Articles | Volume 17, issue 2
https://doi.org/10.5194/tc-17-567-2023
https://doi.org/10.5194/tc-17-567-2023
Research article
 | 
08 Feb 2023
Research article |  | 08 Feb 2023

Landsat, MODIS, and VIIRS snow cover mapping algorithm performance as validated by airborne lidar datasets

Timbo Stillinger, Karl Rittger, Mark S. Raleigh, Alex Michell, Robert E. Davis, and Edward H. Bair

Viewed

Total article views: 3,470 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,329 1,055 86 3,470 123 53 75
  • HTML: 2,329
  • PDF: 1,055
  • XML: 86
  • Total: 3,470
  • Supplement: 123
  • BibTeX: 53
  • EndNote: 75
Views and downloads (calculated since 15 Aug 2022)
Cumulative views and downloads (calculated since 15 Aug 2022)

Viewed (geographical distribution)

Total article views: 3,470 (including HTML, PDF, and XML) Thereof 3,376 with geography defined and 94 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Nov 2024
Download
Short summary
Understanding global snow cover is critical for comprehending climate change and its impacts on the lives of billions of people. Satellites are the best way to monitor global snow cover, yet snow varies at a finer spatial resolution than most satellite images. We assessed subpixel snow mapping methods across a spectrum of conditions using airborne lidar. Spectral-unmixing methods outperformed older operational methods and are ready to to advance snow cover mapping at the global scale.