TY - JOUR

T1 - Three-Dimensional Displacement Fields from InSAR through Tikhonov Regularization and Least-Squares Variance Component Estimation

AU - Mehrabi, Hamid

AU - Voosoghi, Behzad

AU - Motagh, Mahdi

AU - Hanssen, Ramon F.

N1 - Acknowledgements This is a contribution to VOLCAPSE, a research project funded by the European Research Council under the European Union’s H2020 Programme/ERC consolidator grant No. (ERC-CoG 646858), to the Research Network Geo.X, and to the Swedish Centre of Natural Hazards and Disaster Sciences (CNDS). F.M.S. is grateful to Stefano Serafin (University of Innsbruck) for providing great help to retrieve the atmospheric parameters for infrasound modeling. TerraSAR-X and TanDEM-X data are copyright of German Aerospace Agency (DLR) and were provided under the proposal IDs GEO1217, GEO1505, DEM_GEOL1196, and DEM_GEOL1670. We thank Mehdi Nikkhoo for contributing to the deformation modeling, and James Reynolds for sharing the drone videos. We thank Geoscience Australia, BMKG in Indonesia, and GEOFON (Germany) for making seismic data available.

PY - 2019/11

Y1 - 2019/11

N2 - Synthetic aperture radar interferometry (InSAR) measures the projection of three-dimensional (3D) ground displacement in the range direction and in the azimuth direction through image processing. The incapability of InSAR in measuring the 3D displacements restricts its capability for assessing real Earth surface deformation. The near-polar orbiting characteristics of InSAR missions reduce the sensitivity of line-of-sight (LOS) displacements significantly to the north-south components of the real 3D displacement fields and weaken the geometric strength of a given configuration. Applying range measurements from various missions to address 3D displacement leads to an ill-posed inverse problem that needs to be regularized. Moreover, it needs appropriate weighting of the observations to give proper estimates of the parameters. In this study, we propose Tikhonov regularization (TR) and least-squares variance component estimation (LS-VCE) methods for retrieving 3D displacement vectors from range and azimuth displacements. Depending on the functional degree of freedom (DoF) of the inverse problem, the TR and LS-VCE methods are applied in determined and overdetermined equation systems, respectively, to stabilize the ill-conditioned models and estimate the variance components of observations. These methods were evaluated by two synthetic data sets and a real data set from the Sentinel-1 terrain observation by progressive scan (TOPS) and ALOS-2 phased array type L-band synthetic aperture radar (PALSAR-2) missions in 2015 of the MW = 8.3 Illapel earthquake in Chile. Results indicate more than 40% improvement in both the precision and accuracy of retrieving 3D deformation fields when the regularized LS-VCE (RLS-VCE) is adopted instead of the conventional method (CM) that considers primary weighting for observations. Applying the range and azimuth InSAR displacements together with adopting the LS-VCE method reveal a north-south convergent borderline near 31.2° S in the 2015 Illapel earthquake.

AB - Synthetic aperture radar interferometry (InSAR) measures the projection of three-dimensional (3D) ground displacement in the range direction and in the azimuth direction through image processing. The incapability of InSAR in measuring the 3D displacements restricts its capability for assessing real Earth surface deformation. The near-polar orbiting characteristics of InSAR missions reduce the sensitivity of line-of-sight (LOS) displacements significantly to the north-south components of the real 3D displacement fields and weaken the geometric strength of a given configuration. Applying range measurements from various missions to address 3D displacement leads to an ill-posed inverse problem that needs to be regularized. Moreover, it needs appropriate weighting of the observations to give proper estimates of the parameters. In this study, we propose Tikhonov regularization (TR) and least-squares variance component estimation (LS-VCE) methods for retrieving 3D displacement vectors from range and azimuth displacements. Depending on the functional degree of freedom (DoF) of the inverse problem, the TR and LS-VCE methods are applied in determined and overdetermined equation systems, respectively, to stabilize the ill-conditioned models and estimate the variance components of observations. These methods were evaluated by two synthetic data sets and a real data set from the Sentinel-1 terrain observation by progressive scan (TOPS) and ALOS-2 phased array type L-band synthetic aperture radar (PALSAR-2) missions in 2015 of the MW = 8.3 Illapel earthquake in Chile. Results indicate more than 40% improvement in both the precision and accuracy of retrieving 3D deformation fields when the regularized LS-VCE (RLS-VCE) is adopted instead of the conventional method (CM) that considers primary weighting for observations. Applying the range and azimuth InSAR displacements together with adopting the LS-VCE method reveal a north-south convergent borderline near 31.2° S in the 2015 Illapel earthquake.

KW - Differential synthetic aperture radar interferometry (D-InSAR)

KW - Least-squares variance component estimation

KW - Three-dimensional (3D) displacement fields

KW - Tikhonov regularization method

UR - http://www.scopus.com/inward/record.url?scp=85070556502&partnerID=8YFLogxK

U2 - 10.1061/(ASCE)SU.1943-5428.0000289

DO - 10.1061/(ASCE)SU.1943-5428.0000289

M3 - Article

AN - SCOPUS:85070556502

VL - 145

JO - Journal of Surveying Engineering, - ASCE

JF - Journal of Surveying Engineering, - ASCE

SN - 0733-9453

IS - 4

M1 - 04019011

ER -