Special Seminar: Advanced DInSAR analysis of natural and anthropogenic hazards
Dr. Kristy Tiampo received her BSc in Civil Engineering from Tufts University, USA, and her MSc in Civil Engineering from Stanford University, USA. She obtained her PhD in Geophysics from the University of Colorado at Boulder, USA, after practicing as a construction engineer for the US Army Corps of Engineers for almost 10 years, during which time she earned her certification as a Professional Engineer. In 2003 she was appointed Assistant Professor of Geophysics at Western University, Canada, and was the NSERC and Aon Benfield/ICLR Industrial Research Chair in Earthquake Hazard from 2006 through 2011. Today she is Professor and Associate Chair of the Department of Earth Sciences at Western University.
Dr. Tiampo's research program aims to provide a comprehensive understanding of the processes which govern natural and anthropogenic hazards and, in particular, those that generate earthquakes, and thus improve the associated estimates of the regional seismic hazard. This is accomplished through the integration of large quantities of remote sensing data such as space-based Global Positioning System (GPS) data, differential Interferometric Synthetic Aperture Radar (DInSAR), seismicity and gravity, in order to provide critical information on the nature and scale of these hazards. Her research program includes improvements into the nature and quantity of that data, innovative analysis techniques, accurate models of the potential geophysical sources, and timely and appropriate assimilation into various computational models. Significant contributions from her research group include development of the first of a new generation of seismicity measures and effective inversions for the sources of surface deformation associated with earthquake and volcanic hazard as well as anthropogenic signals.
Abstract: In recent years, the wide variety of synthetic aperture radar (SAR) images acquired with different spatial signatures and technical characteristics has provided the impetus for advanced methodologies aimed at producing accurate estimates of surface deformation over broad spatial regions. Advanced differential interferometric SAR (DInSAR) techniques include, for example, persistent scatterer (PS) analysis (Ferretti et al., 2001), designed to identify stable, coherent image pixels, and time series analysis methods such as the Small BAseline Subset (SBAS) algorithm (Berardino et al., 2002; Hooper, 2008). However, each of these techniques has important drawbacks that impact their effectiveness under specific circumstances. For example, in order to confidently select PS pixels with a high degree of accuracy, it is necessary to have at least thirty SAR images (Ferretti et al., 2001), which is both cost prohibitive and results in longer averaging time spans. While very effective in measuring slow line-of-sight (LOS) deformation, SBAS is limited in the temporal domain by the satellite revisit time, which can range from 11 to 41 days. In this talk, I present several new advanced DInSAR techniques aimed at minimizing these difficulties and improving the spatial and temporal resolution of the estimated surface displacement. These include several analysis techniques that employ quad polarized data for improved PS analysis (Samsonov and Tiampo, 2011; Alipour et al., 2013; Tiampo et al., 2013) and a multidimensional SBAS (MSBAS) method that is capable of integrating data from various SAR satellites (Samsonov et al., 2014). Finally, case studies are presented that illustrate the effectiveness of advanced DInSAR analysis for improved understanding of natural and anthropogenic hazards.