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Landsat Collection 1 Level-3 Fractional Snow Covered Area Science Product

The Landsat Collection 1 Fractional Snow Covered Area product provides per-pixel fractional snow cover maps that indicate the percentage of a pixel covered by snow for Landsat 4-8 data.

Return to Landsat Fractional Snow Covered Area Products Overview


Landsat Fractional Snow Cover Area Example
Left: Landsat Collection 1 Surface Reflectance (Landsat 8 bands 4,3,2) and Right: Collection 1 Fractional Snow Covered Area for an area within Landsat CONUS ARD h003v007 acquired on  April 27, 2017. Snow covered areas are displayed in white.

Snow cover is spatially and temporally variable and is often concentrated in remote or inaccessible land regions making spaceborne remote sensing the most feasible approach to measure and monitor snow cover change. Landsat’s spatial resolution offers the capability to resolve snow cover patterns across topographically complex mountainous regions.

While Landsat’s acquisition frequency limits analysis of short-term snow cover variations, longer term changes in snow cover duration and persistence can be detected.The Landsat Collection 1 (C1) Fractional Snow Covered Area (fSCA) product provides per-pixel fractional snow cover maps that indicate the percentage of a pixel covered by snow for Landsat 4-8 data.

Available for Landsat 4-5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) data, the C1 fSCA products are generated from Landsat Collection 1 U.S. Analysis Ready Data (ARD) Surface Reflectance and Top of Atmosphere Reflectance data.

Landsat C1 fSCA products are processed to 30-meter spatial resolution in Albers Equal Area (AEA) projection using the World Geodetic System 1984 (WGS84) datum and gridded to a common tiling scheme.

Product Availability

Landsat C1 fSCA products are available for the Western U.S. and Alaska for the following date ranges:

  • Landsat 8 OLI: April 2013 to December 31, 2021*
  • Landsat 7 ETM+: July 1999 to 2017
  • Landsat 5 TM: March 1984 to May 2012
  • Landsat 4 TM: March 1984 to December 1993

*As of January 1, 2022, newly-acquired Landsat data are processed into Landsat Collection 2 only. 

Package Content

The Landsat C2 fSCA product contains an acquisition-based per-pixel snow cover fraction, an acquisition-based revised cloud mask for quality assessment, and a product metadata file. Additional product specifications can be found in the Landsat Collection 1 Fractional Snow Covered Area Product Guide.

The list below describes the products and filenames that are delivered with the Landsat C1 fSCA product.

Fractional Snow Covered Area (SNOW): Indicates the percentage of the pixel covered by snow
Delivered file name: *_SNOW.tif
Approximate file size: 3.8 MB

Revised Cloud Mask (REVCM): Flags pixels identified as clear, cloud, water, and fill  (based on C Function of Mask (CFMask)). This revised mask more accurately differentiates between snow and cloud, compared to the original CFMask. The water component of this mask is produced using the Landsat Level-3 Dynamic Surface Water Extent (DSWE) product.
Delivered file name: *_REVCM.tif
Approximate file size: 290 KB

