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iForest - Biogeosciences and Forestry

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

Dora Cimini (1), Luigi Portoghesi (1)   , Sergio Madonna (2), Salvatore Grimaldi (3-4), Piermaria Corona (5)

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

Research Articles


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 landslide-prone 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.

  Keywords


Forest Protective Function, Landslide Susceptibility, Logistic Regression, Weight of Evidence, GIS, Alps

Authors’ address

(1)
Dora Cimini
Luigi Portoghesi
Department for Innovation in Biological, Agro-food and Forest systems (DIBAF), University of Tuscia, v. S. Camillo de Lellis, snc - 01100 Viterbo (Italy)
(2)
Sergio Madonna
Department of Science and Technology for Agriculture, forests, Nature and Energy (DAFNE), University of Tuscia, v. S. Camillo de Lellis, snc - 01100 Viterbo (Italy)
(3)
Salvatore Grimaldi
Honors Center of Italian Universities (H2CU), Sapienza University of Rome, v, Eudossiana 18, I-00184 Roma (Italy)
(4)
Salvatore Grimaldi
Department of Mechanical and Aerospace Engineering, Polytechnic Institute of New York University, Six MetroTech, Brooklyn, NY 11201 (USA)
(5)
Piermaria Corona
Forestry Research Center (CREA SEL) The Council for Agricultural Research and Economics, v.le S. Margherita 80, I-52100 Arezzo (Italy)

Corresponding author

 
Luigi Portoghesi
lporto@unitus.it

Citation

Cimini D, Portoghesi L, Madonna S, Grimaldi S, Corona P (2016). Multifactor empirical mapping of the protective function of forests against landslide occurrence: statistical approaches and a case study. iForest 9: 383-393. - doi: 10.3832/ifor1740-008

Academic Editor

Marco Borghetti

Paper history

Received: May 28, 2015
Accepted: Oct 20, 2015

First online: Jan 16, 2016
Publication Date: Jun 01, 2016
Publication Time: 2.93 months

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