Hot spot detection and effusion rate estimation using satellite data to drive lava flow simulations

Abstract

We demonstrated how infrared satellite data can be used to drive numerical simulations of lava flow paths and produced a detailed chronology of lava flow emplacement while an eruptive event was ongoing. We evaluated the lava flow hazard on Etna volcano during the first 40 days of May 2008 eruption by means of the MAGFLOW cellular automata model. This model was developed for simulating lava flow paths and the temporal evolution of lava emplacement. Many data are necessary to run MAGFLOW and to determine how far lava will flow. However, for a given composition, the volumetric flux of lava from the vent (i.e. the lava effusion rate) is the principal parameter controlling final flow dimensions. Measuring effusion rates is therefore of great interest. To this end, we developed an automatic system that uses near-real-time infrared satellite data to estimate the lava effusion rates. Such system exploits the satellite data directly received and automatically processed by RST approach at CNR-IMAA, as input information for the prediction of the path lava flows. In particular, hotspots detected by RST, using both AVHRR and MODIS data, have been used to compute time-varying effusion rates, which have been applied to drive lava flow simulation using the original MAGFLOW cellular automata algorithm. Achieved results confirm the reliability of two methodologies (i.e. RST approach and MAGFLOW model), as well as the potential of the whole integrated processing chain, as an effective tool for real-time monitoring and mitigation of volcanic hazard.