DEVELOPMENT OF METHODS FOR MAPPING GLOBAL SNOW COVER USING MODERATE RESOLUTION IMAGING SPECTRORADIOMETER DATA

An algorithm is being developed to map global snow cover using Earth O bserving System (EOS) Moderate Resolution Imaging Spectroradiometer (M ODIS) data beginning at launch in 1998. As currently planned, digital maps will be produced that will provide daily, and perhaps maximum wee kly, global snow cover at 500-m spatial resolution. Statistics will be generated on the extent and persistence of snow cover in each pixel f or each weekly map, cloud cover permitting. It will also be possible t o generate snow-cover maps at 250-m spatial resolution using MODIS dat a, and to study snow-cover characteristics. Preliminary validation act ivities 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 pr eviously mapped Landsat Thematic Mapper (TM) scene of the Sierra Nevad as 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 SN OMAP classification with a Supervised-classification technique on. six other TM scenes show that SNOMAP and supervised-classification techni ques agree to within about 11% or less for nearly cloud-free scenes an d that SNOMAP provided more consistent results. About 10% of the snow cover known to be present on the 14 March 1991 TM scene covering Glaci er National Park in northern Montana, is obscured by dense forest cove r. 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 a nd tested before and following the launch of MODIS.