Modeling a system for decision support in snow avalanche warning using balanced random forest and weighted random forest

Abstract

In alpine regions, traffic infrastructure may be endangered by snow avalanches. If not protected by physical structures, roads need to be temporarily closed in order to prevent fatal accidents. For assessing the danger of avalanches, local avalanche services use, amongst others, meteorological data measured on a daily basis as well as expert knowledge about avalanche activity. Based on this data, a system for decision support in avalanche warning has been developed. Feasible models were trained using Balanced Random Forests and Weighted Random Forests, yielding a performance useful for human experts. The results are discussed and options for further improvements are pointed out.