day) composite snow-storage index map).
The cost associated with satellite-derived snow and ice products will vary depending
on the data policy associated with the satellite sensor. For commercial satellite
platforms, such as Radarsat-l and 2 SAR, derived products may come with a price tag
in the thousands of dollar range, whereas products from federally funded satellite
platforms (e.g. NOAA AVHRR, DMSP SSMII) are generally available at no cost via
the Internet.
References
Adam, S., Pietroniro, A. and Brugman, M.M.: Glacier snowline mapping using ERS-\ SAR imageI)'.
Remote Sensing of Environment, 61, 46-54 (1997)
Andersen, T.: SNOWSAT-Operational snow mapping in Norway. Proc. First Moderate Resolution
Imaging Spectroradiometer (MODIS) Snow and Ice Workshop, NASA Conf. Pub!. CP-3318,
NASA/Goddard Space Flight Center, Greenbelt, MD 1995, pp. 101-102
Andersen, T.: A VHRR data for snow mapping in Norway. Proc. 5th A VHRR Data Users Meeting,
Tromsoe, Norway 1991
Armstrong, R.L. and Brodzik, M.1.: An earth-gridded SSM/I data set for cl)'ospheric studies and
global change monitoring. Advances in Space Research, 16(10), 155-163 (1995)
Armstrong, R. L., Chang, A., Rango, A., and Josberger, E.: Snow depths and grain-size relationships
with relevance for passive microwave studies. Annals of Glaciology, 17, 171-176 (1993)
Baumgartner, M. F. and Rango, A.: A microcomputer-based alpine snowcover and analysis system
(ASCAS). Photogrammetric Engineering & Remote Sensing, 61 (12), 1475-1486 (1995)
Baumgartner, M. F., Seidel, K., and Martinec, J.: Toward snowmelt runoff forecast based on multi sensor remote-sensing information, IEEE Trans. Geosci. Remote Sens. 25, 746-750 (1987)
Baumgartner, M.F., Seidel, K., Haefner, H., Itten, K.I., and Martinec, J.: Snow cover mapping for
runoff simulations based on Landsat-MSS data in an alpine basin. Proc. Hydrological Applications
of Space Technology, Cocoa Beach Workshop, IAHS Pub!. No. 160, 1986, pp. 191-199
Borodulin, V. V. and Prokacheva, V. G.: Studying lake ice regimes by remote sensing methods. In:
Hydrological Applications of Remote Sensing and Remote Data Transmission. Proc. Hamburg
Symp., IAHS Pub!. No. 145, 1985, pp. 445-450
Bowley, C. J., Barnes, J. c., and Rango, A.: Satellite snow mapping and runoff prediction handbook,
NASA Technical Paper 1829, National Aeronautics and Space Administration, Washington, D.
C. 1981, 87 pp.
Braslau, D. and Bussom, D. E.: Landsat sensing of glaciers with application to mass-balance and
runoff. In: Proc. Modeling Snow Cover Runoff, S. C. Colbeck and M. Ray (eds.), Hanover, New
Hampshire: U.S. Army Cold Regions Res. and Eng. Lab 1979, pp. 77-82