InSAR monitoring of creeping landslides in mountainous regions: A case study in Eldorado National Forest, California

Kang, Ya; Lü, Zhong; Zhao, Chaoying; Xu, Yuankun; Kim, Jin-Woo; Gallegos, Alan J.

doi:10.1016/j.rse.2021.112400

“…Precipitation, subsequent infiltration, and elevated pore-water pressure can result in landslide movement [5]. To find the linkage between rainfall and slope destabilization, the precipitation record can be used to establish a simple 1-dimensional (1D) pore-water pressure diffusion model [5,[73][74][75][76]:…”

Section: Understanding the Delay Between Landslide Movement And Precipitation-pore-water Pressure Diffusion Modelingmentioning

confidence: 99%

“…The pore-water pressure can be solved via Fourier transforms [73][74][75][76] to obtain hydraulic diffusivity and study the correlation (and time lag) between the observed landslide movement time-series and precipitation record.…”

Section: Understanding the Delay Between Landslide Movement And Precipitation-pore-water Pressure Diffusion Modelingmentioning

confidence: 99%

A Framework for Studying Hydrology-Driven Landslide Hazards in Northwestern US Using Satellite InSAR, Precipitation and Soil Moisture Observations: Early Results and Future Directions

Lü

¹

,

Kim

²

2021

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The mountainous Pacific Northwest is prone to heavy winter rainfall, resulting in hundreds of landslides per year, human casualties, and billions of dollars of property damage. Precipitation is a major hydrologic trigger for landslides in the northwestern US and around the world. This paper reviews existing literature to outline a framework to study the linkage between precipitation and landslide hazards over the northwestern US using satellite remote sensing techniques including interferometric synthetic aperture radar (InSAR) methods, Tropical Rainfall Measuring Mission (TRMM) satellite precipitation products, and Soil Moisture Active Passive (SMAP) satellite soil moisture data, along with correlation analysis and numerical modeling. InSAR time-series displacements provide an indication of landslide occurrence and extent, and help characterize the basal slip surface and slide-body volume based on the law of mass conservation. Precipitation and soil moisture sensed from the space and ground contribute to creating hydrogeological models associated with water infiltration. These crucial parameters are tracked through correlation and slope stability analysis to understand landslide dynamics. We highlight the results on mapping landslides over the state of Washington and analyses at a few select sites over southern Washington and southwestern Oregon. We conclude that satellite observations of landslide motions and the attributing hydrological variables from both radar and optical images improve our understanding of the inter-relationships between the hydrologic processes along with topographic and geologic settings, and the landslide kinematics and mechanisms inferred from time-series measurements and landslide modeling on a regional scale.

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“…The estimation error of the atmospheric phase screen (tropospheric delay) due to the high elevation relief variation is a critical factor influencing the application of MT-InSAR [52,53]. In some SBAS processing chains, interferometric atmospheric phase delay corrections were implemented by global meteorological reanalysis data or simulated by linear or power-law models [54,55]. It is challenging to accurately estimate the vertically stratified component due to the enormous relief elevation variation [54,55].…”

Section: Introductionmentioning

confidence: 99%

“…In some SBAS processing chains, interferometric atmospheric phase delay corrections were implemented by global meteorological reanalysis data or simulated by linear or power-law models [54,55]. It is challenging to accurately estimate the vertically stratified component due to the enormous relief elevation variation [54,55].…”

Section: Introductionmentioning

confidence: 99%

Detecting Rock Glacier Displacement in the Central Himalayas Using Multi-Temporal InSAR

