A simplified method for assessing landslide damage indices

Abstract

The Support Analysis Framework (SAF) is a tool that converts descriptions of landslide effects into numerical indices expressing direct, indirect and intangible damage. Sections assessing direct damage are made up of 'elements' characterised by relative values and the 'levels of loss' that they can suffer. By typing an x value into the cell representing an element and a level of loss, formulas multiply the value of the element by the level of loss, obtaining a value used in the damage indices assessing. Indirect damage deals with: (a) emergency response and (b) efforts to restore pre-landslide conditions. The level of loss depends on the number of people affected (a) or the cost of actions (b). For intangible damage, the level of loss depends on the number of people affected. We assess the damage indices for a landslide occurred in Calabria (Italy) in 2005, using both the SAF and the SAFL, a customised version that takes into account the local socio-economic framework by including only elements present in the analysed municipality. We assess the damage indices for three scenarios with different initial conditions and compare them to the 2005 event; the results would have been useful to mitigate damage. The SAF can be used by nonspecialists, and it allows the ranking of damage caused by different landslides, thus supporting local authorities in prioritising countermeasures and civil protection offices to speed up responses to refund requests. The sorting of dormant phenomena according to their possible damage helps with defensive measures, emergency plans and insurance purposes.

Landslide Susceptibility Mapping for the Muchuan County (China): A Comparison Between Bivariate Statistical Models (WoE, EBF, and IoE) and Their Ensembles with Logistic Regression

“…As one of the most frequently-occurring geological disasters in the world, landslides have triggered a series of threats to human society including casualties, economic losses, infrastructure destruction, and geological environment problems [1][2][3]. Therefore, to reduce the losses, it is absolutely necessary to study the landslide susceptibility in a region [4,5].…”

Fragility of transport assets exposed to multiple hazards: State-of-the-art review toward infrastructural resilience

“…In the second approach, the risk is estimated based on semi-quantitative vulnerability indicators using numerical thresholds (ranking) and quantitative estimates of the frequency of the natural hazard (e.g. Petrucci and Gulla 2010;Eidsvig et al 2017). The concept of the quantitative risk analysis (QRA), which quantifies the probability of a given level of loss and the associated uncertainties, has also been touched by Eurocodes (EN1991-17, 2006.…”

Authors Reply to RC1

“…Landslide susceptibility was assessed at the pixel level using the information value method (Yin and Yan, 1988), which is a Bayesian bivariate statistical model that has been shown to be suitable for landslide susceptibility assessment (e.g. Piedade et al, 2011;Guillard andOliveira et al, 2015 and references therein); it has further been recommended as a method for data-driven landslide susceptibility assessment worldwide (Corominas et al, 2014). The susceptibility assessment procedures were based on the work of Garcia (2012), namely, a landslide inventory based on fieldwork and the interpretation of aerial photos with 0.5 m resolution.…”