Deformation monitoring using time-series InSAR with dual-polarization optimization

doi:10.6046/zrzyyg.2024346

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Abstract

The spatial density and interferometric phase quality of high-quality monitoring points serve as key indicators for deformation monitoring using the time-series interferometric synthetic aperture radar (InSAR) technique. To further enhance the deformation monitoring ability of the InSAR technique for non-urban areas, this study proposed a polarization time-series InSAR method that takes into account distributed scatterers (DSs) using dual-polarization images from Sentinel-1. Specifically, polarization processing of the intensity and phase information of time-series SAR data was conducted using various methods based on the characteristics of DSs and taking the dispersion of amplitude (DA) as an indicator for the phase quality assessment. Then, surface deformation monitoring was performed using the data before and after optimization. This study carried out experiments on Ningbo City in Zhejiang Province using 40 scenes of dual-polarization (VV-VH) images from Sentinel-1. The results indicate that the proposed method can significantly increase the density of monitoring points and the interferometric phase quality. Compared to single polarization, the proposed method increased the quantities of persistent scatterers (PSs) and DSs by about 20% and 57.5%, respectively. Furthermore, the interferometric phase quality was also significantly improved, with the average coherence increasing by more than 15%. The proposed method allows for a more detailed reflection of regional deformations.

Keywords polarization time-series InSAR technique dual-polarization images from Sentinel-1 deformation monitoring of complex terrain

ZTFLH:	TP79
	P237

Issue Date: 31 December 2025

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	Jiabin XUAN
	Ruren LI
	Wenxue FU

Cite this article:

Jiabin XUAN,Ruren LI,Wenxue FU. Deformation monitoring using time-series InSAR with dual-polarization optimization[J]. Remote Sensing for Natural Resources, 2025, 37(6): 128-137.

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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024346 OR https://www.gtzyyg.com/EN/Y2025/V37/I6/128

Fig.1 Topographic map of study area

Fig.2 Land cover classification and satellite image map of the study area

Fig.3 Processing flow of dual-polarization time-series InSAR deformation monitoring

Fig.4 Search results of polarization space parameters of SAR pixels

Fig.5 Convergence analysis of the PSO algorithm

Fig.6 Plot of average intensity for different polarisation models

Fig.7 Comparison of the number of PS points in 2 typical areas

Tab.1 Number of PS points selected under different thresholds

Fig.8 Comparison of the number of identified homogeneous pixels

Fig.9 Comparison diagram of DS point identification distribution

Fig.10 Comparison of local area interferograms before and after optimization

Tab.2 Interferogram quality evaluation results

Fig.11 Surface deformation rate map of the study area

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