We all monitor the world around us through waves. After about sixteen weeks in the womb, the ears and eyes of an infant child begin to deliver the first signals of light and sound waves to the brain. In fact, one could argue that consciousness itself is the feeling one receives when processing large amounts of wavefield data. Despite the integral presence of wavefield monitoring in biology, it is only since the dawn of the information age, that society has been able to monitor the world around us with similar fidelity. Where a recorded wavefield can be assumed to have travelled through a simple medium, it is often possible to resolve an image, though where a disordered medium is encountered, and the wavefield is multiply scattered, this becomes more difficult. It is this disordered portion of a wavefield, often referred to as the coda-wave, which this thesis is primarily concerned with. By considering the coda-wave over the coherent arrivals, one loses the ability to resolve the structure of a medium, though in turn gains improved sensitivity to changes within. This makes coda-wave monitoring particularly well suited to problems in which sensitivity to change is a more important quality than the ability to image the medium. On face value, one might consider coda-wave derived monitoring within Early Warning Systems (EWSs), towards hazards such as earthquakes, landslides, or the failure of critical infrastructure. However, operational deployment of such systems must work from simple, robust, and automated alert criteria, and therefore often rely on coherent wavefield observations, typically through passive measurements at the boundary of a region of interest. It is due to this reliance on clear, automated alert criteria derived from passive observation, which limits the lead time provided by EWSs, from only a few tens of seconds for earthquakes, to one day of warning for landslides.
|Qualification||Doctor of Philosophy|
|Award date||25 Mar 2020|
|Publication status||Published - 2020|
- Coda waves