Detecting and modelling transient crustal deformation using Sentinel-1 InSAR and Machine Learning

随着全球导航卫星系统（GNSS）和卫星雷达干涉测量（InSAR）对地表变形的卫星大地测量观测质量的提高，断层行为在时间上的不稳定性越来越明显。在较短的时间尺度上，在世界各地的许多俯冲带观测到缓慢的地震，通常与地震震颤有关（Burgmann, 2018），大陆上的一些走滑断层段也被证明在“缓慢”或“无声”地震中间歇性地“蠕变”（Rousset等人，2016）[图1]。在大地震之前，在年代际尺度上观测到变形率的显著变化（mavromatis等人，2014年）。地震发生后，震后瞬态余震可能持续长达一个世纪（Ingleby和Wright， 2017）。在更长的时间尺度上，已经观察到断层在数千年内改变了其滑动速率（Cowie等人，2017）。该项目的学生将使用由利兹彗星科学家处理的Sentinel-1 InSAR的丰富大地测量数据，以及来自包括ERS和Envisat在内的卫星的存档数据，以及任何可用的GNSS （GPS）数据，来调查故障上瞬态行为的广泛程度。他们将使用机器学习方法来挖掘数据以识别变形瞬态。这可能包括使用监督学习方法对故障进行分类，以及来自时间序列分析、点处理和异常检测等领域的工具。他们将使用第四纪滑动率的估计来了解变形率在不同时间尺度上的变化。他们将利用这些结果来建立和测试地震变形周期的模型，了解变形瞬态的地质控制，并探索瞬态行为对我们对地震危害的理解的影响。研究结果将有潜在的应用于监测不同的灾害，包括世界范围内的火山、英国的山体滑坡和天坑。该项目适合具有地球科学，地质学或地球物理学背景的数学学生，他们对解决问题和使用EO和机器学习方法充满热情。学生将接受最先进的大地测量学和机器学习方法的培训，并有机会参加实地活动。该学生将成为英国自然环境研究委员会地震、火山和构造观测与建模中心（COMET）的一员，并将与来自英国各地具有不同技能和背景的COMET学生进行互动。参考文献/进一步ReadingBÜRGMANN， R. 2018。慢断层滑动的地球物理学、地质学和力学。地球科学进展，2004,26(5):444 - 444。Cowie, p.a., phillips, r.j., roberts, g.p., McCaffrey, k ., zijerveld, l.j.j., gregory, l.c., faure walker, j ., wedmore, l.n.j., dunai, t.j., binnie, s.a., freeman, s.p.h.t., wilcken, k ., shanks, r.p., huismans, r.s., papanikolaou, i ., michetti, a.m.和wilkinson， m . 2017。意大利中部亚平宁山脉造山带规模的隆起驱动了地震断层的幕式行为。科学通报，7,44858。Ingleby, t . & wright, t . 2017。大陆地震后震后速度的大森样衰减。地球物理学报，44,319 -3130。马夫罗马蒂斯，a. p .西格尔，p .和约翰逊，k. m . 2014。2011年Mw 9.0 Tohoku-oki地震前的十年尺度变形瞬变。地球物理学报，41(4):486- 494。Rousset, b ., jolivet, r ., simons, m ., lasserre, c ., riel, b ., milillo, p .， Çakir, z . & renard, f . 2016。北安纳托利亚断层上的一次地震滑动。地球物理学报，43,3254-3262。韦斯，j.r.，沃尔特斯，r.j.，森下，y，赖特，t.j.，拉兹基，m，王，h，侯赛因，e，胡珀，a.j.，艾略特，j.r.，罗林斯，c，余，c, gonzÁlez, p.j.，斯潘斯，k .，李，z . &

As the quality of satellite geodetic observations of surface deformation from Global Navigation Satellite Systems (GNSS) and Satellite Radar Interferometry (InSAR) have improved it has been increasingly clear that fault behaviour is not steady in time. On short time scales, slow earthquakes, often associated with seismic tremor, have been observed at numerous subduction zones around the world (Burgmann, 2018), and some segments of strike-slip faults in the continents have also been shown to "creep" episodically in "slow" or "silent" earthquakes (Rousset et al., 2016) [Figure 1]. Significant changes in deformation rate have been observed on a decadal scale prior to major earthquakes (Mavrommatis et al., 2014). Following earthquakes, postseismic transient afterslip can last for up to a century (Ingleby and Wright, 2017). And on a longer time scale, faults have been observed to change their rates of slip over millennia (Cowie et al., 2017).The student in this project will use the wealth of geodetic data from Sentinel-1 InSAR, processed by COMET scientists in Leeds, alongside archive data from satellites including ERS and Envisat, and any available GNSS (GPS) data, to investigate how widespread transient behaviour is on faults. They will use machine learning approaches to mine the data to identify deformation transients. This may include the use of supervised learning methods to classify faults, as well as tools from fields such as time series analysis, point processes, and anomaly detection. They will use estimates of Quaternary slip rates to understand how deformation rates vary over different timescales. They will use the results to build and test models of the earthquake deformation cycle, to understand the geological controls on deformation transients, and to explore the impact of transient behaviour on our understanding of seismic hazard. The results will have potential applications for monitoring different hazards, including volcanoes worldwide and landslides and sinkholes in the UK.The project would suit a numerate student with a background in earth sciences, geology, or geophysics who is enthusiastic about problem solving and the use of EO and machine learning approaches. The student will be provided with training in state-of-the-art geodetic and machine learning methods and will have the opportunity to participate in field campaigns. The student will be part of the UK Natural Environmental Research Council's Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) and will be expected to interact with COMET students with different skills and backgrounds from across the UK.References / Further ReadingBÜRGMANN, R. 2018. The geophysics, geology and mechanics of slow fault slip. Earth and Planetary Science Letters, 495, 112-134.COWIE, P. A., PHILLIPS, R. J., ROBERTS, G. P., MCCAFFREY, K., ZIJERVELD, L. J. J., GREGORY, L. C., FAURE WALKER, J., WEDMORE, L. N. J., DUNAI, T. J., BINNIE, S. A., FREEMAN, S. P. H. T., WILCKEN, K., SHANKS, R. P., HUISMANS, R. S., PAPANIKOLAOU, I., MICHETTI, A. M. & WILKINSON, M. 2017. Orogen-scale uplift in the central Italian Apennines drives episodic behaviour of earthquake faults. Scientific Reports, 7, 44858.INGLEBY, T. & WRIGHT, T. 2017. Omori-like decay of postseismic velocities following continental earthquakes. Geophysical Research Letters, 44, 3119-3130.MAVROMMATIS, A. P., SEGALL, P. & JOHNSON, K. M. 2014. A decadal-scale deformation transient prior to the 2011 Mw 9.0 Tohoku-oki earthquake. Geophysical Research Letters, 41, 4486-4494.ROUSSET, B., JOLIVET, R., SIMONS, M., LASSERRE, C., RIEL, B., MILILLO, P., ÇAKIR, Z. & RENARD, F. 2016. An aseismic slip transient on the North Anatolian Fault. Geophysical Research Letters, 43, 3254-3262.WEISS, J. R., WALTERS, R. J., MORISHITA, Y., WRIGHT, T. J., LAZECKY, M., WANG, H., HUSSAIN, E., HOOPER, A. J., ELLIOTT, J. R., ROLLINS, C., YU, C., GONZÁLEZ, P. J., SPAANS, K., LI, Z. &