Landslides commonly occur in areas with steep topography and abundant precipitation, and can pose a significant hazard to local communities. Some of the largest known landslides occurred in Alaska, including several that caused local tsunamis. Many more landslides may have gone undetected in remote unpopulated areas due to lack of observations. In this study, we develop an integrated procedure based on seismic and geodetic observations to detect, locate, validate, and characterize landslides in Alaska. Seismic observations have shown promise in continuously monitoring landslide occurrence, while remote sensing techniques are well suited for verification and high-resolution imaging of the detected landslides. We validate our procedure using data from the previously detected June 28, 2016, Lamplugh Glacier landslide. We also present observations of a previously unknown landslide that occurred on September 22, 2017 in the Wrangell Mountains region. The Wrangell Mountains landslide generated a coherent surface wavefield recorded across Alaska and the contiguous US. We used Sentinel-1 Synthetic Aperture Radar and Sentinel-2 optical imagery to map the respective mass deposit. To investigate the landslide dynamics, we inverted regional seismic surface wave data for a centroid single force failure model. Our model suggests that the Wrangell Mountains landslide lasted for about 140~s and had two subevents involving at least five distinct episodes. We estimate that the landslide had displaced 3.1--13.4~million tons of rocks over a distance of 2 km. Our results suggest that combining seismic and geodetic observations can vastly improve the detection and characterization of landslides in remote areas in Alaska and elsewhere, and providing new insights into the landslide dynamics.

Earthquakes are the primary source of seismic waves in seismology and understanding the earthquake source is essential for predicting ground motions and detailing the physics of rupture. Earthquake kinematic source imaging describes the whole rupture process during an earthquake. It does not directly require the resolved source model to be physically or dynamically plausible, but can help in understanding the conditions of rupture dynamics. Therefore, accurate earthquake source models are highly desirable.

In Chapter 2, we develop a frequency-based approach to earthquake slip inversion that requires no prior information on the rupture velocity or slip-rate functions.

In Chapter 3, we characterize the rupture process of the 25 April 2015 Nepal earthquake with globally recorded teleseismic P waves.

In Chapter 4, we investigate the 10 January 2012 Mw 7.2 Sumatra earthquake in the Wharton basin and detect dynamically-triggered large early aftershocks occurring on or near the subduction interface.

In Chapter 5, we constrain the spatiotemporal evolution of the 2009 Tonga-Samoa earthquake with global P-wave back-projection and a multiple moment-tensor inversion. Our results show that the rupture branches east of the trench axis were controlled by the geometry of bending-related faults on the Pacific plate, and that the rupture branch west of the trench axis may correlate with along-strike fore-arc segmentation.

In Chapter 6, we detect and locate 48 previously unidentified large early aftershocks triggered by 7 < M < 8 earthquakes within a few fault lengths, during times that high-amplitude surface waves arrive from the mainshock. The observations indicate that near-to-intermediate-field dynamic triggering commonly exists and fundamentally promotes aftershock occurrence.

In Chapter 7, we analyze the 2006 Mw 7.8 Java tsunami earthquake with global P-wave back-projection, tsunami tide-gauge back-propagation, and P-wave source spectra modeling. The results suggest that the splay faults may have been reactivated during the Java earthquake.

In Chapter 8, we explore back-projection resolution by imaging M6 earthquakes within the Japan subduction zone. The quantitative analysis of uncertainties can provide guidelines for interpreting back-projection results in the region.

Finally, in Chapter 9, we discuss future research prospects of kinematic earthquake source imaging.