Interferometry phase recovery and deformation extraction in low-coherence UHV transmission corridors of complex mountainous regions

The construction of ultra-high voltage (UHV) transmission corridors often spans complex mountainous regions, which are characterized by intricate geographical environments and frequent geological hazards. This study aims to improve deformation monitoring in low-coherence areas of UHV transmission corridors, such as those with dense vegetation, by utilizing Distributed Scatterer Interferometry (DS-InSAR). Using Sentinel-1A data, long-term deformation time series were derived. Compared to traditional time-series InSAR methods, DS-InSAR demonstrated significant improvements across several dimensions. Specifically, phase quality was notably enhanced after optimization using the Phase Linking method, resulting in clearer deformation region boundaries and a significant reduction in noise. Additionally, the number of effective monitoring points increased from 1,481 to 7,698, leading to more densely distributed and reliable deformation results. The annual average deformation rates extracted by traditional time-series InSAR ranged from −146 to 49 mm/year, while those obtained by DS-InSAR ranged from −144 to 74 mm/year. While the overall deformation trends were similar, the traditional time-series InSAR technique slightly overestimated the deformation magnitude. This study provides theoretical support for key technologies in deformation extraction for low-coherence areas in UHV transmission corridor construction.

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Publication Details

Journal
Frontiers in Earth Science
Published
2025-12-18
DOI
https://doi.org/10.3389/feart.2025.1682093
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
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article

Interferometry phase recovery and deformation extraction in low-coherence UHV transmission corridors of complex mountainous regions

Yeong-Min Do, Yi Liu, Bin Liu, Hao Han et al.
Frontiers in Earth Science
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Interferometry phase recovery and deformation extraction in low-coherence UHV transmission corridors of complex mountainous regions

Yeong-Min Do, Yi Liu, Bin Liu, Hao Han, Binbin Zhao, Xiaoang Kong, Shenli Wang
article en

Abstract

The construction of ultra-high voltage (UHV) transmission corridors often spans complex mountainous regions, which are characterized by intricate geographical environments and frequent geological hazards. This study aims to improve deformation monitoring in low-coherence areas of UHV transmission corridors, such as those with dense vegetation, by utilizing Distributed Scatterer Interferometry (DS-InSAR). Using Sentinel-1A data, long-term deformation time series were derived. Compared to traditional time-series InSAR methods, DS-InSAR demonstrated significant improvements across several dimensions. Specifically, phase quality was notably enhanced after optimization using the Phase Linking method, resulting in clearer deformation region boundaries and a significant reduction in noise. Additionally, the number of effective monitoring points increased from 1,481 to 7,698, leading to more densely distributed and reliable deformation results. The annual average deformation rates extracted by traditional time-series InSAR ranged from −146 to 49 mm/year, while those obtained by DS-InSAR ranged from −144 to 74 mm/year. While the overall deformation trends were similar, the traditional time-series InSAR technique slightly overestimated the deformation magnitude. This study provides theoretical support for key technologies in deformation extraction for low-coherence areas in UHV transmission corridor construction.

Frontiers in Earth ScienceVol. 13
State Grid Corporation of China (China) (CN)
Openalex Percentile: Top 48%
Synthetic Aperture Radar (SAR) Applications and Techniques
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Interferometry phase recovery and deformation extraction in low-coherence UHV transmission corridors of complex mountainous regions — Yeong-Min Do, Yi Liu, et al. · Frontiers in Earth Science (2025) | TGRS Research Map | TGRS