Satellite Pre-Failure Detection and In Situ Monitoring of the Landslide of the Tunnel du Chambon, French Alps

Desrues, Mathilde; Lacroix, Pascal; Brenguier, Ombeline

doi:10.3390/geosciences9070313

Cited by 20 publications

(12 citation statements)

References 30 publications

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“…They have contrasting behavior: the displacement rates of the upper part (from 0 to 20 m) decrease over time while those of the lower part (from 80 to 100 m) increase. This pendulum motion is in agreement with a rotational movement which is confirmed by topographic surveys [49,55]. The profile P2 identifies two distinct compartments, with a slide-type behavior (from 2 to 50 m) and a subsidence type behavior (from 60 to 92 m).…”

Section: Displacement Fields At the Chambon Landslidesupporting

confidence: 77%

TSM—Tracing Surface Motion: A Generic Toolbox for Analyzing Ground-Based Image Time Series of Slope Deformation

Desrues

Malet

Brenguier³

et al. 2019

Remote Sensing

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Passive sensors such as multi-spectral (e.g., Single Lens Reflex, SLR) cameras are increasingly being used for geohazards monitoring (landslides, cliffs affected by rock falls, ice glaciers, and volcano flanks) because of their low cost compared to expensive terrestrial laser scanner (TLS) or radar imaging (GB-InSAR) systems. Indeed, due to the large consumer market, sensor resolution and quality (e.g., gain, dynamic range, and geometry) are increasing rapidly. For gravitational processes, such as landslides, recent research has focused on the development and implementation of image correlation techniques to estimate the spatial shift between at least a pair of images by maximizing a cross-correlation function. A generic and fully automated pipeline is proposed for the processing of long image time series acquired for several site configurations. The system associates modules for 1) the selection of the image sequences, 2) the registration of the image stacks and the correction of the camera movements, and 3) the calculation of the terrain motion using change detection approaches. The system is based on the open-source photogrammetric library MicMac and tailored for the processing of monoscopic images. A sensitivity analysis is conducted to design and test the image processing for two use cases respectively the Chambon landslide (Isère, France) characterized by slow motion (< 10 cm.day−1), and the Pas de l’Ours landslide (Hautes-Alpes, France) characterized by moderate motion (> 50 cm.day−1). Four categories of parameters are tested: the image modality, the image matching parameters, the size of the stable area used in the co-registration stage, and the strategy used to combine the images in the time series. The application of the pipeline on the two use cases provides information about the kinematics and the spatial behavior of the landslides.

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Section: Displacement Fields At the Chambon Landslidesupporting

confidence: 77%

TSM—Tracing Surface Motion: A Generic Toolbox for Analyzing Ground-Based Image Time Series of Slope Deformation

Desrues

Malet

Brenguier³

et al. 2019

Remote Sensing

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“…In all case studies, the observed displacements are in agreement with the ground-truth measurements. Besides this, there are also high-resolution optical images analyzed for the landslide of the Tunnel du Chambon in the French Alps by Desrues et al, [50] who have shown the potential landslide failure. Another large-scale landslide of Harmaliere and new movements and slope…”

Section: Previous Measurements Of Slope Movements In the French Alpsmentioning

confidence: 99%

Landslide Mapping and Monitoring Using Persistent Scatterer Interferometry (PSI) Technique in the French Alps

et al. 2020

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Continuous geodetic measurements in landslide prone regions are necessary to avoid disasters and better understand the spatiotemporal and kinematic evolution of landslides. The detection and characterization of landslides in high alpine environments remains a challenge associated with difficult accessibility, extensive coverage, limitations of available techniques, and the complex nature of landslide process. Recent studies using space-based observations and especially Persistent Scatterer Interferometry (PSI) techniques with the integration of in-situ monitoring instrumentation are providing vital information for an actual landslide monitoring. In the present study, the Stanford Method for Persistent Scatterers InSAR package (StaMPS) is employed to process the series of Sentinel 1-A and 1-B Synthetic Aperture Radar (SAR) images acquired between 2015 and 2019 along ascending and descending orbits for the selected area in the French Alps. We applied the proposed approach, based on extraction of Active Deformation Areas (ADA), to automatically detect and assess the state of activity and the intensity of the suspected slow-moving landslides in the study area. We illustrated the potential of Sentinel-1 data with the aim of detecting regions of relatively low motion rates that be can attributed to activate landslide and updated pre-existing national landslide inventory maps on a regional scale in terms of slow moving landslides. Our results are compared to pre-existing landslide inventories. More than 100 unknown slow-moving landslides, their spatial pattern, deformation rate, state of activity, as well as orientation are successfully identified over an area of 4000 km2 located in the French Alps. We also address the current limitations due the nature of PSI and geometric characteristic of InSAR data for measuring slope movements in mountainous environments like Alps.

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“…Holbling et al [51] used SPOT-5 remotely sensed data for landslide change detection, whereas [52] used ALOS/PALSAR imageries and InSAR techniques for landslide detection. On the other hand, Desrues et al [54] used LiDAR DEM and satellite images for landslide detection and mapping.…”

Section: Types and Role Of Remote Sensing Techniquesmentioning

confidence: 99%

Remote Sensing Approaches and Related Techniques to Map and Study Landslides

Ray¹,

Lazzari²,

Olutimehin³

2020

Landslides - Investigation and Monitoring

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Landslide is one of the costliest and fatal geological hazards, threatening and influencing the socioeconomic conditions in many countries globally. Remote sensing approaches are widely used in landslide studies. Landslide threats can also be investigated through slope stability model, susceptibility mapping, hazard assessment, risk analysis, and other methods. Although it is possible to conduct landslide studies using in-situ observation, it is time-consuming, expensive, and sometimes challenging to collect data at inaccessible terrains. Remote sensing data can be used in landslide monitoring, mapping, hazard prediction and assessment, and other investigations. The primary goal of this chapter is to review the existing remote sensing approaches and techniques used to study landslides and explore the possibilities of potential remote sensing tools that can effectively be used in landslide studies in the future. This chapter also provides critical and comprehensive reviews of landslide studies focus¬ing on the role played by remote sensing data and approaches in landslide hazard assessment. Further, the reviews discuss the application of remotely sensed products for landslide detection, mapping, prediction, and evaluation around the world. This systematic review may contribute to better understanding the extensive use of remotely sensed data and spatial analysis techniques to conduct landslide studies at a range of scales.

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Satellite Pre-Failure Detection and In Situ Monitoring of the Landslide of the Tunnel du Chambon, French Alps

Cited by 20 publications

References 30 publications

TSM—Tracing Surface Motion: A Generic Toolbox for Analyzing Ground-Based Image Time Series of Slope Deformation

TSM—Tracing Surface Motion: A Generic Toolbox for Analyzing Ground-Based Image Time Series of Slope Deformation

Landslide Mapping and Monitoring Using Persistent Scatterer Interferometry (PSI) Technique in the French Alps

Remote Sensing Approaches and Related Techniques to Map and Study Landslides

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