Modeling slope instabilities with multi-temporal InSAR considering hydrogeological triggering factors: A case study across Badong County in the Three Gorges Area

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Zhuge Xia
  • Mahdi Motagh
  • Wandi Wang
  • Tao Li
  • Mimi Peng
  • Chao Zhou
  • Sadra Karimzadeh

External Research Organisations

  • Hohai University
  • Helmholtz Centre Potsdam - German Research Centre for Geosciences (GFZ)
  • Wuhan University
  • Xidian University
  • China University of Geosciences
  • University of Tabriz
  • Tokyo Institute of Technology
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Details

Original languageEnglish
Article number114212
Number of pages15
JournalRemote sensing of environment
Volume309
Early online date28 May 2024
Publication statusPublished - 1 Aug 2024

Abstract

Multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a widely used technique for monitoring subtle ground instabilities, with a precision ranging from centimeters to millimeters. Traditional MT-InSAR analysis often employs low-pass temporal filtering to suppress stochastic noise and extract deformation features from measurements. However, these approaches may hinder the detection and estimation of transient slope instabilities triggered by external factors. In this study, we propose a methodology for characterizing transient deformation of reservoir bank slopes under the coupling effects of rainfall and reservoir water level (RWL) changes. Following MT-InSAR analysis, slope kinematics is analyzed using time series decomposition and independent component analysis (ICA) to separate trends from seasonality. Although triggers of slope instability exhibit similar periods of increase and decrease, they are not entirely synchronized. Therefore, the seasonal components of surface deformation along with environmental triggers are analyzed using a wavelet transform to determine the time-lag between them. This helps define an effective priori search windows for constraining transient behaviors in landslide kinematics. A constrained least-squares optimization is finally applied to extract step-like kinematics features. Our methodology's effectiveness is evaluated using a dataset comprising 102 TerraSAR-X (TSX) images in High-resolution Spotlight (HS) mode, 197 Sentinel-1 images, 10 ALOS-1 and 12 ALOS-2 Stripmap images, collected from 2006 to 2022 across Badong County, located along the Yangtze River. After the successful validation against in-situ measurements and comparison with conventional post-processing strategies, we apply our method to generate a map of hazardous sliding areas and evaluate the regional-scale slope instability of slow-moving landslides across Badong County in the Three Gorges Area (TGA).

Keywords

    Independent Component Analysis (ICA), Multi-temporal InSAR (MT-InSAR), Satellite remote sensing, Slow-moving landslides, Three Gorges Area (TGA), Wavelet transform

ASJC Scopus subject areas

Cite this

Modeling slope instabilities with multi-temporal InSAR considering hydrogeological triggering factors: A case study across Badong County in the Three Gorges Area. / Xia, Zhuge; Motagh, Mahdi; Wang, Wandi et al.
In: Remote sensing of environment, Vol. 309, 114212, 01.08.2024.

Research output: Contribution to journalArticleResearchpeer review

Xia Z, Motagh M, Wang W, Li T, Peng M, Zhou C et al. Modeling slope instabilities with multi-temporal InSAR considering hydrogeological triggering factors: A case study across Badong County in the Three Gorges Area. Remote sensing of environment. 2024 Aug 1;309:114212. Epub 2024 May 28. doi: 10.1016/j.rse.2024.114212
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title = "Modeling slope instabilities with multi-temporal InSAR considering hydrogeological triggering factors: A case study across Badong County in the Three Gorges Area",
abstract = "Multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a widely used technique for monitoring subtle ground instabilities, with a precision ranging from centimeters to millimeters. Traditional MT-InSAR analysis often employs low-pass temporal filtering to suppress stochastic noise and extract deformation features from measurements. However, these approaches may hinder the detection and estimation of transient slope instabilities triggered by external factors. In this study, we propose a methodology for characterizing transient deformation of reservoir bank slopes under the coupling effects of rainfall and reservoir water level (RWL) changes. Following MT-InSAR analysis, slope kinematics is analyzed using time series decomposition and independent component analysis (ICA) to separate trends from seasonality. Although triggers of slope instability exhibit similar periods of increase and decrease, they are not entirely synchronized. Therefore, the seasonal components of surface deformation along with environmental triggers are analyzed using a wavelet transform to determine the time-lag between them. This helps define an effective priori search windows for constraining transient behaviors in landslide kinematics. A constrained least-squares optimization is finally applied to extract step-like kinematics features. Our methodology's effectiveness is evaluated using a dataset comprising 102 TerraSAR-X (TSX) images in High-resolution Spotlight (HS) mode, 197 Sentinel-1 images, 10 ALOS-1 and 12 ALOS-2 Stripmap images, collected from 2006 to 2022 across Badong County, located along the Yangtze River. After the successful validation against in-situ measurements and comparison with conventional post-processing strategies, we apply our method to generate a map of hazardous sliding areas and evaluate the regional-scale slope instability of slow-moving landslides across Badong County in the Three Gorges Area (TGA).",
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T1 - Modeling slope instabilities with multi-temporal InSAR considering hydrogeological triggering factors

T2 - A case study across Badong County in the Three Gorges Area

AU - Xia, Zhuge

AU - Motagh, Mahdi

AU - Wang, Wandi

AU - Li, Tao

AU - Peng, Mimi

AU - Zhou, Chao

AU - Karimzadeh, Sadra

N1 - Publisher Copyright: © 2024 Elsevier Inc.

PY - 2024/8/1

Y1 - 2024/8/1

N2 - Multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a widely used technique for monitoring subtle ground instabilities, with a precision ranging from centimeters to millimeters. Traditional MT-InSAR analysis often employs low-pass temporal filtering to suppress stochastic noise and extract deformation features from measurements. However, these approaches may hinder the detection and estimation of transient slope instabilities triggered by external factors. In this study, we propose a methodology for characterizing transient deformation of reservoir bank slopes under the coupling effects of rainfall and reservoir water level (RWL) changes. Following MT-InSAR analysis, slope kinematics is analyzed using time series decomposition and independent component analysis (ICA) to separate trends from seasonality. Although triggers of slope instability exhibit similar periods of increase and decrease, they are not entirely synchronized. Therefore, the seasonal components of surface deformation along with environmental triggers are analyzed using a wavelet transform to determine the time-lag between them. This helps define an effective priori search windows for constraining transient behaviors in landslide kinematics. A constrained least-squares optimization is finally applied to extract step-like kinematics features. Our methodology's effectiveness is evaluated using a dataset comprising 102 TerraSAR-X (TSX) images in High-resolution Spotlight (HS) mode, 197 Sentinel-1 images, 10 ALOS-1 and 12 ALOS-2 Stripmap images, collected from 2006 to 2022 across Badong County, located along the Yangtze River. After the successful validation against in-situ measurements and comparison with conventional post-processing strategies, we apply our method to generate a map of hazardous sliding areas and evaluate the regional-scale slope instability of slow-moving landslides across Badong County in the Three Gorges Area (TGA).

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KW - Satellite remote sensing

KW - Slow-moving landslides

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JO - Remote sensing of environment

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