Determining Forest Parameters for Avalanche Simulation using Remote Sensing Data

Artikel aus einem Buch

17574BU

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