Estimating exposure around San Miguel Volcano, El Salvador
San Miguel, one of the most active volcanoes in El Salvador, is surrounded by several villages and cantons, which could be seriously affected in case of a new eruption. This study presents an exposure analysis of the San Miguel volcano area by considering population distribution, land use, private h...
| Autores: | , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/194488 |
| Acceso en línea: | http://hdl.handle.net/10261/194488 |
| Access Level: | acceso abierto |
| Palabra clave: | Vulnerability San Miguel volcano Hazard assessment Exposure analysis |
| Sumario: | San Miguel, one of the most active volcanoes in El Salvador, is surrounded by several villages and cantons, which could be seriously affected in case of a new eruption. This study presents an exposure analysis of the San Miguel volcano area by considering population distribution, land use, private houses, official buildings (hospitals, schools, etc.), and communication infrastructure. We use spatial analysis Geographic Information System tools to estimate exposure for different volcanic hazards (air fallout, lava flows, pyroclastic density currents, lahars). Moreover, in the particular case of private houses and official buildings, we estimate a Vulnerability Index for the hazardous areas, applying the Physical Vulnerability Methodology based on the characterization of the type of construction materials of walls and roofs. We construct different exposure maps for: 1) population, 2) land use, 3) road networks, 4) schools, and 5) health centers. This approach identifies the elements at risk according to each potential hazard, thus providing the authorities with a comprehensive tool to better understand the problem and to define emergency plans to minimize risk. © 2019 Elsevier B.V. |
|---|