Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation
Geodetic measurements of surface deformation have been used for several decades to study how the Earth's surface responds to a wide range of geophysical processes. Geodetic time series acquired over a finite spatial extent can be used to quantify the time dependence of surface strain for a wide...
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ftdatacite:10.7907/z9hd7snp 2023-05-15T16:21:49+02:00 Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation Riel, Bryan Valmonte 2017 PDF https://dx.doi.org/10.7907/z9hd7snp https://resolver.caltech.edu/CaltechTHESIS:10032016-210146623 en eng California Institute of Technology No commercial reproduction, distribution, display or performance rights in this work are provided. Hydrology GPS InSAR Geophysics FOS Earth and related environmental sciences Geodesy Transient detection Volcanology Thesis Text Dissertation thesis 2017 ftdatacite https://doi.org/10.7907/z9hd7snp 2021-11-05T12:55:41Z Geodetic measurements of surface deformation have been used for several decades to study how the Earth's surface responds to a wide range of geophysical processes. Geodetic time series acquired over a finite spatial extent can be used to quantify the time dependence of surface strain for a wide range of spatial and temporal scales. In this thesis, we present a new method for automatically decomposing geodetic time series into temporal components corresponding to different geophysical processes. This method relies on constructing an overcomplete temporal dictionary of reference functions such that any geodetic signal can be described by a linear combination of the functions in the dictionary. By solving a linear least squares problem with sparsity-inducing regularization, we can limit the total number of dictionary elements needed to reconstruct a signal. In Chapter 2, we present the development of this method in the context of transient detection, where we define transient deformation as nonperiodic, nonsecular accumulation of strain in the crust. The sparsity regularization term automatically localizes the dominant timescales and onset times of any transient signals. We apply this method to Global Positioning System (GPS) data for a slow slip event in the Cascadia subduction zone while incorporating a spatial weighting scheme that filters for spatially coherent signals. In Chapter 3, we use a combination of unique space geodetic measurements and seismic observations to study the 2014 collapse of Bárðarbunga Caldera in Iceland associated with a major eruption event. The eruption sequence, which involved deflation of a magma chamber underneath the caldera and emplacement of a dike leading to lava flow, resulted in rapid subsidence of the glacier surface overlying the caldera and wide-scale ground deformation encompassing the rift zone associated with the dike emplacement. We present a model of the collapse that suggests that the majority of the observed subsidence occurs aseismically via a deflating sill-like magma chamber. In Chapter 4, we extend upon the transient detection framework presented in Chapter 2 to study complex surface deformation over groundwater basins near Los Angeles, California. We develop a distributed time series analysis framework based on the sparse estimation techniques of Chapter 2 and apply it to an 18-year interferometric synthetic aperture radar (InSAR) time series covering the Los Angeles area. We compare long- and short-term ground deformation signals to hydraulic head data from monitoring wells to understand the mechanical link between pressure variations in subsurface aquifers and observed ground deformation. Thesis glacier Iceland DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Hydrology GPS InSAR Geophysics FOS Earth and related environmental sciences Geodesy Transient detection Volcanology |
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Hydrology GPS InSAR Geophysics FOS Earth and related environmental sciences Geodesy Transient detection Volcanology Riel, Bryan Valmonte Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation |
topic_facet |
Hydrology GPS InSAR Geophysics FOS Earth and related environmental sciences Geodesy Transient detection Volcanology |
description |
Geodetic measurements of surface deformation have been used for several decades to study how the Earth's surface responds to a wide range of geophysical processes. Geodetic time series acquired over a finite spatial extent can be used to quantify the time dependence of surface strain for a wide range of spatial and temporal scales. In this thesis, we present a new method for automatically decomposing geodetic time series into temporal components corresponding to different geophysical processes. This method relies on constructing an overcomplete temporal dictionary of reference functions such that any geodetic signal can be described by a linear combination of the functions in the dictionary. By solving a linear least squares problem with sparsity-inducing regularization, we can limit the total number of dictionary elements needed to reconstruct a signal. In Chapter 2, we present the development of this method in the context of transient detection, where we define transient deformation as nonperiodic, nonsecular accumulation of strain in the crust. The sparsity regularization term automatically localizes the dominant timescales and onset times of any transient signals. We apply this method to Global Positioning System (GPS) data for a slow slip event in the Cascadia subduction zone while incorporating a spatial weighting scheme that filters for spatially coherent signals. In Chapter 3, we use a combination of unique space geodetic measurements and seismic observations to study the 2014 collapse of Bárðarbunga Caldera in Iceland associated with a major eruption event. The eruption sequence, which involved deflation of a magma chamber underneath the caldera and emplacement of a dike leading to lava flow, resulted in rapid subsidence of the glacier surface overlying the caldera and wide-scale ground deformation encompassing the rift zone associated with the dike emplacement. We present a model of the collapse that suggests that the majority of the observed subsidence occurs aseismically via a deflating sill-like magma chamber. In Chapter 4, we extend upon the transient detection framework presented in Chapter 2 to study complex surface deformation over groundwater basins near Los Angeles, California. We develop a distributed time series analysis framework based on the sparse estimation techniques of Chapter 2 and apply it to an 18-year interferometric synthetic aperture radar (InSAR) time series covering the Los Angeles area. We compare long- and short-term ground deformation signals to hydraulic head data from monitoring wells to understand the mechanical link between pressure variations in subsurface aquifers and observed ground deformation. |
format |
Thesis |
author |
Riel, Bryan Valmonte |
author_facet |
Riel, Bryan Valmonte |
author_sort |
Riel, Bryan Valmonte |
title |
Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation |
title_short |
Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation |
title_full |
Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation |
title_fullStr |
Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation |
title_full_unstemmed |
Automatic Decomposition of Geodetic Time Series for Studies of Ground Deformation |
title_sort |
automatic decomposition of geodetic time series for studies of ground deformation |
publisher |
California Institute of Technology |
publishDate |
2017 |
url |
https://dx.doi.org/10.7907/z9hd7snp https://resolver.caltech.edu/CaltechTHESIS:10032016-210146623 |
genre |
glacier Iceland |
genre_facet |
glacier Iceland |
op_rights |
No commercial reproduction, distribution, display or performance rights in this work are provided. |
op_doi |
https://doi.org/10.7907/z9hd7snp |
_version_ |
1766009800139735040 |