About the research

Many populated areas are vulnerable to lava flows, which cause considerable economic damage as illustrated by the 2018 Kilauea eruption and the 1973 Eldfell eruption. Forecasting of lava flow hazards has only shown moderate success until now due to the complexity of lava flow dynamics. Important information regarding lava morphology, which can improve the forecasting of lava flows, is currently not being used. Linking lava flow morphology with parameters such as effusion rate and emplacement speed has the potential to improve real-time monitoring of lava flow dynamics. Information from lava morphology remains largely underexploited due to a lack of time-efficient, automated mapping techniques and to lava simulation codes being incapable of integrating time-evolving morphologically-derived information. The goals of MoLa are: 1) Develop state-of-the-art mapping techniques of lava flow morphology so morphological information can be optimally utilized during effusive eruptions. 2) Implement this information in a lava simulation code to improve lava flow forecasting. The goals will be achieved through interdisciplinary collaboration between experts in image signal processing, remote sensing, volcanology, lava flow simulation and institutions responsible for monitoring and forecasting lava flows. Lava flows from the Icelandic volcano Hekla will be used to develop the methods, and the project results will potentially improve lava hazard mitigation world-wide.

Keywords: Lava, Monitoring, Hazard, Remote sensing, Lava flow simulation

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