Abstract
Volcanic eruptions are one of the most threatening natural hazards that require to be continuously monitored to prevent tragic events. The eruption at volcanoes usually manifest mantle motions and large-scale tectonic movements, however a nearby earthquake can also trigger seismicity and disturb a volcanic system. Since the activity of the volcanoes including inflation or deflation are usually accompanied by ground surface deformation, one of the tools to monitor their activities is to measure the surface displacements using space geodesy. Interferometric synthetic aperture radar is a technique that can measure ground surface displacements with sub-centimeter accuracy. In practice, every volcano possesses special characteristics and geographical location that might be challenging for space measurements. The challenge includes decorrelation of interferograms because of snowfall and vegetation, or a non-linear change in time. In this study, we first investigate the non-linear phase linking methods in high resolution and implement the state-of-art techniques in the MIami Phase Linking in Python software (MiaplPy). We assess the decorrelation models and the contribution of systematic bias in InSAR time series. Then we compare the error propagation for different unwrapping networks using L- and L2-norm minimization. We then apply the software to volcanic systems in Ecuador and western North America. We study the shallow hydrothermal system at Guagua Pichincha and magmatic system underneath Chiles-Cerro Negro volcanic complex and Cayambe in Ecuador using InSAR measurements and geodetic modelling and we investigate the possible earthquake triggering activities.