Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

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

Metadata Updated: January 20, 2025

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

Downloads & Resources

Dates

Metadata Created Date January 11, 2025
Metadata Updated Date January 20, 2025

Metadata Source

Harvested from OpenEI data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date January 11, 2025
Metadata Updated Date January 20, 2025
Publisher University of Wisconsin
Maintainer
Identifier https://data.openei.org/submissions/7226
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
Datagov Dedupe Retained 20250120155001
Harvest Object Id 9b78419c-0b95-4dad-8887-8a5ca48c1433
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/
Old Spatial {"type":"Polygon","coordinates":-119.2167,39.5883,-118.8167,39.5883,-118.8167,39.9883,-119.2167,39.9883,-119.2167,39.5883}
Program Code 019:006
Projectlead Elisabet Metcalfe
Projectnumber EE0006760
Projecttitle PoroTomo Project
Source Datajson Identifier True
Source Hash 3b0841004fd3858e970bc20d04688080db4da357520f15a970c4b58f11664bf7
Source Schema Version 1.1
Spatial {"type":"Polygon","coordinates":-119.2167,39.5883,-118.8167,39.5883,-118.8167,39.9883,-119.2167,39.9883,-119.2167,39.5883}

Didn't find what you're looking for? Suggest a dataset here.