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Statistical and Geospatial Analysis ...

Girven, Erin.

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Statistical and Geospatial Analysis of InSAR Data for Characterization of Processes Controlling Motion of the Slow-Moving Berkeley Landslides.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical and Geospatial Analysis of InSAR Data for Characterization of Processes Controlling Motion of the Slow-Moving Berkeley Landslides./
Author:	Girven, Erin.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	90 p.
Notes:	Source: Masters Abstracts International, Volume: 81-04.
Contained By:	Masters Abstracts International81-04.
Subject:	Geology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13886139
ISBN:	9781085775380

Statistical and Geospatial Analysis of InSAR Data for Characterization of Processes Controlling Motion of the Slow-Moving Berkeley Landslides.
Girven, Erin.

Statistical and Geospatial Analysis of InSAR Data for Characterization of Processes Controlling Motion of the Slow-Moving Berkeley Landslides. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 90 p.

Source: Masters Abstracts International, Volume: 81-04.

Thesis (M.S.)--State University of New York at Buffalo, 2019.

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

Understanding seasonal processes is paramount in characterizing hazard of slow-moving landslides, but is often limited by the temporal and spatial resolution of ground-based and satellite data. Here we use time-series analysis of 2009-2014 TerraSAR-X InSAR data with as low as 11-day repeat pass and 463, 372 pixels covering the four slow-moving landslides in the Berkeley Hills region of northern California. These slides cause long-term structural damage to buildings and underground infrastructure. Combination of TerraSAR-X observations with ascending RSAT2 observations allows an estimation of vertical and downslope horizontal components of motion for each slide. Using the more robust TerraSAR-X satellite data, we then use Principal Component and Independent Component Analyses (PCA and ICA, respectively), to isolate four components of slide motion at each of four slides. Three of these trends exhibit seasonal components of motion. Cross-correlation with temperature and precipitation show complex relationships between hillslope motion and seasonal cyclings, and a direct relationship between slide cumulative precipitation and slide acceleration at a lag of 30 days.

ISBN: 9781085775380Subjects--Topical Terms:

516570
Geology.
Subjects--Index Terms:

Independent component analysis

Statistical and Geospatial Analysis of InSAR Data for Characterization of Processes Controlling Motion of the Slow-Moving Berkeley Landslides.
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245 1 0 $a Statistical and Geospatial Analysis of InSAR Data for Characterization of Processes Controlling Motion of the Slow-Moving Berkeley Landslides.
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300 $a 90 p.
500 $a Source: Masters Abstracts International, Volume: 81-04.
500 $a Advisor: Bursik, Marcus.
502 $a Thesis (M.S.)--State University of New York at Buffalo, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Understanding seasonal processes is paramount in characterizing hazard of slow-moving landslides, but is often limited by the temporal and spatial resolution of ground-based and satellite data. Here we use time-series analysis of 2009-2014 TerraSAR-X InSAR data with as low as 11-day repeat pass and 463, 372 pixels covering the four slow-moving landslides in the Berkeley Hills region of northern California. These slides cause long-term structural damage to buildings and underground infrastructure. Combination of TerraSAR-X observations with ascending RSAT2 observations allows an estimation of vertical and downslope horizontal components of motion for each slide. Using the more robust TerraSAR-X satellite data, we then use Principal Component and Independent Component Analyses (PCA and ICA, respectively), to isolate four components of slide motion at each of four slides. Three of these trends exhibit seasonal components of motion. Cross-correlation with temperature and precipitation show complex relationships between hillslope motion and seasonal cyclings, and a direct relationship between slide cumulative precipitation and slide acceleration at a lag of 30 days.
590 $a School code: 0656.
650 4 $a Geology. $3 516570
650 4 $a Geophysics. $3 535228
650 4 $a Remote sensing. $3 535394
653 $a Independent component analysis
653 $a InSAR
653 $a Landslides
653 $a Slow-moving
653 $a California
690 $a 0372
690 $a 0373
690 $a 0799
710 2 $a State University of New York at Buffalo. $b Geology. $3 3276846
773 0 $t Masters Abstracts International $g 81-04.
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793 $a English
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