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Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data

Metadata Updated: June 25, 2021

Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence graph. The edge-vertex incidence matrix and the normalized edge Laplacian matrix are factors in the covariance matrix for the pair-wise data. Using empirical measures of residual scatter in the pair-wise observations, we estimate the variance at each epoch by inverting the covariance of the pair-wise data. We evaluate the rank deficiency of the corresponding least-squares problem via the edge-vertex incidence matrix. We implement our method in a MATLAB software package called GraphTreeTA available on GitHub (https://github.com/feigl/gipht). We apply temporal adjustment to the data set described in Lu et al. (2005) at Okmok volcano, Alaska, which erupted most recently in 1997 and 2008. The data set contains 44 differential volumetric changes and uncertainties estimated from interferograms between 1997 and 2004. Estimates show that approximately half of the magma volume lost during the 1997 eruption was recovered by the summer of 2003. Between June 2002 and September 2003, the estimated rate of volumetric increase is (6.2 +/- 0.6) x 10^6 m^3/yr. Our preferred model provides a reasonable fit that is compatible with viscoelastic relaxation in the five years following the 1997 eruption. Although we demonstrate the approach using volumetric rates of change, our formulation in terms of incidence graphs applies to any quantity derived from pair-wise differences, such as wrapped phase or wrapped residuals.

Date of final oral examination: 05/19/2016 This thesis is approved by the following members of the Final Oral Committee: Kurt L. Feigl, Professor, Geoscience Michael Cardiff, Assistant Professor, Geoscience Clifford H. Thurber, Vilas Distinguished Professor, Geoscience

Access & Use Information

Public: This dataset is intended for public access and use. License: Creative Commons Attribution

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Dates

Metadata Created Date June 24, 2021
Metadata Updated Date June 25, 2021

Metadata Source

Harvested from OpenEI data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date June 24, 2021
Metadata Updated Date June 25, 2021
Publisher University of Wisconsin
Maintainer
Identifier https://data.openei.org/submissions/3734
Data First Published 2016-07-28T06:00:00Z
Data Last Modified 2020-01-27T22:40:32Z
Public Access Level public
Bureau Code 019:20
Metadata Context https://openei.org/data.json
Metadata Catalog ID https://openei.org/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Data Quality True
Harvest Object Id 5f0f65b1-f8e8-4150-8120-b60352ce7abf
Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
Harvest Source Title OpenEI data.json
Homepage URL https://gdr.openei.org/submissions/1075
License https://creativecommons.org/licenses/by/4.0/
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Program Code 019:006
Projectlead Elisabet Metcalfe
Projectnumber EE0006760
Projecttitle PoroTomo Project
Source Datajson Identifier True
Source Hash a2257d0e1d31afc3c8dc5275037d2f65cf056480
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