HALL, DK, RIGGS, GA, SALOMONSON, VV (1995). DEVELOPMENT OF METHODS FOR MAPPING GLOBAL SNOW COVER USING MODERATE RESOLUTION IMAGING SPECTRORADIOMETER DATA. REMOTE SENSING OF ENVIRONMENT, 54(2), 127-140.
An algorithm is being developed to map global snow cover using Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning at launch in 1998. As currently planned, digital maps will be produced that will provide daily, and perhaps maximum weekly, global snow cover at 500-m spatial resolution. Statistics will be generated on the extent and persistence of snow cover in each pixel for each weekly map, cloud cover permitting. It will also be possible to generate snow-cover maps at 250-m spatial resolution using MODIS data, and to study snow-cover characteristics. Preliminary validation activities of the prototype version of our snow-mapping algorithm, SNOMAP, have been undertaken. SNOMAP will use criteria tests and a decision rule to identify snow in each 500-m MODIS pixel. Use of SNOMAP on a previously mapped Landsat Thematic Mapper (TM) scene of the Sierra Nevadas has shown that SNOMAP is 98% accurate in identifying snow in pixels that are snow covered by 60% or more. Results of a comparison of a SNOMAP classification with a Supervised-classification technique on. six other TM scenes show that SNOMAP and supervised-classification techniques agree to within about 11% or less for nearly cloud-free scenes and that SNOMAP provided more consistent results. About 10% of the snow cover known to be present on the 14 March 1991 TM scene covering Glacier National Park in northern Montana, is obscured by dense forest cover. Mapping snow cover in areas of dense forests is a limitation in the use of this procedure for global snow-cover mapping. This limitation, and sources of error will be assessed globally as SNOMAP is refined and tested before and following the launch of MODIS.