Multifactor empirical mapping of the protective function of forests against landslide occurrence: statistical approaches and a case study

This is the final paper of:  Multifactor empirical mapping of the protective function of forests against landslide occurrence: statistical approaches and a case study- published iForest - Biogeosciences and Forestry, Volume 9, Issue 3, Pages 383-393 (2016)
doi: https://doi.org/10.3832/ifor1740-008 Published: Jan 16, 2016 - Copyright © 2016 SISEF

Abstract

Forests are increasingly valued for services beyond timber and non-timber
products including land protection with respect to events such as landslides,
soil erosion, floods and avalanches. The most important properties of a protective
forest are its ecological and mechanical stability. Planning and implementing
multifunctional forest management in protective forests is challenging
because of the trade-offs and synergies among the many functions of the forest.
In this study, a multifactor empirical method is presented for assessing
the protective role of forests on a stand scale with respect to landslide occurrence.
Multifactor methodologies typically estimate landslide susceptibility exploiting
the relationship between past landslide patterns and site characteristics.
Two statistical approaches were here applied to assess the probability of
landslide occurrence: the weight-of-evidence technique and the logistic regression
technique. Statistical analysis was performed on the basis of landslide
detachment zone only. The question of how to estimate protective forest function
was answered through the comparison of models established with different
sets of predicting factors. This study ultimately aims to provide a decision-
support tool focused on mapping the potential role of forests in landslideprone
areas. A case study from the Italian Alps was considered. The density of
landslide detachment outside forest areas proves to be more than twice than
that within forest areas.