Description du projet
Prévoir la menace de la destruction
On estime que 1 500 volcans terrestres sont potentiellement actifs à travers le monde. Nombre d’entre eux semblent éteints depuis des siècles, mais certains ne sont peut-être qu’«endormis». Quelque 73 éruptions de 70 volcans différents ont été confirmées en 2019. Les éruptions mortelles ont beau être relativement rares, elles ont bien lieu. C’est la raison pour laquelle la prévision des éruptions – durée et intensité – est si importante. Le projet DEEPVOLC, financé par l’UE, applique les percées réalisées dans les domaines de l’intelligence artificielle et du suivi par satellite pour créer de nouveaux ensembles de données géodésiques au pouvoir transformateur. Plus particulièrement, il tirera parti des observations de la mission satellitaire européenne Sentinel-1S lancée récemment, qui a amélioré la capacité des scientifiques de mesurer la déformation de la surface de tous les volcans de la planète. Il créera, à terme, un système de suivi et de prédiction de la déformation engendrée par la migration sous-jacente du magma, un indicateur d’une éventuelle activité volcanique.
Objectif
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.
Champ scientifique
- 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
Programme(s)
Régime de financement
ERC-COG - Consolidator GrantInstitution d’accueil
LS2 9JT Leeds
Royaume-Uni