With Contributions From:

• Main Authors: The Modis Snow, Dorothy K. Hall, Hydrological Sciences Branch, George A. Riggs, Vincent V. Salomonson, Jonathan S. Barton, Janet Y. L. Chien, Nicolo E. Digirolamo, Andrew G. Klein, Hugh W. Powell, Andrew B. Tait
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Published: 2001
• Subjects: Sea ice
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.549.7393; http://modis.gsfc.nasa.gov/data/atbd/atbd_mod10.pdf

Algorithms have been developed to map snow and ice cover (including ice on large, inland lakes), albedo, sea ice cover, and sea ice surface temperature (IST), using Earth Observation System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data. The Level-3 products will provide daily and 8-day composites of global snow and lake ice cover at 500-m resolution, and sea ice cover and ice-surface temperature (IST) at 1-km resolution. Statistics will be provided regarding the extent and persistence of snow and ice cover at each grid cell for the Level-3 products. The snow-mapping algorithm (Snowmap) employs a grouped-criteria technique using the Normalized Difference Snow Index (NDSI) and other spectral threshold tests to identify and classify snow on a pixel-by-pixel basis, and to map snow cover in dense forests. The usefulness of the NDSI is based on the fact that snow and ice are considerably more reflective in the visible than in the short-wave IR part of the spectrum, and the reflectance of most clouds remains high in the short-wave IR, while the reflectance of snow is low.