Articles | Volume 15, issue 3
The Cryosphere, 15, 1485–1500, 2021
The Cryosphere, 15, 1485–1500, 2021

Research article 24 Mar 2021

Research article | 24 Mar 2021

Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States

Jennifer M. Jacobs et al.

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Cited articles

Adams, M. S., Bühler, Y., and Fromm, R.: Multitemporal accuracy and precision assessment of unmanned aerial system photogrammetry for slope-scale snow depth maps in Alpine terrain, Pure Appl. Geophys., 175, 3303–3324, 2018. 
Broxton, P., Harpold, A., Biederman, J., Troch, P. A., Molotch, N., and Brooks, P.: Quantifying the effects of vegetation structure on snow accumulation and ablation in mixed-conifer forests, Ecohydrology, 8, 1073–1094, 2015. 
Broxton, P. D., van Leeuwen, W. J., and Biederman, J. A.: Improving Snow Water Equivalent Maps With Machine Learning of Snow Survey and Lidar Measurements, Water Resour. Res., 55, 3739–3757,, 2019. 
Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075–1088,, 2016. 
Bühler, Y., Adams, M. S., Stoffel, A., and Boesch, R.: Photogrammetric reconstruction of homogenous snow surfaces in alpine terrain applying near-infrared UAS imagery, Int. J. Remote Sens., 38, 3135–3158, 2017. 
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.