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Determining forest parameters for avalanche simulation using remote sensing data
Abstract Mountain forests offer effective, natural and cost-efficient protection against avalanches. Trees reduce the probability of an avalanche formation and can significantly decelerate small to medium size avalanches. Remote sensing methods enable an efficient assessment of forest structural parameters on large scale and therefore determine the protective capacity of a specific forest. The aims of this study are: (i) to evaluate the quality of forest structural parameters obtained from remote sensing data using two different methods; and (ii) to determine how forest parameters and forest cover changes influence avalanche runout. We compared the control assessment of maximum tree height and crown coverage in 107 plots (50 in evergreen and 57 in deciduous forests). The same parameters were analysed using (i) a photogrammetry-based vegetation height model (VHMP) and (ii) a LiDAR-based vegetation height model (VHML). The control assessment of surface roughness was compared to the analysis of a digital terrain model (DTM). We then simulated two avalanche case studies near Davos (Switzerland) with forest parameters estimated by the remote sensing and control methods. Tree height and crown coverage assessed with both remote sensing methods (VHMP and VHML) did not differ significantly from the control measurements. However, surface roughness was underestimated. This had a significant influence on simulation results. For the first case study, a wet-snow avalanche, the simulated runout distances did not differ significantly, when using forest parameters from either of the two tested remote sensing methods. The simulated runout distance increased for an avalanche scenario with less forest cover in the release area and/or less forest cover after forest destruction by a preceding avalanche event. For the second case study, a dry-snow avalanche, the forest cover was underestimated by the VHMP, which led to longer simulated runout distances. Our study indicates that available remote sensing methods are increasingly suitable for the determination of forest parameters which are relevant for avalanche simulation models. However, more research is needed on the precise estimation of forest cover in release areas and understanding how forest cover changes affect avalanche runout.
Highlights High resolution remote sensing data are suitable to determine forest parameters for avalanche simulation Surface roughness is underestimated using a 1 m resolution digital terrain model Underestimation of forest cover in release areas may lead to an overestimation of runout distance Spatial and temporal changes in forest structure should be taken into account in avalanche modeling
Determining forest parameters for avalanche simulation using remote sensing data
Abstract Mountain forests offer effective, natural and cost-efficient protection against avalanches. Trees reduce the probability of an avalanche formation and can significantly decelerate small to medium size avalanches. Remote sensing methods enable an efficient assessment of forest structural parameters on large scale and therefore determine the protective capacity of a specific forest. The aims of this study are: (i) to evaluate the quality of forest structural parameters obtained from remote sensing data using two different methods; and (ii) to determine how forest parameters and forest cover changes influence avalanche runout. We compared the control assessment of maximum tree height and crown coverage in 107 plots (50 in evergreen and 57 in deciduous forests). The same parameters were analysed using (i) a photogrammetry-based vegetation height model (VHMP) and (ii) a LiDAR-based vegetation height model (VHML). The control assessment of surface roughness was compared to the analysis of a digital terrain model (DTM). We then simulated two avalanche case studies near Davos (Switzerland) with forest parameters estimated by the remote sensing and control methods. Tree height and crown coverage assessed with both remote sensing methods (VHMP and VHML) did not differ significantly from the control measurements. However, surface roughness was underestimated. This had a significant influence on simulation results. For the first case study, a wet-snow avalanche, the simulated runout distances did not differ significantly, when using forest parameters from either of the two tested remote sensing methods. The simulated runout distance increased for an avalanche scenario with less forest cover in the release area and/or less forest cover after forest destruction by a preceding avalanche event. For the second case study, a dry-snow avalanche, the forest cover was underestimated by the VHMP, which led to longer simulated runout distances. Our study indicates that available remote sensing methods are increasingly suitable for the determination of forest parameters which are relevant for avalanche simulation models. However, more research is needed on the precise estimation of forest cover in release areas and understanding how forest cover changes affect avalanche runout.
Highlights High resolution remote sensing data are suitable to determine forest parameters for avalanche simulation Surface roughness is underestimated using a 1 m resolution digital terrain model Underestimation of forest cover in release areas may lead to an overestimation of runout distance Spatial and temporal changes in forest structure should be taken into account in avalanche modeling
Determining forest parameters for avalanche simulation using remote sensing data
Brožová, Natalie (author) / Fischer, Jan-Thomas (author) / Bühler, Yves (author) / Bartelt, Perry (author) / Bebi, Peter (author)
2019-12-29
Article (Journal)
Electronic Resource
English
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