Articles | Volume 16, issue 1
https://doi.org/10.5194/tc-16-159-2022
© Author(s) 2022. 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-16-159-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Sentinel-1 snow depth retrieval at sub-kilometer resolution over the European Alps
Hans Lievens
CORRESPONDING AUTHOR
Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
Isis Brangers
Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
Hans-Peter Marshall
Department of Geosciences, Boise State University, Boise, ID, USA
Tobias Jonas
WSL – Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Marc Olefs
ZAMG – Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
Gabriëlle De Lannoy
Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
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- A long-term daily gridded snow depth dataset for the Northern Hemisphere from 1980 to 2019 based on machine learning Y. Hu et al. 10.1080/20964471.2023.2177435
- Snow depth retrieval method for PolSAR data using multi-parameters snow backscattering model H. Qiao et al. 10.1016/j.isprsjprs.2024.09.005
- A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks M. Guidicelli et al. 10.1016/j.hydroa.2024.100190
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- Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements Y. Hu et al. 10.3389/frsen.2022.855159
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- Forest Snow Depth Estimation Based on Optimized Features and DNN Network Using C-Band SAR Data G. Yu et al. 10.1109/LGRS.2024.3379202
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- A Synthetic Aperture Radar Based Method for Long Term Monitoring of Seasonal Snowmelt and Wintertime Rain-On-Snow Events in Svalbard H. Vickers et al. 10.3389/feart.2022.868945
- Potential of the Bi-Static SAR Satellite Companion Mission Harmony for Land-Ice Observations A. Kääb et al. 10.3390/rs16162918
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- Spatial Dispersion and Non-Negative Matrix Factorization of SAR Backscattering as Tools for Monitoring Snow Depth Evolution in Mountain Areas: A Case Study at Central Pyrenees (Spain) A. Amoruso et al. 10.3390/rs14030653
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
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- GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient A. Capelli et al. 10.5194/tc-16-505-2022
- METHOD AND ACCURACY OF ESTIMATING SNOW DEPTH USING SENTINEL-1 SAR DATA IN GUNMA PREFECTURE IN JAPAN H. ABO et al. 10.2208/jscejj.22-00345
61 citations as recorded by crossref.
- Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites Z. Hoppinen et al. 10.5194/tc-18-5407-2024
- Comparison of Machine Learning-Based Snow Depth Estimates and Development of a New Operational Retrieval Algorithm over China J. Yang et al. 10.3390/rs14122800
- Snow detection in alpine regions with Convolutional Neural Networks: discriminating snow from cold clouds and water body Y. Lu et al. 10.1080/15481603.2022.2112391
- Investigation of Environmental Effects on Coherence Loss in SAR Interferometry for Snow Water Equivalent Retrieval J. Ruiz et al. 10.1109/TGRS.2022.3223760
- Comparison of Three Different Random Forest Approaches to Retrieve Daily High-Resolution Snow Cover Maps from MODIS and Sentinel-2 in a Mountain Area, Gran Paradiso National Park (NW Alps) C. Richiardi et al. 10.3390/rs15020343
- Evaluating L-band InSAR snow water equivalent retrievals with repeat ground-penetrating radar and terrestrial lidar surveys in northern Colorado R. Bonnell et al. 10.5194/tc-18-3765-2024
- Marginal snowpacks: The basis for a global definition and existing research needs J. López-Moreno et al. 10.1016/j.earscirev.2024.104751
- A long-term daily gridded snow depth dataset for the Northern Hemisphere from 1980 to 2019 based on machine learning Y. Hu et al. 10.1080/20964471.2023.2177435
- Snow depth retrieval method for PolSAR data using multi-parameters snow backscattering model H. Qiao et al. 10.1016/j.isprsjprs.2024.09.005
- A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks M. Guidicelli et al. 10.1016/j.hydroa.2024.100190
- Exploring the use of multi-source high-resolution satellite data for snow water equivalent reconstruction over mountainous catchments V. Premier et al. 10.5194/tc-17-2387-2023
- High‐resolution snow depth prediction using Random Forest algorithm with topographic parameters: A case study in the Greiner watershed, Nunavut J. Meloche et al. 10.1002/hyp.14546
- Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements Y. Hu et al. 10.3389/frsen.2022.855159
- Tower-based C-band radar measurements of an alpine snowpack I. Brangers et al. 10.5194/tc-18-3177-2024
- Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing L. Tsang et al. 10.5194/tc-16-3531-2022
- Snowpack relative permittivity and density derived from near‐coincident lidar and ground‐penetrating radar R. Bonnell et al. 10.1002/hyp.14996
