Articles | Volume 15, issue 3
https://doi.org/10.5194/tc-15-1485-2021
© Author(s) 2021. 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-15-1485-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Snow depth mapping with unpiloted aerial system lidar observations: a case study in Durham, New Hampshire, United States
Jennifer M. Jacobs
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, University of New
Hampshire, Durham, NH 03824, USA
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Adam G. Hunsaker
Department of Civil and Environmental Engineering, University of New
Hampshire, Durham, NH 03824, USA
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Franklin B. Sullivan
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Michael Palace
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Department of Earth Sciences, University of New Hampshire, Durham, NH
03824, USA
Elizabeth A. Burakowski
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Christina Herrick
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Eunsang Cho
Department of Civil and Environmental Engineering, University of New
Hampshire, Durham, NH 03824, USA
Earth Systems Research Center, Institute for the Study of Earth,
Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
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- Drone-based ground-penetrating radar (GPR) application to snow hydrology E. Valence et al. 10.5194/tc-16-3843-2022
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- Impact of Forest Canopy Closure on Snow Processes in the Changbai Mountains, Northeast China Y. Gao et al. 10.3389/fenvs.2022.929309
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- Applicability of alpine snow depth estimation based on multitemporal UAV-LiDAR data: A case study in the Maxian Mountains, Northwest China T. Feng et al. 10.1016/j.jhydrol.2022.129006
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- Snow depth estimation at country-scale with high spatial and temporal resolution R. Daudt et al. 10.1016/j.isprsjprs.2023.01.017
- Exploring snow distribution dynamics in steep forested slopes with UAV-borne LiDAR K. Koutantou et al. 10.1016/j.coldregions.2022.103587
- Evaluating the Effects of UAS Flight Speed on Lidar Snow Depth Estimation in a Heterogeneous Landscape F. Sullivan et al. 10.3390/rs15215091
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- UAS remote sensing applications to abrupt cold region hazards M. Verfaillie et al. 10.3389/frsen.2023.1095275
- Marginal snowpacks: The basis for a global definition and existing research needs J. López-Moreno et al. 10.1016/j.earscirev.2024.104751
- Factors Influencing the Accuracy of Shallow Snow Depth Measured Using UAV-Based Photogrammetry S. Lee et al. 10.3390/rs13040828
30 citations as recorded by crossref.
- Composite Ski-Resort Registration Method Based on Laser Point Cloud Information W. Wang et al. 10.3390/machines10050405
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Unmanned Aerial Vehicles in Hydrology and Water Management: Applications, Challenges, and Perspectives B. Acharya et al. 10.1029/2021WR029925
- A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests V. Dharmadasa et al. 10.1016/j.coldregions.2024.104134
- Bayesian physical–statistical retrieval of snow water equivalent and snow depth from X- and Ku-band synthetic aperture radar – demonstration using airborne SnowSAr in SnowEx'17 S. Singh et al. 10.5194/tc-18-747-2024
- Combining Daily Sensor Observations and Spatial LiDAR Data for Mapping Snow Water Equivalent in a Sub‐Alpine Forest J. Geissler et al. 10.1029/2023WR034460
- Impact of distributed meteorological forcing on simulated snow cover and hydrological fluxes over a mid-elevation alpine micro-scale catchment A. Gupta et al. 10.5194/hess-27-191-2023
- Spatially continuous snow depth mapping by aeroplane photogrammetry for annual peak of winter from 2017 to 2021 in open areas L. Bührle et al. 10.5194/tc-17-3383-2023
- Drone-based ground-penetrating radar (GPR) application to snow hydrology E. Valence et al. 10.5194/tc-16-3843-2022
- Understanding wind-driven melt of patchy snow cover L. van der Valk et al. 10.5194/tc-16-4319-2022
- Development and Testing of a UAV Laser Scanner and Multispectral Camera System for Eco-Geomorphic Applications C. Tomsett & J. Leyland 10.3390/s21227719
- UAV hyperspectral imaging for multiscale assessment of Landsat 9 snow grain size and albedo S. Skiles et al. 10.3389/frsen.2022.1038287
- Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation K. Maier et al. 10.1016/j.isprsjprs.2022.01.020
- 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
- Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar V. Dharmadasa et al. 10.5194/tc-17-1225-2023
- Meteorological control on snow depth evolution and snowpack energy exchanges in an agro-forested environment by a measurement-based approach: A case study in Sainte-Marthe, Eastern Canada V. Dharmadasa et al. 10.1016/j.agrformet.2024.109915
- Impact of Forest Canopy Closure on Snow Processes in the Changbai Mountains, Northeast China Y. Gao et al. 10.3389/fenvs.2022.929309
- Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar E. Cho et al. 10.1016/j.jhydrol.2021.126722
- Tree canopy and snow depth relationships at fine scales with terrestrial laser scanning A. Hojatimalekshah et al. 10.5194/tc-15-2187-2021
- An Accuracy Assessment of Snow Depth Measurements in Agro-Forested Environments by UAV Lidar V. Dharmadasa et al. 10.3390/rs14071649
- 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
- Applicability of alpine snow depth estimation based on multitemporal UAV-LiDAR data: A case study in the Maxian Mountains, Northwest China T. Feng et al. 10.1016/j.jhydrol.2022.129006
- Comparing Three Freeze-Thaw Schemes Using C-Band Radar Data in Southeastern New Hampshire, USA M. Moradi et al. 10.3390/rs16152784
- Assessing UAV-based laser scanning for monitoring glacial processes and interactions at high spatial and temporal resolutions N. Baurley et al. 10.3389/frsen.2022.1027065
- Snow depth estimation at country-scale with high spatial and temporal resolution R. Daudt et al. 10.1016/j.isprsjprs.2023.01.017
- Exploring snow distribution dynamics in steep forested slopes with UAV-borne LiDAR K. Koutantou et al. 10.1016/j.coldregions.2022.103587
- Evaluating the Effects of UAS Flight Speed on Lidar Snow Depth Estimation in a Heterogeneous Landscape F. Sullivan et al. 10.3390/rs15215091
- Measuring prairie snow water equivalent with combined UAV-borne gamma spectrometry and lidar P. Harder et al. 10.5194/tc-18-3277-2024
- UAS remote sensing applications to abrupt cold region hazards M. Verfaillie et al. 10.3389/frsen.2023.1095275
- Marginal snowpacks: The basis for a global definition and existing research needs J. López-Moreno et al. 10.1016/j.earscirev.2024.104751
1 citations as recorded by crossref.
Latest update: 20 Nov 2024
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.
This pilot study describes a proof of concept for using lidar on an unpiloted aerial vehicle to...