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*Coming soon in 2018*

The U.S. Geological Survey (USGS) will soon make available Landsat Level- 3 Fractional Snow Covered Area data for Landsat 4-5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) that are consistently processed to the highest scientific standards and level of processing required for direct use in monitoring and assessing landscape change.

The Landsat Fractional Snow Covered Area product indicates the percentage of a pixel covered by snow. The Landsat Fractional Snow Covered Area product is generated from U.S. Landsat Analysis Ready Data (ARD) Surface Reflectance data.

The Landsat Fractional Snow Covered Area product is 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 Fractional Snow Covered Area will become available for the Western U.S. and Alaska for the following date ranges:

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

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

 

Package Content

The Landsat Fractional Snow Covered Area product indicates the percentage of a pixel covered by snow.  Additional product specifications can be found in the Landsat Fractional Snow Covered Area Product Guide. The Fractional Snow Covered Area package includes a metadata file in Extensible Markup Language (.xml) format.

The table below lists the products and filenames that are delivered with the Landsat Fractional Snow Covered Area product.

Product

Description

Delivered File Name

Approximate File Size (Kbytes)

Fractional Snow Covered Area (SNOW)

Indicates the percentage of the pixel covered by snow

*_SNOW.tif

3,876

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 DSWE product.

*_REVCM.tif

292

 

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.
  • A Quality Assessment process is applied to the Fractional Snow Covered Area product prior to public release, which includes visually assessing each scene-level Fractional Snow Covered Area product for excessive commission errors caused by factors such as incorrect cloud masks or poor georeferencing. Therefore, while the majority of Landsat scenes are used to generate the Fractional Snow Covered Area product, certain scenes may not be able to be processed to produce a scientifically viable Fractional Snow Covered Area product.
  • Efficacy of the SR correction is likely to be reduced in areas where atmospheric correction is affected by adverse conditions: a. Hyper-arid or snow-covered regions b. Low sun angle conditions c. Coastal regions where land area is small relative to adjacent water d. Areas with extensive cloud contamination e. Users are cautioned against correcting data acquired over high latitudes (> 65º) Refer to the SR Quality Assessment (QA) bands for pixel-level condition and validity flags.
  • The fSCA algorithm tends to flag water boundaries 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 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.

 

Data Access

Landsat Fractional Snow Covered Area will be available for download from EarthExplorerThe data will be located under the Landsat category, Landsat Collection 1 Level-3 Science Products subcategory, and listed as Fractional Snow Covered Area.

 

Documentation

Landsat Fractional Snow Covered Area Product Guide

Landsat Fractional Snow Covered Area Algorithm Description Document

List of 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 (fSCA) Science Products courtesy of the U.S. Geological Survey.

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

 

References

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.