Exploring PAZ co-polarimetric SAR data for surface movement mapping and scattering characterization

Ling Chang*, A. Stein

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

In this contribution, we investigate PAZ co-polarimetric SAR data applicability for surface movement mapping and scattering characterization. PAZ simultaneously collects SAR imagery in both VV and HH channels. Using a small stack of PAZ data, we apply the real-valued impulse response function correlation to identify constantly coherent scatterers (CCS), separately in VV and HH, in the course of time series InSAR (Interferometric SAR) processing. The proposed method has an advantage to selecting the CCS with minimal incoherent scatterer inclusion and exact radar location, which can eventually lead to the precise deformation time series estimations of all CCS, and a high-precision surface movement map. Moreover, we apply the co-polarimetric phase difference (CPD) method to classify the CCS in terms of scattering mechanisms which provides a new attribute to every individual CCS. We recognize the sibling pairs by both thresholding the spatial distance between any two CCS observed separately in VV and HH, and using common scattering characteristic as a new criterion. The deformation estimates of sibling pairs are used to reduce the biases in the deformation estimates of every ground target. The proposed methods are demonstrated in a test site, in the northern part of the Netherlands, using 10 co-polarimetric SAR data acquired between September 2019 and April 2020. The results show that sibling pairs behave a linear deformation trend over time, and that the other pairs show a correlation between their deformation and temperature, and the sibling pairs with the surface, dihedral, volume scattering mechanisms account for and , respectively. We conclude that by combining data from VV and HH polarization as siblings, PAZ co-polarimetric SAR data are highly suited to map surface changes and characterize surface features.
Original languageEnglish
Article number102280
Pages (from-to)1-11
Number of pages11
JournalInternational Journal of Applied Earth Observation and Geoinformation
Volume96
DOIs
Publication statusPublished - 1 Apr 2021

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-GOLD

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