- Constraining Mountain Streamflow Constituents by Integrating Citizen Scientist Acquired Geochemical Samples and Sentinel‐1 SAR Wet Snow Time‐Series for the Shimshal Catchment in the Karakoram Mountains of Pakistan J. Lund et al. 10.1029/2022WR032171
- Multifeature GNSS-R Snow Depth Retrieval Using GA-BP Neural Network W. Liu et al. 10.1109/LGRS.2023.3291404
- Snow accumulation, albedo and melt patterns following road construction on permafrost, Inuvik–Tuktoyaktuk Highway, Canada J. Hammar et al. 10.5194/tc-17-5357-2023
- Assessment of L-band InSAR snow estimation techniques over a shallow, heterogeneous prairie snowpack R. Palomaki & E. Sproles 10.1016/j.rse.2023.113744
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- Deriving Snow Depth From ICESat-2 Lidar Multiple Scattering Measurements: Uncertainty Analyses X. Lu et al. 10.3389/frsen.2022.891481
- Reanalyzing the spatial representativeness of snow depth at automated monitoring stations using airborne lidar data J. Herbert et al. 10.5194/tc-18-3495-2024
- Passive Microwave Remote Sensing of Snow Depth: Techniques, Challenges and Future Directions S. Tanniru & R. Ramsankaran 10.3390/rs15041052
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- Snow depth retrieval from microwave remote sensing by combining wavelet transform and machine learning models in Northern Xinjiang, China H. Hou et al. 10.1117/1.JRS.18.024517
- Forest Snow Depth Estimation Based on Optimized Features and DNN Network Using C-Band SAR Data G. Yu et al. 10.1109/LGRS.2024.3379202
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- Estimating snow depth based on dual polarimetric radar index from Sentinel-1 GRD data: A case study in the Scandinavian Mountains T. Feng et al. 10.1016/j.jag.2024.103873
- Capability assessment of Sentinel-1 data for estimation of snow hydrological potential in the Khanabad watershed in the Hindu Kush Himalayas of Afghanistan A. Mahmoodzada et al. 10.1016/j.rsase.2022.100758
- Operational snow-hydrological modeling for Switzerland R. Mott et al. 10.3389/feart.2023.1228158
- 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
- Sentinel-1 time series for mapping snow cover depletion and timing of snowmelt in Arctic periglacial environments: case study from Zackenberg and Kobbefjord, Greenland S. Buchelt et al. 10.5194/tc-16-625-2022
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- A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. 10.3389/fsci.2023.1190191
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- Estimating high-resolution snow depth over the North Hemisphere mountains utilizing active microwave backscatter and machine learning Z. Ni et al. 10.1016/j.jhydrol.2024.132203
- A machine learning approach for estimating snow depth across the European Alps from Sentinel-1 imagery D. Dunmire et al. 10.1016/j.rse.2024.114369
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- Potential of the Bi-Static SAR Satellite Companion Mission Harmony for Land-Ice Observations A. Kääb et al. 10.3390/rs16162918
- Airborne Multichannel UWB FMCW Radar for Snow Depth Measurements S. Kolpuke et al. 10.1109/TGRS.2024.3359125
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- Spatial Dispersion and Non-Negative Matrix Factorization of SAR Backscattering as Tools for Monitoring Snow Depth Evolution in Mountain Areas: A Case Study at Central Pyrenees (Spain) A. Amoruso et al. 10.3390/rs14030653
- Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication G. De Lannoy et al. 10.3389/frwa.2022.981745
- Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR) J. Tarricone et al. 10.5194/tc-17-1997-2023
- Spatially distributed snow depth, bulk density, and snow water equivalent from ground-based and airborne sensor integration at Grand Mesa, Colorado, USA T. Meehan et al. 10.5194/tc-18-3253-2024
3 citations as recorded by crossref.
- Quantitative Evaluation of the Soil Signal Effect on the Correlation between Sentinel-1 Cross Ratio and Snow Depth T. Feng et al. 10.3390/rs13224691
- GNSS signal-based snow water equivalent determination for different snowpack conditions along a steep elevation gradient A. Capelli et al. 10.5194/tc-16-505-2022
- METHOD AND ACCURACY OF ESTIMATING SNOW DEPTH USING SENTINEL-1 SAR DATA IN GUNMA PREFECTURE IN JAPAN H. ABO et al. 10.2208/jscejj.22-00345
Latest update: 27 Dec 2024
Short summary
Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are presented over the European Alps. The novel observations can improve our knowledge of seasonal snow mass in areas with complex topography, where satellite-based estimates are currently lacking, and benefit a number of applications including water resource management, flood forecasting, and numerical weather prediction.
Snow depth observations at high spatial resolution from the Sentinel-1 satellite mission are...