Articles | Volume 29, issue 18
https://doi.org/10.5194/hess-29-4539-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-4539-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2025
Research article |
| 22 Sep 2025
| 22 Sep 2025
Characterizing the spatial distribution of field-scale snowpack using unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry
Ingram School of Engineering, Texas State University, San Marcos, TX, USA
Megan Verfaillie
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
Adam G. Hunsaker
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
Franklin B. Sullivan
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
Michael Palace
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
Department of Earth Sciences, University of New Hampshire, Durham, NH, USA
Cameron Wagner
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
present address: U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, NH, USA
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Manuscript not accepted for further review
Short summary
Short summary
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
Short summary
This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to map shallow snowpack (< 20 cm) depth in open terrain and forests. The 1 m2 resolution snow depth map, generated by subtracting snow-off from snow-on lidar-derived digital terrain models, consistently had 0.5 to 1 cm precision in the field, with a considerable reduction in accuracy in the forest. Performance depends on the point cloud density and the ground surface variability and vegetation.
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Short summary
Unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry effectively map high-resolution snow depths. Our study found that UAS lidar outperformed SfM, particularly in capturing stable snow distribution patterns. Vegetation type was the primary factor influencing snow depth across forest and field areas, reflecting soil variables, such as organic matter. When analyzed separately, slope and forest canopy shadowing played key roles.
Unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry effectively...
