Articles | Volume 12, issue 2
https://doi.org/10.5194/tc-12-627-2018
© 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-12-627-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Brief Communication: Mapping river ice using drones and structure from motion
Knut Alfredsen
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Norwegian
University of Science and Technology, 7491 Trondheim, Norway
Christian Haas
I AM HYDRO GmbH, Märtishofweg 2, 78112 St. Georgen, Germany
Jeffrey A. Tuhtan
Centre for Biorobotics, Tallinn University of Technology, Tallinn, Estonia
Peggy Zinke
Department of Civil and Environmental Engineering, Norwegian
University of Science and Technology, 7491 Trondheim, Norway
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Cited
23 citations as recorded by crossref.
- UAS remote sensing applications to abrupt cold region hazards M. Verfaillie et al. 10.3389/frsen.2023.1095275
- Studies on Three-Dimensional (3D) Accuracy Optimization and Repeatability of UAV in Complex Pit-Rim Landforms As Assisted by Oblique Imaging and RTK Positioning R. Bi et al. 10.3390/s21238109
- Assessing and Mitigating Ice-Jam Flood Hazards and Risks: A European Perspective K. Lindenschmidt et al. 10.3390/w15010076
- Estimation of River Ice Thickness in the Shisifenzi Reach of the Yellow River With Remote Sensing and Air Temperature Data B. Liu et al. 10.1109/JSTARS.2023.3285229
- Drones in urban stormwater management: a review and future perspectives W. McDonald 10.1080/1573062X.2019.1687745
- Quantifying the Effect of River Ice Surface Roughness on Sentinel-1 SAR Backscatter R. Palomaki & E. Sproles 10.3390/rs14225644
- Integrating Perspectives to Understand Lake Ice Dynamics in a Changing World S. Sharma et al. 10.1029/2020JG005799
- Evaluating the Structure from Motion Technique for Measurement of Bed Morphology in Physical Model Studies S. Karmacharya et al. 10.3390/w13070998
- Research on semantic segmentation algorithm of high latitude urban river ice based on deep transfer learning W. Zhao et al. 10.1080/01431161.2024.2360695
- Fluvial and aquatic applications of Structure from Motion photogrammetry and unmanned aerial vehicle/drone technology J. Carrivick & M. Smith 10.1002/wat2.1328
- Review of River Ice Observation and Data Analysis Technologies I. Zakharov et al. 10.3390/hydrology11080126
- Seasonal Subsurface Thaw Dynamics of an Aufeis Feature Inferred From Geophysical Methods N. Terry et al. 10.1029/2019JF005345
- Application of ‘Structure from Motion’ (SfM) technique in physical hydraulic modelling S. Kumar Karmacharya et al. 10.1088/1742-6596/1266/1/012008
- Identifying river ice on the Tibetan Plateau based on the relative difference in spectral bands H. Li et al. 10.1016/j.jhydrol.2021.126613
- ICENET: A Semantic Segmentation Deep Network for River Ice by Fusing Positional and Channel-Wise Attentive Features X. Zhang et al. 10.3390/rs12020221
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Drone Surveying of Volumetric Ice Growth in a Steep River E. Rødtang et al. 10.3389/frsen.2021.767073
- Aerial photogrammetry to characterise and numerically model an ice jam in Southern Quebec J. Duguay et al. 10.2166/nh.2023.010
- Ice roughness estimation via remotely piloted aircraft and photogrammetry J. Ehrman et al. 10.5194/tc-15-4031-2021
- Monitoring high-altitude river ice distribution at the basin scale in the northeastern Tibetan Plateau from a Landsat time-series spanning 1999–2018 H. Li et al. 10.1016/j.rse.2020.111915
- Morphosedimentary response of a fluvio-estuarine beach to interannual variability in landfast ice dynamics J. Bernier et al. 10.1016/j.geomorph.2023.108950
- Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
- Support vector machine learning applied to digital images of river ice conditions H. Kalke & M. Loewen 10.1016/j.coldregions.2018.08.014
22 citations as recorded by crossref.