Zhang

¹

,

Feng

²

,

Zhang

³

et al. 2021

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Rock glaciers represent typical periglacial landscapes and are distributed widely in alpine mountain environments. Rock glacier activity represents a critical indicator of water reserves state, permafrost distribution, and landslide disaster susceptibility. The dynamics of rock glacier activity in alpine periglacial environments are poorly quantified, especially in the central Himalayas. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been shown to be a useful technique for rock glacier deformation detection. In this study, we developed a multi-baseline persistent scatterer (PS) and distributed scatterer (DS) combined MT-InSAR method to monitor the activity of rock glaciers in the central Himalayas. In periglacial landforms, the application of the PS interferometry (PSI) method is restricted by insufficient PS due to large temporal baseline intervals and temporal decorrelation, which hinder comprehensive measurements of rock glaciers. Thus, we first evaluated the rock glacier interferometric coherence of all possible interferometric combinations and determined a multi-baseline network based on rock glacier coherence; then, we constructed a Delaunay triangulation network (DTN) by exploiting both PS and DS points. To improve the robustness of deformation parameters estimation in the DTN, we combined the Nelder–Mead algorithm with the M-estimator method to estimate the deformation rate variation at the arcs of the DTN and introduced a ridge-estimator-based weighted least square (WLR) method for the inversion of the deformation rate from the deformation rate variation. We applied our method to Sentinel-1A ascending and descending geometry data (May 2018 to January 2019) and obtained measurements of rock glacier deformation for 4327 rock glaciers over the central Himalayas, at least more than 15% detecting with single geometry data. The line-of-sight (LOS) deformation of rock glaciers in the central Himalayas ranged from −150 mm to 150 mm. We classified the active deformation area (ADA) of all individual rock glaciers with the threshold determined by the standard deviation of the deformation map. The results show that 49% of the detected rock glaciers (monitoring rate greater than 30%) are highly active, with an ADA ratio greater than 10%. After projecting the LOS deformation to the steep slope direction and classifying the rock glacier activity following the IPA Action Group guideline, 12% of the identified rock glaciers were classified as active and 86% were classified as transitional. This research is the first multi-baseline, PS, and DS network-based MT-InSAR method applied to detecting large-scale rock glaciers activity.

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“…However, due to the fact that the mining area subsidence is often accompanied by a large number of large gradients, the detection capability of InSAR will be constrained. This is because that the impact of spatial miscorrelation is relatively large [10], resulting in hollow area appeared in InSAR interferograms. This is also a big limitation of the current mining area deformation monitoring by InSAR.…”

Section: Introductionmentioning

confidence: 99%

Probability Integral Method Parameter Determination by SBAS‐InSAR Technology and GWO Algorithm

Liu¹,

Zhang

²

,

Chen

³

et al. 2021

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This paper proposed a method based on the SBAS-InSAR and gray wolf optimization algorithm aiming at the time-consuming and laborious defects of the traditional method used to obtain the expected parameters of the probability integral method and the shortcomings of the InSAR technology in the field of large gradient deformation detection in the mining area. The fitness function of the algorithm was established based on the geometric relationship between the radar side imaging and the three-dimensional model of the probability integral method. The stable sinking point of the settlement boundary obtained by SBAS-InSAR was used as the input value for the calculation of the predicted parameters of the probability integral method. Firstly, the simulation experiment was employed for the simulation of the direction of the InSAR line of sight combined with the geological mining conditions of the assumed working face, thereby obtaining the probability integral prediction parameters of the working face. Consequently, the maximum relative error of q , b , tanβ, and θ 0 does not exceed 8%, and that of S 1 , S 2 , S 3 , and S 4 does not exceed 35.5% (low parameter sensitivity). The error of the LOS-direction deformation fitting is 0.076 m, which meets the tolerance requirements, and the result is trustworthy. At last, the parameter finding method is applied to the engineering example, that is, the 112201 working face of Xiaobaodang Coal Mine in the northern Shaanxi mining area. The settlement value of the stable boundary point is obtained based on the SBAS-InSAR results, which is substituted into the fitness function. And the GWO optimization algorithm is used for optimization and parameter finding; the probability integral expected parameters of the working face are calculated as q = 0.63 , b = 0.37 , tan β = 2.76 , θ 0 = 83.94 , S 1 = − 36.34 m , S 2 = 26.69 m , S 3 = − 45.64 m , and S 4 = 39.62 m . Substitute the obtained parameters into the probability integral model for the prediction of the vertical and horizontal displacements of the working face, and verify its accuracy with the GPS measured data. The results showed that the maximum absolute error of vertical displacement reached 116 mm, the median error was 63 mm, and the maximum absolute error of north-south horizontal movement reached 56 mm; meanwhile, the median error was 23 mm, the maximum absolute error of east-west horizontal movement reached 61 mm, and the median error was 29 mm; all the above parameters are within the tolerance range, indicating that the method for the calculation of probability integral parameters proposed in this paper is applicable in actual engineering.

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InSAR monitoring of creeping landslides in mountainous regions: A case study in Eldorado National Forest, California

Cited by 80 publications

References 61 publications

A Framework for Studying Hydrology-Driven Landslide Hazards in Northwestern US Using Satellite InSAR, Precipitation and Soil Moisture Observations: Early Results and Future Directions

A Framework for Studying Hydrology-Driven Landslide Hazards in Northwestern US Using Satellite InSAR, Precipitation and Soil Moisture Observations: Early Results and Future Directions

Detecting Rock Glacier Displacement in the Central Himalayas Using Multi-Temporal InSAR

Probability Integral Method Parameter Determination by SBAS‐InSAR Technology and GWO Algorithm

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