A Support Analysis Framework for mass movement damage assessment_ applications to case studies in Calabria (Italy)

Olga Petrucci; Giovanni Gullà, 2009, A Support Analysis Framework for mass movement damage assessment_ applications to case studies in Calabria (Italy), Natural hazards and earth system sciences (Online) 9 (2009): 315–326. doi_10.5194/nhess-9-315-2009,
URL: http://www.cnr.it/prodotto/i/187246

The analysis of data describing damage caused by mass movements in Calabria (Italy) allowed the organisation of the Support Analysis Framework (SAF), a spreadsheet that converts damage descriptions into numerical indices expressing direct, indirect, and intangible damage. The SAF assesses damage indices of past mass movements and the potential outcomes of dormant phenomena re-activations. It is based on the effects on damaged elements and is independent of both physical and geometric phenomenon characteristics. SAF sections that assess direct damage encompass several lines, each describing an element characterised by a value fixed on a relative arbitrary scale. The levels of loss are classified as_ L4_ complete; L3_ high; L2_ medium; or L1_ low. For a generic line l, the SAF multiplies the value of a damaged element by its level of loss, obtaining dl, the contribution of the line to the damage. Indirect damage is appraised by two sections accounting for_ (a) actions aiming to overcome emergency situations and (b) actions aiming to restore pre-movement conditions. The level of loss depends on the number of people involved (a) or the cost of actions (b). For intangible damage, the level of loss depends on the number of people involved. We examined three phenomena, assessing damage using the SAF and SAFL, customised versions of SAF based on the elements actually present in the analysed municipalities that consider the values of elements in the community framework. We show that in less populated, inland, and affluent municipalities, the impact of mass movements is greater than in coastal areas. The SAF can be useful to sort groups of phenomena according to their probable future damage, supplying results significant either for insurance companies or for local authorities involved in both disaster management and planning of defensive measures.

Data from https://intranet.cnr.it/people/