Applying neighbourhood classification systems to natural hazards: a case study of Mt Vesuvius

The dynamic forces of urbanisation that characterised much of the 20th Century and still dominate population growth in developing countries have led to the increasing risk of natural hazards in cities around the world (Chester 2000, Pelling 2003). None of these physical dangers is more tangible than the threat volcanoes pose to the large populations living in close proximity. Vesuvius, a recognised decade volcano following the UN’s International Decade for Natural Disaster Reduction (IDNDR) has an estimated 550,000 people that live in areas susceptible to Pyroclastic Density Currents (PDC) (Barberi 2008) and a further 4 million at risk from ash fallout around the sprawling suburbs of Naples. Though quiescent since 1944, the prospect of a large eruption of Vesuvius presents a greater geophysical threat to the Campania region of Italy than perhaps ever before. With the Neopolitan region at risk from such an event, this paper proposes a new methodology for creating a Social Vulnerability Index (SoVi) using geodemographic classification systems. In this study, Experian’s MOSAIC Italy database is combined with geophysical risk boundaries to assess the overall vulnerability of the population around Vesuvius

Utilizzo di fioretto meccanico e carotiere microstratigrafico inguainante per la valutazione degli spessori e della stratigrafia delle coltri vulcanoclastiche soggette a fenomeni di colata rapida di fango

Geologia Tecnica & Ambiental

GIS-assisted modelling for debris flow hazard assessment based on the events of May 1998 in the area of Sarno, Southern Italy. Part II: Velocity and Dynamic Pressure

The velocity and dynamic pressure of debris flows are critical determinants of the impact of these natural phenomena on infrastructure. Therefore, the prediction of these parameters is critical for hazard assessment and vulnerability analysis. We present here an approach to predict the velocity of debris flows on the basis of the energy line concept. First, we obtained empirically and field-based estimates of debris flow peak discharge, mean velocity at peak discharge and velocity, at channel bends and within the fans of ten of the debris flow events that occurred in May 1998 in the area of Sarno, Southern Italy. We used this data to calibrate regression models that enable the prediction of velocity as a function of the vertical distance between the energy line and the surface. Despite the complexity in morphology and behaviour of these flows, the statistical fits were good and the debris flow velocities can be predicted with an associated uncertainty of less than 30% and less than 3 m s−1. We wrote code in Visual Basic for Applications (VBA) that runs within ArcGIS® to implement the results of these calibrations and enable the automatic production of velocity and dynamic pressure maps. The collected data and resulting empirical models constitute a realistic basis for more complex numerical modelling. In addition, the GIS implementation constitutes a useful decisionsupport tool for real-time hazard mitigation