Determining Forest Parameters for Avalanche Simulation using Remote Sensing Data

353-356

Artikel aus einem Buch

200204837

ABSTRACT: Mountain forests offer effective, natural and cost-efficient protection against avalanches. Trees
stabilize snowpack and therefore reduce the avalanche formation and release. Another effect of trees is the
capacity of stopping or decelerating small to medium sized avalanches in the forested terrain. To simulate
the forest influence on the avalanche dynamics, the scientific version of the simulation tool RAMMS calculates
frictional as well as detrainment effects. Gathering field data of relevant forest structural parameters can
be time-consuming, but remote sensing data, such as the digital terrain model (DTM) in combination with the
newly available vegetation height model (VHM) allows an efficient assessment of such parameters on large
scales. In order to assess the differences of maximal tree height, surface roughness, resulting detrainment
coefficients and the runout length of avalanche simulations, two remote sensing methods were tested together
with forest information obtained in the field. Depending on the forest type (species composition and
density), we identified only slight differences in the maximal height between the remote sensing methods and
the field method, but we found surface roughness was significantly underestimated using the digital terrain
model compared to the field observation. The derived detrainment coefficients did not show a significant
influence on the simulation outputs. Comparing all the methods together, they did not show any major difference
in the simulation outputs, such as the estimated runout distances. The DTM in combination with the
current VHM available for Switzerland may thus have a sufficient accuracy to determine forest input parameters
for large-scale avalanche simulations in forested terrain.
KEYWORDS: forest avalanche, remote sensing, vegetation height model, avalanche simulation, RAMMS