We interrogate and develop physically based statistical methods for forecasting the evolution of seismicity in both tectonic and volcanic settings. Professor Mark Naylor is pioneering the use of inlabru (a novel spatio-temporal point process method) for modelling the evolution of seismicity with application to operational seismology. Inlabru is a Bayesian spatio-temporal modelling code that holds great potential for modelling, simulating and forecasting in many aspects of earth and environmental science, particularly natural hazards. Inlabru is built on R which allows us to re-use many of the existing packages for handling spatial datasets; for example, we can load shape files for fault networks and directly use them as a covariate in our earthquake forecasts. We exploit a close collaboration between the statistical experts developing the inlabru framework and geoscientists with hazard-specific expertise to build a new generation of hazard forecasts. This work is funded by Horizon 2020 and in collaboration with Professor Finn Lindgren from the School of Mathematics. More information about the 'Hazard modelling using inlabru and statistical seismology' project Publications * Affiliated members highlighted in bold (2020) An automatically generated high-resolution earthquake catalogue for the 2016–2017 Central Italy seismic sequence, including P and S phase arrival times. Geophysical Journal International, 225. 555-571. Authors: Spallarossa, D., Cattaneo, M., Scafidi, D., Michele, M., Chiaraluce, L., Segou, M., Main, I. G. View publication (2020) Data-driven optimization of seismicity models using diverse data sets: generation, evaluation and ranking using inlabru. Journal of Geophysical Research. Solid Earth, 125. Authors: Bayliss, K., Naylor, M., Illian, J., Main, I. View publication Key staff Dr Andrew Bell Professor Ian Main Dr Mark Naylor This article was published on 2024-07-01
