Hamid Mehrabi, Ph.D. ,

Assistant Professor

Department Of Geomatics Engineering
Faculty Of Civil Engineering And Transportation

Email

h.mehrabi@eng.ui.ac.ir

Address

University of Isfahan Azadi square Isfahan, Iran
Postal Code : 8174673441

Overview

Research Output

All

Article

2025

2014

Articles

2025

Enhanced land subsidence interpolation through a hybrid deep convolutional neural network and InSAR time series

( Article . Gold )

Azarm, Z., Mehrabi, H., Nadi, S.

Publication Date: 2025

Geoscientific Model Development (1991959X)18(19)pp. 6903-6919

Multichannel Monte Carlo Singular Spectrum Analysis with Colored Noise Assessment: Application to Greenland GNSS Vertical Displacement

( Article )

Esmaeili, F., Mehrabi, H., Khazraei, S.M., Amiri-simkooei, A.

Publication Date: 2025

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (21511535)

2021

Three-dimensional strain descriptors at the Earth’s surface through 3D retrieved co-event displacement fields of differential interferometric synthetic aperture radar

( Article )

Mehrabi, H.

Publication Date: 2021

Journal Of Geodesy (14321394)95(4)

2019

Three-dimensional displacement fields from insar through tikhonov regularization and least-squares variance component estimation

( Article . Green • Hybrid Gold )

Mehrabi, H., Voosoghi, B., Motagh m., M., Hanssen, R.F.

Publication Date: 2019

Journal of Surveying Engineering, - ASCE (07339453)145(4)

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. © 2019 This work is made available under the terms of the Creative Commons Attribution 4.0 International license,.

2018

On estimating the curvature attributes and strain invariants of deformed surface through radial basis functions

( Article )

Mehrabi, H., Voosoghi, B.

Publication Date: 2018

Computational and Applied Mathematics (18070302)37(2)pp. 978-995

View All (7)