Articles | Volume 12, issue 11
The Cryosphere, 12, 3535–3550, 2018
https://doi.org/10.5194/tc-12-3535-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The Cryosphere, 12, 3535–3550, 2018
https://doi.org/10.5194/tc-12-3535-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 13 Nov 2018
Research article | 13 Nov 2018
Monitoring snow depth change across a range of landscapes with ephemeral snowpacks using structure from motion applied to lightweight unmanned aerial vehicle videos
Richard Fernandes et al.
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Cited
11 citations as recorded by crossref.
- Deriving Land and Water Surface Elevations in the Northeastern Yucatán Peninsula Using PPK GPS and UAV-Based Structure from Motion T. Pingel et al. 10.1080/23754931.2021.1871937
- Assessing the Ability of Structure From Motion to Map High‐Resolution Snow Surface Elevations in Complex Terrain: A Case Study From Senator Beck Basin, CO J. Meyer & S. Skiles 10.1029/2018WR024518
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets G. Richardson et al. 10.3390/drones5030099
- Citizen science for monitoring seasonal-scale beach erosion and behaviour with aerial drones N. Pucino et al. 10.1038/s41598-021-83477-6
- Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
- Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States J. Jacobs et al. 10.5194/tc-15-1485-2021
- Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain J. Revuelto et al. 10.1016/j.coldregions.2021.103344
- Estimating Snow Depth and Leaf Area Index Based on UAV Digital Photogrammetry T. Lendzioch et al. 10.3390/s19051027
- Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area J. Goetz & A. Brenning 10.1029/2019WR025251
- Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry T. Redpath et al. 10.5194/tc-12-3477-2018
10 citations as recorded by crossref.
- Deriving Land and Water Surface Elevations in the Northeastern Yucatán Peninsula Using PPK GPS and UAV-Based Structure from Motion T. Pingel et al. 10.1080/23754931.2021.1871937
- Assessing the Ability of Structure From Motion to Map High‐Resolution Snow Surface Elevations in Complex Terrain: A Case Study From Senator Beck Basin, CO J. Meyer & S. Skiles 10.1029/2018WR024518
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets G. Richardson et al. 10.3390/drones5030099
- Citizen science for monitoring seasonal-scale beach erosion and behaviour with aerial drones N. Pucino et al. 10.1038/s41598-021-83477-6
- Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
- Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States J. Jacobs et al. 10.5194/tc-15-1485-2021
- Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain J. Revuelto et al. 10.1016/j.coldregions.2021.103344
- Estimating Snow Depth and Leaf Area Index Based on UAV Digital Photogrammetry T. Lendzioch et al. 10.3390/s19051027
- Quantifying Uncertainties in Snow Depth Mapping From Structure From Motion Photogrammetry in an Alpine Area J. Goetz & A. Brenning 10.1029/2019WR025251
1 citations as recorded by crossref.
Latest update: 17 Oct 2021
Short summary
The use of lightweight UAV-based surveys of surface elevation to map snow depth and weekly snow depth change was evaluated over five study areas spanning a range of topography and vegetation cover. Snow depth was estimated with an accuracy of better than 10 cm in the vertical and 3 cm in the horizontal. Vegetation in the snow-free elevation map was a major source of error. As a result, the snow depth change between two dates with snow cover was estimated with an accuracy of better than 4 cm.
The use of lightweight UAV-based surveys of surface elevation to map snow depth and weekly snow...
