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A novel step-like deformation model for reservoir landslide monitoring with multi-temporal InSAR.

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Title: A novel step-like deformation model for reservoir landslide monitoring with multi-temporal InSAR.
Authors: Liu, Guoshi1,2 (AUTHOR), Sun, Qian3 (AUTHOR) sandra@hunnu.edu.cn, Hu, Jun1 (AUTHOR), Liu, Leilei1 (AUTHOR), Zheng, Wanji1 (AUTHOR), Han, Bing4 (AUTHOR), Li, Junfeng4 (AUTHOR), Liu, Jihong5 (AUTHOR)
Source: SCIENCE CHINA Earth Sciences. Feb2026, Vol. 69 Issue 2, p679-701. 23p.
Subject Terms: *Radar interferometry, *Logistic functions (Mathematics), *Deformations (Mechanics), *Landslide dams, *Water levels, *Parameter estimation
Abstract: Reservoir landslides are significant geological hazards that pose severe risks to reservoir safety. Detecting the spatial-temporal evolution of slope movement is crucial for effective risk assessment and disaster mitigation. InSAR technology has been extensively employed to monitor surface deformations in reservoir landslides. However, the accuracy of InSAR-derived deformation fields is often limited by the reliability of prior deformation model. Traditional models, which primarily rely on linear or periodic function, frequently overlook the step-like evolution characteristics of reservoir landslides. To address this limitation, this study introduces a multi-temporal InSAR approach that incorporates Sigmoid function to enhance the deformation modeling of reservoir landslides. To solve the nonlinear parameters within the model, Taylor series expansion-based observation equation is constructed to estimate these parameters accurately. The proposed model was evaluated using both the simulated and real datasets from the Hongyanzi landslide in the Pubugou reservoir area. The results demonstrate that the proposed model significantly improves the accuracies of parameter estimation and deformation time-series. Experiments conducted under the sensitivity of interferogram stacks and varying atmospheric phase screen interference magnitudes further confirm the proposed model's robustness and application potential. In addition, the sensitivity analysis of the initial parameters in the real data experiment scenario demonstrates the robustness of the proposed model's nonlinear parameter estimation. Finally, the cross-correlation analysis reveals that the deformation of the Hongyanzi landslide is triggered by the decline of the reservoir water level, and quantitatively evaluates the lag time between the deformation and the reservoir water level. Our results offer novel insights for InSAR monitoring of other complex deformation evolution scenarios. Prior information is incorporated into the deformation modeling to estimate a more reliable InSAR deformation field. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 191574072
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Label: Title
  Group: Ti
  Data: A novel step-like deformation model for reservoir landslide monitoring with multi-temporal InSAR.
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  Data: <searchLink fieldCode="AR" term="%22Liu%2C+Guoshi%22">Liu, Guoshi</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Qian%22">Sun, Qian</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> sandra@hunnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Hu%2C+Jun%22">Hu, Jun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Leilei%22">Liu, Leilei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zheng%2C+Wanji%22">Zheng, Wanji</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Han%2C+Bing%22">Han, Bing</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Junfeng%22">Li, Junfeng</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Jihong%22">Liu, Jihong</searchLink><relatesTo>5</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22SCIENCE+CHINA+Earth+Sciences%22">SCIENCE CHINA Earth Sciences</searchLink>. Feb2026, Vol. 69 Issue 2, p679-701. 23p.
– Name: Subject
  Label: Subject Terms
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  Data: *<searchLink fieldCode="DE" term="%22Radar+interferometry%22">Radar interferometry</searchLink><br />*<searchLink fieldCode="DE" term="%22Logistic+functions+%28Mathematics%29%22">Logistic functions (Mathematics)</searchLink><br />*<searchLink fieldCode="DE" term="%22Deformations+%28Mechanics%29%22">Deformations (Mechanics)</searchLink><br />*<searchLink fieldCode="DE" term="%22Landslide+dams%22">Landslide dams</searchLink><br />*<searchLink fieldCode="DE" term="%22Water+levels%22">Water levels</searchLink><br />*<searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Reservoir landslides are significant geological hazards that pose severe risks to reservoir safety. Detecting the spatial-temporal evolution of slope movement is crucial for effective risk assessment and disaster mitigation. InSAR technology has been extensively employed to monitor surface deformations in reservoir landslides. However, the accuracy of InSAR-derived deformation fields is often limited by the reliability of prior deformation model. Traditional models, which primarily rely on linear or periodic function, frequently overlook the step-like evolution characteristics of reservoir landslides. To address this limitation, this study introduces a multi-temporal InSAR approach that incorporates Sigmoid function to enhance the deformation modeling of reservoir landslides. To solve the nonlinear parameters within the model, Taylor series expansion-based observation equation is constructed to estimate these parameters accurately. The proposed model was evaluated using both the simulated and real datasets from the Hongyanzi landslide in the Pubugou reservoir area. The results demonstrate that the proposed model significantly improves the accuracies of parameter estimation and deformation time-series. Experiments conducted under the sensitivity of interferogram stacks and varying atmospheric phase screen interference magnitudes further confirm the proposed model's robustness and application potential. In addition, the sensitivity analysis of the initial parameters in the real data experiment scenario demonstrates the robustness of the proposed model's nonlinear parameter estimation. Finally, the cross-correlation analysis reveals that the deformation of the Hongyanzi landslide is triggered by the decline of the reservoir water level, and quantitatively evaluates the lag time between the deformation and the reservoir water level. Our results offer novel insights for InSAR monitoring of other complex deformation evolution scenarios. Prior information is incorporated into the deformation modeling to estimate a more reliable InSAR deformation field. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s11430-025-1780-2
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 23
        StartPage: 679
    Subjects:
      – SubjectFull: Radar interferometry
        Type: general
      – SubjectFull: Logistic functions (Mathematics)
        Type: general
      – SubjectFull: Deformations (Mechanics)
        Type: general
      – SubjectFull: Landslide dams
        Type: general
      – SubjectFull: Water levels
        Type: general
      – SubjectFull: Parameter estimation
        Type: general
    Titles:
      – TitleFull: A novel step-like deformation model for reservoir landslide monitoring with multi-temporal InSAR.
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            NameFull: Liu, Guoshi
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            NameFull: Sun, Qian
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            NameFull: Hu, Jun
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            NameFull: Liu, Leilei
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            – D: 01
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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              Value: 69
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            – TitleFull: SCIENCE CHINA Earth Sciences
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