{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T13:52:54Z","timestamp":1778853174347,"version":"3.51.4"},"reference-count":63,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2014,12,11]],"date-time":"2014-12-11T00:00:00Z","timestamp":1418256000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing of snow-covered area (SCA) can be binary (indicating the presence\/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013\u2013August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%\u201393% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%\u2013100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%\u201398% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring\/summer transition from snow-covered to snow-free conditions lasted 17\u201356 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.<\/jats:p>","DOI":"10.3390\/rs61212478","type":"journal-article","created":{"date-parts":[[2014,12,11]],"date-time":"2014-12-11T10:53:38Z","timestamp":1418295218000},"page":"12478-12508","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Prevalence of Pure Versus Mixed Snow Cover Pixels across Spatial Resolutions in Alpine Environments"],"prefix":"10.3390","volume":"6","author":[{"given":"David","family":"Selkowitz","sequence":"first","affiliation":[{"name":"US Geological Survey, Alaska Science Center, 4210 University Drive, Anchorage, AK 99508, USA"},{"name":"Department of Geography, University of Utah, 260 S. Central Campus Dr., Room 270, Salt Lake City, UT 84112\u20139155, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Forster","sequence":"additional","affiliation":[{"name":"Department of Geography, University of Utah, 260 S. Central Campus Dr., Room 270, Salt Lake City, UT 84112\u20139155, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Megan","family":"Caldwell","sequence":"additional","affiliation":[{"name":"US Geological Survey, Geosciences and Environmental Change Science Center, P.O. Box 25046, DFC, MS 980, Denver, CO 80225, USA"},{"name":"Department of Ecology and Evolutionary Biology, University of Colorado, Campus Box 334, Boulder, CO 80339\u20130334, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,12,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1029\/97WR03755","article-title":"Estimating the spatial distribution of snow in mountain basins using remote sensing and energy balance modeling","volume":"34","author":"Cline","year":"1998","journal-title":"Water Resour. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1016\/j.rse.2007.08.010","article-title":"Merging complementary remote sensing datasets in the context of snow water equivalent reconstruction","volume":"112","author":"Durand","year":"2008","journal-title":"Remote Sens. 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