Articles | Volume 12, issue 11
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.
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
| 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
CORRESPONDING AUTHOR
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, K1A 0Y7, Canada
Christian Prevost
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, K1A 0Y7, Canada
Francis Canisius
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, K1A 0Y7, Canada
Sylvain G. Leblanc
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, K1A 0Y7, Canada
Matt Maloley
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, K1A 0Y7, Canada
Sarah Oakes
Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, K1A 0Y7, Canada
Kiyomi Holman
Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, K1N 6Y5, Canada
Anders Knudby
Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, K1N 6Y5, Canada
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Cited
27 citations as recorded by crossref.
- Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review W. Lee et al. 10.1007/s13143-023-00344-2
- Mapping Glacier Ablation With a UAV in the North Cascades: A Structure-from-Motion Approach S. Healy & A. Khan 10.3389/frsen.2021.764765
- 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
- Location Dictates Snow Aerodynamic Roughness S. Fassnacht et al. 10.3390/glacies1010001
- Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets G. Richardson et al. 10.3390/drones5030099
- Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions L. Meriö et al. 10.5194/tc-17-4363-2023
- 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
- Characterizing the spatial distribution of field-scale snowpack using unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry E. Cho et al. 10.5194/hess-29-4539-2025
- A Call for More Snow Sampling S. Fassnacht 10.3390/geosciences11110435
- Virtual snow stakes: a new method for snow depth measurement at remote camera stations K. Strickfaden et al. 10.1002/wsb.1481
- Dense neural network outperforms other machine learning models for scaling-up lichen cover maps in Eastern Canada G. Richardson et al. 10.1371/journal.pone.0292839
- A snow depth estimation method with LiDAR system in snow groomer Q. Jiao et al. 10.1016/j.coldregions.2025.104462
- Collaborative wildlife–snow science: Integrating wildlife and snow expertise to improve research and management A. Reinking et al. 10.1002/ecs2.4094
- Unmanned Aerial Vehicle-Based Structure from Motion Technique for Precise Snow Depth Retrieval—Implication for Optimal Ground Control Point Deployment Strategy S. Shu et al. 10.3390/rs15092297
- Application of Fixed-Wing UAV-Based Photogrammetry Data for Snow Depth Mapping in Alpine Conditions M. Masný et al. 10.3390/drones5040114
- 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
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Mapping snow depth and volume at the alpine watershed scale from aerial imagery using Structure from Motion J. Meyer et al. 10.3389/feart.2022.989792
- Citizen science for monitoring seasonal-scale beach erosion and behaviour with aerial drones N. Pucino et al. 10.1038/s41598-021-83477-6
- New opportunities for low-cost LiDAR-derived snow depth estimates from a consumer drone-mounted smartphone F. King et al. 10.1016/j.coldregions.2022.103757
- Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
- Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment A. Rauhala et al. 10.5194/tc-17-4343-2023
- Albedo change from snow algae blooms can contribute substantially to snow melt in the North Cascades, USA S. Healy & A. Khan 10.1038/s43247-023-00768-8
- Evaluation of LiDAR-Derived Snow Depth Estimates From the iPhone 12 Pro F. King et al. 10.1109/LGRS.2022.3166665
- Repeat mapping of snow depth across an alpine catchment with RPAS photogrammetry T. Redpath et al. 10.5194/tc-12-3477-2018
26 citations as recorded by crossref.
- Parameterizations of Snow Cover, Snow Albedo and Snow Density in Land Surface Models: A Comparative Review W. Lee et al. 10.1007/s13143-023-00344-2
- Mapping Glacier Ablation With a UAV in the North Cascades: A Structure-from-Motion Approach S. Healy & A. Khan 10.3389/frsen.2021.764765
- 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
- Location Dictates Snow Aerodynamic Roughness S. Fassnacht et al. 10.3390/glacies1010001
- Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets G. Richardson et al. 10.3390/drones5030099
- Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 2: Snow processes and snow–canopy interactions L. Meriö et al. 10.5194/tc-17-4363-2023
- 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
- Characterizing the spatial distribution of field-scale snowpack using unpiloted aerial system (UAS) lidar and structure-from-motion (SfM) photogrammetry E. Cho et al. 10.5194/hess-29-4539-2025
- A Call for More Snow Sampling S. Fassnacht 10.3390/geosciences11110435
- Virtual snow stakes: a new method for snow depth measurement at remote camera stations K. Strickfaden et al. 10.1002/wsb.1481
- Dense neural network outperforms other machine learning models for scaling-up lichen cover maps in Eastern Canada G. Richardson et al. 10.1371/journal.pone.0292839
- A snow depth estimation method with LiDAR system in snow groomer Q. Jiao et al. 10.1016/j.coldregions.2025.104462
- Collaborative wildlife–snow science: Integrating wildlife and snow expertise to improve research and management A. Reinking et al. 10.1002/ecs2.4094
- Unmanned Aerial Vehicle-Based Structure from Motion Technique for Precise Snow Depth Retrieval—Implication for Optimal Ground Control Point Deployment Strategy S. Shu et al. 10.3390/rs15092297
- Application of Fixed-Wing UAV-Based Photogrammetry Data for Snow Depth Mapping in Alpine Conditions M. Masný et al. 10.3390/drones5040114
- 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
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Mapping snow depth and volume at the alpine watershed scale from aerial imagery using Structure from Motion J. Meyer et al. 10.3389/feart.2022.989792
- Citizen science for monitoring seasonal-scale beach erosion and behaviour with aerial drones N. Pucino et al. 10.1038/s41598-021-83477-6
- New opportunities for low-cost LiDAR-derived snow depth estimates from a consumer drone-mounted smartphone F. King et al. 10.1016/j.coldregions.2022.103757
- Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
- Measuring the spatiotemporal variability in snow depth in subarctic environments using UASs – Part 1: Measurements, processing, and accuracy assessment A. Rauhala et al. 10.5194/tc-17-4343-2023
- Albedo change from snow algae blooms can contribute substantially to snow melt in the North Cascades, USA S. Healy & A. Khan 10.1038/s43247-023-00768-8
- Evaluation of LiDAR-Derived Snow Depth Estimates From the iPhone 12 Pro F. King et al. 10.1109/LGRS.2022.3166665
1 citations as recorded by crossref.
Latest update: 31 Oct 2025
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...
