We deal with the theme of the simulation of risk analysis using a technological approach based on the integration of exclusively free and open source tools: PostgreSQL as Database Management System (DBMS) and Quantum GIS-GRASS as Geographic Information System (GIS) platform. The case study is represented by a seismic land in Sicily characterized by steep slopes and frequent instability phenomena. This area includes a city of about 30.000 inhabitants (Enna) that lies on the top of a mountain at about 990 m a.s.l.. The access to the city is assured by few and very winding roads that are also highly vulnerable to seismic and hydrogeological hazards. When exceptional rainfall events occur the loss of efficiency of these roads should compromise timeliness and effectiveness of rescue operations. The data of the sample area have been structured into the adopted DBMS and the connection to the GIS functionalities allows simulating the exceptional events. We analyzed the hazard vulnerability and exposure related to these events and calculated the final risk defining three classes for each scenario: low (L) medium (M) and high (H). This study can be a valuable tool to prioritize risk levels and set priorities for intervention to the main road networks.
A spatial DB model to simulate the road network efficiency in hydrogeological emergency
MANGIAMELI, MICHELE;MUSSUMECI, Giuseppe
2015-01-01
Abstract
We deal with the theme of the simulation of risk analysis using a technological approach based on the integration of exclusively free and open source tools: PostgreSQL as Database Management System (DBMS) and Quantum GIS-GRASS as Geographic Information System (GIS) platform. The case study is represented by a seismic land in Sicily characterized by steep slopes and frequent instability phenomena. This area includes a city of about 30.000 inhabitants (Enna) that lies on the top of a mountain at about 990 m a.s.l.. The access to the city is assured by few and very winding roads that are also highly vulnerable to seismic and hydrogeological hazards. When exceptional rainfall events occur the loss of efficiency of these roads should compromise timeliness and effectiveness of rescue operations. The data of the sample area have been structured into the adopted DBMS and the connection to the GIS functionalities allows simulating the exceptional events. We analyzed the hazard vulnerability and exposure related to these events and calculated the final risk defining three classes for each scenario: low (L) medium (M) and high (H). This study can be a valuable tool to prioritize risk levels and set priorities for intervention to the main road networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.