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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Nov 2026
Research article |
| 05 Nov 2026
| 05 Nov 2026
Identifying Snow-Covered Areas from Unoccupied Aerial Systems (UAS) Visible Imagery and Lidar: A Comparison of Methods
Mahsa Moradi
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH, USA
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
Andrew G. Fleming
Department of Earth & Environment, Boston University, Boston, MA, USA
Adam Hunsaker
Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH, USA
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
Jennifer M. Jacobs
Department of Civil and Environmental Engineering, University of New Hampshire, Durham, NH, USA
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
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While land surface models are a common approach for estimating macroscale snow water equivalent (SWE), the SWE accuracy is often limited by uncertainties in model physics and forcing inputs. In this study, we found large underestimations of modeled SWE compared to observations. Precipitation forcings and melting physics limitations dominantly contribute to the SWE underestimations. Results provide insights into prioritizing strategies to improve the SWE simulations for hydrologic applications.
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Manuscript not accepted for further review
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This study compares snow depth measurements from two manual instruments and an airborne platform in a field and forest. The manual instruments’ snow depths differed by 1 to 3 cm. The airborne measurements , which do not penetrate the leaf litter, were consistently shallower than either manual instrument. When combining airborne snow depth maps with manual density measurements, corrections may be required to create unbiased maps of snow properties.
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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.
Visible images from unoccupied aerial systems (UAS) can be used to map snow, especially where...
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