Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data
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
Citation Formats
TY - DATA
AB - 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
AU - Reinisch, Elena
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO -
KW - energy
KW - PoroTomo
KW - InSAR
KW - time series
KW - temporal adjustment
KW - graph theory
KW - poroelastic tomography
KW - thesis
KW - paper
KW - model
KW - parameters
KW - modeling
KW - time-dependent
KW - time-varying
KW - weighted least-squares
KW - inversion
KW - radar
KW - interferometric
KW - synthetic aperture
KW - laplacian
KW - covariance
KW - matrix
KW - MatLab
KW - GraphTreeTA
KW - Alaska
KW - AK
KW - Okmok
KW - volcano
KW - magma
KW - volume
KW - method
KW - implementation
KW - application
KW - viscous
KW - flow
KW - viscoelastic relaxation
KW - remote sensing
LA - English
DA - 2016/07/28
PY - 2016
PB - University of Wisconsin
T1 - Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data
UR - https://data.openei.org/submissions/7226
ER -
Reinisch, Elena. Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data. University of Wisconsin, 28 July, 2016, GDR. https://gdr.openei.org/submissions/1075.
Reinisch, E. (2016). Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data. [Data set]. GDR. University of Wisconsin. https://gdr.openei.org/submissions/1075
Reinisch, Elena. Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data. University of Wisconsin, July, 28, 2016. Distributed by GDR. https://gdr.openei.org/submissions/1075
@misc{OEDI_Dataset_7226,
title = {Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data},
author = {Reinisch, Elena},
abstractNote = {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},
url = {https://gdr.openei.org/submissions/1075},
year = {2016},
howpublished = {GDR, University of Wisconsin, https://gdr.openei.org/submissions/1075},
note = {Accessed: 2025-04-24}
}
Details
Data from Jul 28, 2016
Last updated Jan 27, 2020
Submitted Jul 13, 2018
Organization
University of Wisconsin
Contact
Kurt Feigl
608.262.8960
Authors
Original Source
https://gdr.openei.org/submissions/1075Research Areas
Keywords
energy, PoroTomo, InSAR, time series, temporal adjustment, graph theory, poroelastic tomography, thesis, paper, model, parameters, modeling, time-dependent, time-varying, weighted least-squares, inversion, radar, interferometric, synthetic aperture, laplacian, covariance, matrix, MatLab, GraphTreeTA, Alaska, AK, Okmok, volcano, magma, volume, method, implementation, application, viscous, flow, viscoelastic relaxation, remote sensingDOE Project Details
Project Name PoroTomo Project
Project Lead Elisabet Metcalfe
Project Number EE0006760