- UAS remote sensing applications to abrupt cold region hazards M. Verfaillie et al. 10.3389/frsen.2023.1095275
- Studies on Three-Dimensional (3D) Accuracy Optimization and Repeatability of UAV in Complex Pit-Rim Landforms As Assisted by Oblique Imaging and RTK Positioning R. Bi et al. 10.3390/s21238109
- Assessing and Mitigating Ice-Jam Flood Hazards and Risks: A European Perspective K. Lindenschmidt et al. 10.3390/w15010076
- Estimation of River Ice Thickness in the Shisifenzi Reach of the Yellow River With Remote Sensing and Air Temperature Data B. Liu et al. 10.1109/JSTARS.2023.3285229
- Drones in urban stormwater management: a review and future perspectives W. McDonald 10.1080/1573062X.2019.1687745
- Quantifying the Effect of River Ice Surface Roughness on Sentinel-1 SAR Backscatter R. Palomaki & E. Sproles 10.3390/rs14225644
- Integrating Perspectives to Understand Lake Ice Dynamics in a Changing World S. Sharma et al. 10.1029/2020JG005799
- Evaluating the Structure from Motion Technique for Measurement of Bed Morphology in Physical Model Studies S. Karmacharya et al. 10.3390/w13070998
- Research on semantic segmentation algorithm of high latitude urban river ice based on deep transfer learning W. Zhao et al. 10.1080/01431161.2024.2360695
- Fluvial and aquatic applications of Structure from Motion photogrammetry and unmanned aerial vehicle/drone technology J. Carrivick & M. Smith 10.1002/wat2.1328
- Review of River Ice Observation and Data Analysis Technologies I. Zakharov et al. 10.3390/hydrology11080126
- Seasonal Subsurface Thaw Dynamics of an Aufeis Feature Inferred From Geophysical Methods N. Terry et al. 10.1029/2019JF005345
- Application of ‘Structure from Motion’ (SfM) technique in physical hydraulic modelling S. Kumar Karmacharya et al. 10.1088/1742-6596/1266/1/012008
- Identifying river ice on the Tibetan Plateau based on the relative difference in spectral bands H. Li et al. 10.1016/j.jhydrol.2021.126613
- ICENET: A Semantic Segmentation Deep Network for River Ice by Fusing Positional and Channel-Wise Attentive Features X. Zhang et al. 10.3390/rs12020221
- Unpiloted Aerial Vehicle Retrieval of Snow Depth Over Freshwater Lake Ice Using Structure From Motion G. Gunn et al. 10.3389/frsen.2021.675846
- Drone Surveying of Volumetric Ice Growth in a Steep River E. Rødtang et al. 10.3389/frsen.2021.767073
- Aerial photogrammetry to characterise and numerically model an ice jam in Southern Quebec J. Duguay et al. 10.2166/nh.2023.010
- Ice roughness estimation via remotely piloted aircraft and photogrammetry J. Ehrman et al. 10.5194/tc-15-4031-2021
- Monitoring high-altitude river ice distribution at the basin scale in the northeastern Tibetan Plateau from a Landsat time-series spanning 1999–2018 H. Li et al. 10.1016/j.rse.2020.111915
- Morphosedimentary response of a fluvio-estuarine beach to interannual variability in landfast ice dynamics J. Bernier et al. 10.1016/j.geomorph.2023.108950
- Applications of Unmanned Aerial Vehicles in Cryosphere: Latest Advances and Prospects C. Gaffey & A. Bhardwaj 10.3390/rs12060948
1 citations as recorded by crossref.
Latest update: 14 Dec 2024
Short summary
The formation and breakup of ice on rivers in winter may have impacts on everything from built infrastructure to river ecology. Collecting data on river ice is challenging both technically and because since access to the ice may not always be safe. Here we use a low cost drone to map river ice using aerial imagery and a photogrammetry. Through this we can assess ice volumes, ice extent and ice formation and how ice can affect processes in the river and the utilisation of rivers in winter.
The formation and breakup of ice on rivers in winter may have impacts on everything from built...