AUTHOR=Zhu Chuanguang , Long Sichun , Zhang Jixian , Wu Wenhao , Zhang Liya 

TITLE=Time Series Multi-Sensors of Interferometry Synthetic Aperture Radar for Monitoring Ground Deformation

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2022.929958

DOI=10.3389/fenvs.2022.929958

ISSN=2296-665X

ABSTRACT=A stack of images is a prerequisite for the multi-temporal interferometric synthetic aperture radar (MT-InSAR) due to the wrapped nature of the interferometric phase. Although SBAS technique can relieve the requirement of the amount of SAR data, a dozens of SAR acquisitions could be regarded as the minimum requirement. However, due to the limitation of imaging capability of spaceborne SAR system, the amount of available SAR data acquired from only one SAR sensor is often not enough to satisfy the requirement for phase unwrapping based on the Nyquist sampling assumption. Fortunately, there sometimes maybe more than one SAR stacks, i.e. stacks of SAR data acquired from different SAR systems. In this paper we propose a methodology to detect ground deformation by combining multiple SAR images acquired from different satellite systems for MT-InSAR analysis. Firstly, the low-pass deformation is estimated based on time series SAR acquisitions with low spatial resolution and long wavelength such as ENVISAT ASAR (ASAR). This information is then incorporated into the processing of time series of SAR acquisitions with high spatial resolution and short wavelength, such as TerraSAR-X (TSX). Specifically, the low-pass deformation will be subtracted from each differential interferograms generated from short-wavelength SAR images, and the rest of MT-InSAR analysis will be based on the double-differentiation interferograms. Then, the residual deformation will be calculated from these double-differentiation interferograms and together with the low-pass deformation forms the full deformation. As the principal component of deformation has already been subtracted, the phase gradient of those double-differentiated interferograms will be smooth enough to facilitate the phase unwrapping. Between January 2009 and September 2010, 14 ASAR images and 11 TSX images acquired from Tianjin, China are selected as the test data. A root mean square error (RMSE) of 9.1 mm/year is achieved from 11 TSX images while a RMSE of 3.7 mm/year from 14 ASAR images. However, a RMSE of 1.6 mm/year is achieved when integrating 11 TSX images and 14 ASAR images for MT-InSAR analysis. The experiments show that the proposed method can effectively detect the ground deformation.