Projektbeschreibung
Drohende Zerstörung vorhersagen
Weltweit gibt es schätzungsweise 1 500 potenziell aktive Vulkane auf dem Festland. Viele scheinen seit Jahrhunderten erloschen zu sein – unter Umständen „ruhen“ sie jedoch nur. Im Jahr 2019 gab es 73 bestätigte Ausbrüche von 70 verschiedenen Vulkanen. Tödliche Eruptionen sind zwar nicht häufig, kommen aber vor. Aus diesem Grund ist die Vorhersage von Ausbrüchen – mit Zeitpunkt und Schweregrad – so wichtig. Das EU-finanzierte Projekt DEEPVOLC nutzt Fortschritte in der künstlichen Intelligenz und der Satellitenüberwachung, um transformative neue geodätische Datensätze zu erstellen. Die Beobachtungen werden insbesondere auf der kürzlich gestarteten europäischen Satellitenmission Sentinel-1S basieren, welche die Möglichkeiten von Wissenschaftlerinnen und Wissenschaftlern verbessert hat, Oberflächenverformungen an allen Vulkanen weltweit zu messen. Letztendlich wird so ein System zur Überwachung und Vorhersage der durch Magmaverschiebungen entstehenden Verformungen geschaffen – ein Indikator für potenzielle vulkanische Tätigkeit.
Ziel
DEEPVOLC will radically advance the way future activity is forecast at volcanoes by applying advances in artificial intelligence to transformative new geodetic datasets. 200 million people live within 30 km of a volcano. Accurate forecasting of volcanic eruptions is problematic because 1) it relies on human interpretation at individual volcanoes, 2) a volcano can behave in unexpected ways not previously seen at that location, and 3) most volcanoes are not instrumented. DEEPVOLC will address this by i) applying artificial intelligence, ii) using data for all volcanoes worldwide, and iii) exploiting advances in satellite monitoring. A key indicator of potential volcanic activity is deformation of a volcano's surface due to magma migrating beneath. Surface movements as small as a few millimetres can now be measured from space, using satellite-borne radar. A recently-launched European satellite mission, Sentinel-1, has transformed our ability to measure surface deformation at all of the world's volcanoes, acquiring data at least twice every twelve days. However, forecasting how deforming volcanoes will behave in the future remains challenging. In this project I will apply recently developed deep learning approaches to the satellite data. This is an entirely new approach to forecasting volcanic activity, which currently relies on the individual expertise available at each observatory, and which is only now made possible due to the launch of Sentinel-1 and advances in deep learning algorithms. DEEPVOLC will combine knowledge from all volcanoes that have been active in the era of satellite deformation observations, and will continue to improve as it ingests data from new activity. The main deliverable will be a system for volcano observatories that uses knowledge of how volcanoes behave globally to automatically identify deformation at volcanoes locally, and forecast how the deformation will evolve, indicating the probability of eruption.
Wissenschaftliches Gebiet
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- natural sciencesearth and related environmental sciencesgeologyvolcanology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradar
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
Programm/Programme
Thema/Themen
Finanzierungsplan
ERC-COG - Consolidator GrantGastgebende Einrichtung
LS2 9JT Leeds
Vereinigtes Königreich