en
Scientific article
Open access
English

Near-Real-Time Tephra Fallout Assessment at Mt. Etna, Italy

Published inRemote Sensing, vol. 11, no. 2987, p. 1-18
Publication date2019
Abstract

During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based on quantitative volcanological observations and modelling. The new system runs at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) and is able to provide a reliable hazard assessment to the National Department of Civil Protection (DPC) during explosive eruptions. The new operational system combines data from low-cost calibrated visible cameras and satellite images to estimate the variation of column height with time and model volcanic plume and fallout in near-real-time (NRT). The new system has three main objectives: (i) to determine column height in NRT using multiple sensors (calibrated cameras and satellite images); (ii) to compute isomass and isopleth maps of tephra deposits in NRT; (iii) to help the DPC to best select the eruption scenarios run daily by INGV-OE every three hours. A particular novel feature of the new system is the computation of an isopleth map, which helps to identify the region of sedimentation of large clasts (≥5 cm) that could cause injuries to tourists, hikers, guides, and scientists, as well as damage buildings in the proximity of the summit craters. The proposed system could be easily adapted to other volcano observatories worldwide.

Keywords
  • Hazard assessment
  • Column height
  • Near-real-time forecasts
  • Maximum clast forecasts
  • Operational system
  • Etna volcano
Citation (ISO format)
SCOLLO, Simona et al. Near-Real-Time Tephra Fallout Assessment at Mt. Etna, Italy. In: Remote Sensing, 2019, vol. 11, n° 2987, p. 1–18. doi: 10.3390/rs11242987
Main files (1)
Article (Published version)
Identifiers
ISSN of the journal2072-4292
273views
144downloads

Technical informations

Creation09/02/2020 8:11:00 PM
First validation09/02/2020 8:11:00 PM
Update time03/15/2023 10:30:29 PM
Status update03/15/2023 10:30:28 PM
Last indexation02/12/2024 11:54:40 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack