The Cryosphere
The Cryosphere
TC
Articles | Volume 20, issue 11
Articles | Volume 20, issue 11
https://doi.org/10.5194/tc-20-6309-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-6309-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 11
Research article
 | 
05 Nov 2026
Research article |  | 05 Nov 2026

Identifying Snow-Covered Areas from Unoccupied Aerial Systems (UAS) Visible Imagery and Lidar: A Comparison of Methods

Mahsa Moradi, Andrew G. Fleming, Adam Hunsaker, and Jennifer M. Jacobs

Viewed

Total article views: 3,490 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,545 1,736 209 3,490 589 179 180
  • HTML: 1,545
  • PDF: 1,736
  • XML: 209
  • Total: 3,490
  • Supplement: 589
  • BibTeX: 179
  • EndNote: 180
Views and downloads (calculated since 01 Oct 2025)
Cumulative views and downloads (calculated since 01 Oct 2025)

Viewed (geographical distribution)

Total article views: 3,490 (including HTML, PDF, and XML) Thereof 3,435 with geography defined and 55 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 05 Nov 2026
Download
Short summary
Visible images from unoccupied aerial systems (UAS) can be used to map snow, especially where snow is shallow and does not last long. We tested several methods for identifying snow-covered areas using UAS images collected in southern New Hampshire, USA. We found that using the full color information gives the most reliable results. We showed how UAS surveys can be planned to create accurate snow cover maps, helping track snow in changing conditions.
Read more
Share
Altmetrics
Final-revised paper
Preprint