Articles | Volume 21, issue 11
https://doi.org/10.5194/nhess-21-3539-2021
© 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/nhess-21-3539-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Nov 2021
Research article |
| 22 Nov 2021
| 22 Nov 2021
Multiscale analysis of surface roughness for the improvement of natural hazard modelling
Alpine Environment and Natural Hazards, WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Department of Environmental Systems Science, Swiss Federal Institute of Technology (ETH Zurich), Zurich, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Flüelastrasse 11, 7260 Davos
Dorf, Switzerland
Tommaso Baggio
Department of Land, Environment, Agriculture and Forestry, University of Padua, Legnaro, Italy
Vincenzo D'Agostino
Department of Land, Environment, Agriculture and Forestry, University of Padua, Legnaro, Italy
Yves Bühler
Alpine Environment and Natural Hazards, WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Flüelastrasse 11, 7260 Davos
Dorf, Switzerland
Peter Bebi
Alpine Environment and Natural Hazards, WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
Climate Change, Extremes and Natural Hazards in Alpine Regions Research Center CERC, Flüelastrasse 11, 7260 Davos
Dorf, Switzerland
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Cited
15 citations as recorded by crossref.
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- Post-windthrow forest development in spruce-dominated mountain forests in Central Europe N. Piazza et al. 10.1016/j.foreco.2024.121884
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- Opportunity mapping for nature-based solutions: Mitigating storm surge and land erosion in the Caribbean L. Soanes et al. 10.1016/j.nbsj.2023.100095
- Comparability of multi‐temporal DTMs derived from different LiDAR platforms: Error sources and uncertainties in the application of geomorphic impact studies N. Kamp et al. 10.1002/esp.5540
- Rockfall susceptibility along Pasang Lhamu and Galchhi-Rasuwagadhi highways, Rasuwa, Central Nepal B. Pokharel et al. 10.1007/s10064-023-03174-8
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- Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada J. Sykes et al. 10.5194/nhess-24-947-2024
- R_IC: A novel and versatile implementation of the index of connectivity in R L. Martini et al. 10.1016/j.envsoft.2022.105446
- Novel indices for snow avalanche protection assessment and monitoring of wind-disturbed forests T. Baggio et al. 10.1016/j.ecoleng.2022.106677
- A simplified geostatistical approach for characterizing key aspects of short-range roughness S. Trevisani et al. 10.1016/j.catena.2023.106927
- Investigation of the effects of hybrid modeling approaches, factor standardization, and categorical mapping on the performance of landslide susceptibility mapping in Van, Turkey D. Ozturk & N. Uzel-Gunini 10.1007/s11069-022-05480-y
- Unprecedented Winter Rainfall Initiates Large Snow Avalanche and Mass Movement Cycle in New Zealand's Southern Alps/Kā Tiritiri o te Moana A. Miller et al. 10.1029/2022GL102105
- Using drone-based multispectral imaging for investigating gravelly debris flows and geomorphic characteristics H. Chen et al. 10.1007/s12665-024-11544-y
13 citations as recorded by crossref.
- Automated avalanche hazard indication mapping on a statewide scale Y. Bühler et al. 10.5194/nhess-22-1825-2022
- Modeling deadwood for rockfall mitigation assessments in windthrow areas A. Ringenbach et al. 10.5194/esurf-10-1303-2022
- Post-windthrow forest development in spruce-dominated mountain forests in Central Europe N. Piazza et al. 10.1016/j.foreco.2024.121884
- Large-scale risk assessment on snow avalanche hazard in alpine regions G. Ortner et al. 10.5194/nhess-23-2089-2023
- Opportunity mapping for nature-based solutions: Mitigating storm surge and land erosion in the Caribbean L. Soanes et al. 10.1016/j.nbsj.2023.100095
- Comparability of multi‐temporal DTMs derived from different LiDAR platforms: Error sources and uncertainties in the application of geomorphic impact studies N. Kamp et al. 10.1002/esp.5540
- Rockfall susceptibility along Pasang Lhamu and Galchhi-Rasuwagadhi highways, Rasuwa, Central Nepal B. Pokharel et al. 10.1007/s10064-023-03174-8
- The impact of terrain model source and resolution on snow avalanche modeling A. Miller et al. 10.5194/nhess-22-2673-2022
- Automated Avalanche Terrain Exposure Scale (ATES) mapping – local validation and optimization in western Canada J. Sykes et al. 10.5194/nhess-24-947-2024
- R_IC: A novel and versatile implementation of the index of connectivity in R L. Martini et al. 10.1016/j.envsoft.2022.105446
- Novel indices for snow avalanche protection assessment and monitoring of wind-disturbed forests T. Baggio et al. 10.1016/j.ecoleng.2022.106677
- A simplified geostatistical approach for characterizing key aspects of short-range roughness S. Trevisani et al. 10.1016/j.catena.2023.106927
- Investigation of the effects of hybrid modeling approaches, factor standardization, and categorical mapping on the performance of landslide susceptibility mapping in Van, Turkey D. Ozturk & N. Uzel-Gunini 10.1007/s11069-022-05480-y
2 citations as recorded by crossref.
- Unprecedented Winter Rainfall Initiates Large Snow Avalanche and Mass Movement Cycle in New Zealand's Southern Alps/Kā Tiritiri o te Moana A. Miller et al. 10.1029/2022GL102105
- Using drone-based multispectral imaging for investigating gravelly debris flows and geomorphic characteristics H. Chen et al. 10.1007/s12665-024-11544-y
Latest update: 25 Apr 2024
Short summary
Surface roughness plays a great role in natural hazard processes but is not always well implemented in natural hazard modelling. The results of our study show how surface roughness can be useful in representing vegetation and ground structures, which are currently underrated. By including surface roughness in natural hazard modelling, we could better illustrate the processes and thus improve hazard mapping, which is crucial for infrastructure and settlement planning in mountainous areas.
Surface roughness plays a great role in natural hazard processes but is not always well...
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