Estimating spatiotemporal ground deformation with improved persistent-scatterer radar interferometry

Guoxiang Liu, Sean M. Buckley, Xiaoli Ding, Qiang Chen, Xiaojun Luo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

50 Citations (Scopus)

Abstract

Synthetic aperture radar interferometry has been applied widely in recent years to ground deformation monitoring although difficulties are often encountered when applying the technology, among which the spatial and temporal decorrelation and atmospheric artifacts are the most prominent. The persistent-scatterer interferometric synthetic aperture radar (PS-InSAR) technique has overcome some of the difficulties by focusing only on the temporally coherent radar targets in a time series of synthetic aperture radar (SAR) images. This paper presents an improved PS-InSAR technique by introducing PS-neighborhood networking and empirical mode decomposition (EMD) approaches in the PS-InSAR solution. Linear deformation rates and topographic errors are estimated based on a least squares method, while the nonlinear deformation and atmospheric signals are computed by singular value decomposition and the EMD method. An area in Phoenix, AZ, is used as a test site to determine its historical subsidence with 39 C-band SAR images acquired by European Remote Sensing 1 and 2 satellites from 1992 to 2000.
Original languageEnglish
Article number5210230
Pages (from-to)3209-3219
Number of pages11
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume47
Issue number9
DOIs
Publication statusPublished - 1 Sep 2009

Keywords

  • Atmospheric signal
  • Empirical mode decomposition (EMD)
  • Ground deformation
  • Persistent-scatterer (PS) networking
  • Radar interferometry

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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