Caveats and Constraints

  • The scale factor in the Extensible Markup Language (.xml) file for the SNOW band is incorrect. The scale factor should be 0.001 instead of the current 0.0001 shown in the .xml file. The valid range for these fractions when unscaled should be between 0.0 and 1.0.
  • C1 fSCA products are derived from available Landsat Collection 1 U.S. ARD SR products. SR products are generated using two algorithms, the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) for Landsat 4-7 and the Landsat Surface Reflectance Code (LaSRC) for Landsat 8. Occasionally, Landsat data cannot be processed to SR due to missing auxiliary data. More information pertaining to the auxiliary data characteristics is available from the LEDAPS and LaSRC Product Guides. Date ranges of missing auxiliary data are listed under “Caveats and Constraints” on the Landsat Surface Reflectance webpage.
  • The C1 fSCA algorithm tends to flag water boundaries and dark water pixels as false-positives. The Revised Cloud Mask is designed to use the Landsat DSWE product to alleviate many of these false-positives. However, the initial version of the fSCA product for ARD tiles does not have access to the DSWE product because it was not available for ARD tiles during processing.
  • The C1 fSCA algorithm uses National Land Cover Database (NLCD) canopy cover and land cover products for canopy adjustment to address canopy covered areas of snow. If the NLCD canopy cover or land cover products are not accurate for a particular area due to fire, logging, urbanization, etc., the canopy-adjusted results may have issues with accuracy.
  • The valid range and class values in the XML file for the revised cloud mask (REVCM) band are missing the information about pixel value of 4. This pixel value indicates deeply shadowed pixels and was added to capture the snow in dark areas of the glaciers. In most cases the shadowing is due to terrain but could also be due to clouds. Due to unavailability of the DSWE Science Product at the time of fSCA processing, the dark water pixels may also be flagged as terrain shadowing. The information about possible pixel values of the REVCM band and their interpretations are provided in the Landsat Collection 1 Fractional Snow Covered Area Product Guide.

User Communities

Landsat Fractional Snow Covered Area User Communities

Community Potential Use
Colorado State University Western U.S. snowpack
Various conference connections Planning and mangement of fire occurence or managed lands
Landsat science Reference for other Landsat Science Products

Data Access

Landsat Collection 1 fSCA product is available for download from EarthExplorerThe data are located under the Landsat category, Landsat Collection 1 Level-3 subcategory, and listed as Fractional Snow Covered Area.

Visit the Landsat Data Access webpage for information about bulk download options.  


Landsat Collection 1 Fractional Snow Covered Area Product Guide

Landsat Collection 1 Fractional Snow Covered Area Algorithm Description Document (ADD)

Landsat Collection 1 Fractional Snow Covered Area Digital Object Identifier (DOI):

List of Landsat Collection 1 Fractional Snow Covered Area ARD tiles

Citation Information

There are no restrictions on the use of Landsat Science Products. It is not a requirement of data use, but the following citation may be used in publication or presentation materials to acknowledge the USGS as a data source and to credit the original research.

Landsat Level 3 Fractional Snow Covered Area Science Product courtesy of the U.S. Geological Survey.

The Fractional Snow Covered Area product is based directly on work described in:

Painter, T. H., Rittger, K., McKenzie, C., Slaughter, P., Davis, R. E., & Dozier, J., 2009. Retrieval of subpixel snow covered area, grain size, and albedo from MODIS. Remote Sensing of Environment, 113(4), 868-879.

Selkowitz, D.J., Painter, T.H., Rittger, K.E., Schmidt, G., & Forster, R., 2017. "The USGS Landsat Snow Covered Area Products: Methods and Preliminary Validation." Automated Approaches for Snow and Ice Cover Monitoring Using Optical Remote Sensing. D. Selkowitz. Salt Lake City, UT: The University of Utah. pp. 76-119. Available online:


Selkowitz, D. J., & Forster, R. R., 2016. Automated mapping of persistent ice and snow cover across the western U.S. with Landsat. ISPRS Journal of Photogrammetry and Remote Sensing, 117, 126-140. DOI: 10.1016/j.isprsjprs.2016.04.001

Selkowitz, D.J, Painter, T., Schmidt, G., Rittger, K., and Forster, R., 2015, The USGS Landsat Snow Covered Area Science Data Product [poster], in Fall Meeting, San Francisco, Calif., 14-18 December 2015, Fall Meeting Abstracts: Washington, D.C., American Geophysical Union, abstract number C41D-0759.

Selkowitz, David. 2011. Landsat-derived Patterns of Snow Covered Area (SCA) and the Potential for Enhancing the Spatial Resolution of MODIS-derived SCA Estimates. AGU Fall Meeting Abstracts 05.