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Spatiotemporal Patterns of Seasonali...

Cohen-Waeber, Julien Francois.

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Spatiotemporal Patterns of Seasonality in Landslide Deformation from InSAR and GPS.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Spatiotemporal Patterns of Seasonality in Landslide Deformation from InSAR and GPS./
Author:	Cohen-Waeber, Julien Francois.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	138 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-03, Section: B.
Contained By:	Dissertations Abstracts International80-03B.
Subject:	Geological engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10822163
ISBN:	9780438325395

Spatiotemporal Patterns of Seasonality in Landslide Deformation from InSAR and GPS.
Cohen-Waeber, Julien Francois.

Spatiotemporal Patterns of Seasonality in Landslide Deformation from InSAR and GPS. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 138 p.

Source: Dissertations Abstracts International, Volume: 80-03, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2018.

This item must not be sold to any third party vendors.

High-resolution characterization of landslide deformation and its spatiotemporal response to external triggering mechanisms is a first step toward improved hazard forecasting. Slope instability in the San Francisco East Bay Hills (EBH), including the Lawrence Berkeley National Laboratory (LBL), has been a prevalent problem since development of the area began. The EBH are home to a number of very slowly moving (~20 mm/yr), earth and rock flow-type landslide complexes whose activity has been shown to vary spatiotemporally in response to seasonal precipitation and seismic activity. Advanced technologies such as Interferometric Synthetic Aperture Radar (InSAR) and continuous Global Positioning Systems (cGPS) are well suited for monitoring these types of processes, as they allow for remote detection and characterization of ground surface displacements with sub-centimeter precision and accuracy. Relying on InSAR and cGPS, two time histories of ground deformation with exceptionally high spatial and temporal resolution are produced for the EBH. The spatiotemporal patterns of variability in each of these signals are identified and related to different ground deformation mechanisms. After careful evaluation of nearly 50 inventoried landslide deposits, a network of 6 autonomous cGPS landslide monitoring stations was instrumented across four select sites. Established in 2012, the network is set to continue monitoring ground deformation at high rates (1Hz and 20Hz) through the foreseeable future. The methodology for this field instrumentation effort is described and the resulting time series are examined. The data reveals seasonally modulated shrink/swelling cycles of the surficial soils and downslope velocities indicative of landslide deformation. Relying on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSARTM), InSAR time series analysis produces a record of ground deformation over the same study area, with exceptionally dense spatial coverage. Through the use of functional curve fitting, and Principal and Independent Component Analyses the data reveals four distinct spatial and temporal surface deformation patterns which relate to different geo-mechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore-pressure changes controlled by annual seasonal cycles and multi-year drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings.

ISBN: 9780438325395Subjects--Topical Terms:

2122713
Geological engineering.

Spatiotemporal Patterns of Seasonality in Landslide Deformation from InSAR and GPS.
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500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Sitar, Nicholas;Burgmann, Roland.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a High-resolution characterization of landslide deformation and its spatiotemporal response to external triggering mechanisms is a first step toward improved hazard forecasting. Slope instability in the San Francisco East Bay Hills (EBH), including the Lawrence Berkeley National Laboratory (LBL), has been a prevalent problem since development of the area began. The EBH are home to a number of very slowly moving (~20 mm/yr), earth and rock flow-type landslide complexes whose activity has been shown to vary spatiotemporally in response to seasonal precipitation and seismic activity. Advanced technologies such as Interferometric Synthetic Aperture Radar (InSAR) and continuous Global Positioning Systems (cGPS) are well suited for monitoring these types of processes, as they allow for remote detection and characterization of ground surface displacements with sub-centimeter precision and accuracy. Relying on InSAR and cGPS, two time histories of ground deformation with exceptionally high spatial and temporal resolution are produced for the EBH. The spatiotemporal patterns of variability in each of these signals are identified and related to different ground deformation mechanisms. After careful evaluation of nearly 50 inventoried landslide deposits, a network of 6 autonomous cGPS landslide monitoring stations was instrumented across four select sites. Established in 2012, the network is set to continue monitoring ground deformation at high rates (1Hz and 20Hz) through the foreseeable future. The methodology for this field instrumentation effort is described and the resulting time series are examined. The data reveals seasonally modulated shrink/swelling cycles of the surficial soils and downslope velocities indicative of landslide deformation. Relying on TerraSAR-X satellite images (2009-2014) and an improved data processing algorithm (SqueeSARTM), InSAR time series analysis produces a record of ground deformation over the same study area, with exceptionally dense spatial coverage. Through the use of functional curve fitting, and Principal and Independent Component Analyses the data reveals four distinct spatial and temporal surface deformation patterns which relate to different geo-mechanical processes. Two components of time-dependent landslide deformation isolate continuous motion and motion driven by precipitation-modulated pore-pressure changes controlled by annual seasonal cycles and multi-year drought conditions. Two components capturing more widespread seasonal deformation separate precipitation-modulated soil swelling from annual cycles that may be related to groundwater level changes and thermal expansion of buildings.
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