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Spatiotemporal Patterns of Precipitation‐Modulated Landslide Deformation From Independent Component Analysis of InSAR Time Series
Author(s) -
CohenWaeber J.,
Bürgmann R.,
Chaussard E.,
Giannico C.,
Ferretti A.
Publication year - 2018
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2017gl075950
Subject(s) - interferometric synthetic aperture radar , landslide , geology , deformation (meteorology) , precipitation , series (stratigraphy) , deformation monitoring , time series , synthetic aperture radar , remote sensing , seismology , meteorology , geography , paleontology , oceanography , machine learning , computer science
Long‐term landslide deformation is disruptive and costly in urbanized environments. We rely on TerraSAR‐X satellite images (2009–2014) and an improved data processing algorithm (SqueeSAR™) to produce an exceptionally dense Interferometric Synthetic Aperture Radar ground deformation time series for the San Francisco East Bay Hills. Independent and principal component analyses of the time series reveal four distinct spatial and temporal surface deformation patterns in the area around Blakemont landslide, which we relate to different geomechanical 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 multiyear 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. High‐resolution characterization of landslide response to precipitation is a first step toward improved hazard forecasting.