Comparing Satellite Based and Ground Based Radar Interferometry and Field Observations at the Canillo Landslide (Pyrenees)

Corominas, Jordi; Iglesias, Rubén; Aguasca, A.; Mallorquí, Jordi J.; Fábregas, X.; Planas, Xavier; Gili, Josep A.

doi:10.1007/978-3-319-09057-3_51

Cited by 8 publications

(11 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The initial velocity of the field can be calculated from the displacement data to be approximately V 0 ∼ 2 − 4 cm/year, a value that is in accordance to literature values as well (Corominas et al, 2014). Using the parameter values previously discussed, Equation (13) can be solved for τ d,ref to yield:…”

Section: Forecasting and Parameter Constraintsmentioning

confidence: 58%

Forecasting landslides by taking their temperature: Combining mathematical and experimental modeling with field data on the case of the El Forn landslide (Andorra)

Seguí¹,

Veveakis²

2020

Preprint

View full text Add to dashboard Cite

In this study we are suggesting a temperature-based modeling approach for deep-seated landslides, validated through combined field monitoring and experimental testing. The Silurian shales of the shear band of El Forn landslide (Andorra) have been characterized through thermal and rate controlled triaxial tests, thereby calibrating a mathematical model that is used to monitor the behavior of deep-seated landslides. We show that by measuring the temperature inside the shear band of the active landslide, we are able to quantify and reduce the uncertainty of the model's parameters, to adequately monitor and forecast the response of the selected deep-seated landslide. In particular, it is shown that by calibrating the model's parameters through the experimental and field data of a traditionally unobservable quantity, basal temperature, the model is able to reproduce the evolution of the observable displacement of the slide.

show abstract

Section: Forecasting and Parameter Constraintsmentioning

confidence: 58%

Forecasting landslides by taking their temperature: Combining mathematical and experimental modeling with field data on the case of the El Forn landslide (Andorra)

Seguí¹,

Veveakis²

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Finally, a third rockslide with a lower extension originated on the hillside known as La Roca del Forn, in the northeast side of the hillslope, was identified. Recent local instabilities have been identified in different locations within the landslide mass [43]. The landslide of El Forn de Canillo was originated as the result of the hillside destabilization, due to a decompression phenomenon after the removal of the Valira Glacier during the Pleistocene, after the Maximum Ice Extent.…”

Section: Canillo Landslidementioning

confidence: 99%

“…Between the years 2007 and 2009, a network of geotechnical devices, including inclinometers, rod extensometers and piezometers, were installed over the landslide surface to characterize and understand the dynamics of the sliding mass. A total of 10 boreholes, reaching typically a depth between 40 and 60 m, were drilled and equipped with this instrumentation [43,44]. The readings recorded have provided evidence that, in addition to a residual movement of some millimeters per year in the main body of the slide, the most active part of the landslide corresponds to the secondary landslide of Cal Borró-Cal Ponet.…”

Section: Canillo Landslidementioning

confidence: 99%

Landslide Monitoring Using Multi-Temporal SAR Interferometry with Advanced Persistent Scatterers Identification Methods and Super High-Spatial Resolution TerraSAR-X Images

et al. 2018

Self Cite

View full text Add to dashboard Cite

Landslides are one of the most common and dangerous threats in the world that generate considerable damage and economic losses. An efficient landslide monitoring tool is the Differential Synthetic Aperture Radar Interferometry (DInSAR) or Persistent Scatter Interferometry (PSI). However, landslides are usually located in mountainous areas and the area of interest can be partially or even heavily vegetated. The inherent temporal decorrelation that dramatically reduces the number of Persistent Scatters (PSs) of the scene limits in practice the application of this technique. Thus, it is crucial to be able to detect as much PSs as possible that can be usually embedded in decorrelated areas. High resolution imagery combined with efficient pixel selection methods can make possible the application of DInSAR techniques in landslide monitoring. In this paper, different strategies to identify PS Candidates (PSCs) have been employed together with 32 super high-spatial resolution (SHR) TerraSAR-X (TSX) images, staring-spotlight mode, to monitor the Canillo landslide (Andorra). The results show that advanced PSI strategies (i.e., the temporal sub-look coherence (TSC) and temporal phase coherence (TPC) methods) are able to obtain much more valid PSs than the classical amplitude dispersion (D A ) method. In addition, the TPC method presents the best performance among all three full-resolution strategies employed. The SHR TSX data allows for obtaining much higher densities of PSs compared with a lower-spatial resolution SAR data set (Sentinel-1A in this study). Thanks to the huge amount of valid PSs obtained by the TPC method with SHR TSX images, the complexity of the structure of the Canillo landslide has been highlighted and three different slide units have been identified. The results of this study indicate that the TPC approach together with SHR SAR images can be a powerful tool to characterize displacement rates and extension of complex landslides in challenging areas.

show abstract

“…This kind of instruments have been used for several applications such as landslide monitoring, subsidence hazards in urban areas, volcano monitoring, etc. [Corominas et al 2015] and , when a classical Orbital DInSAR system cannot be used due to the bad geometric orientation of the scenario or because the revisit time of the Spaceborne sensor is not short enough to monitor the deformation. The main characteristics of the UPC RiskSAR equipment (GBSAR) in two configurations are summarized in table 3.…”

Section: Differential Sar Interferometrymentioning

confidence: 99%

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Janeras

Jara

Royan

et al. 2017

Engineering Geology

Self Cite

View full text Add to dashboard Cite

Montserrat Mountain is located near Barcelona in Catalonia, in the northeast of Spain, and its massif is formed by conglomerate interleaved by siltstone/sandstone with steep slopes very prone to rockfalls. The increasing number of visitors in the monastery area, reaching 2.4 million per year, has highlighted the risk derived from rockfalls for this building area and also for the terrestrial accesses, both roads and the rack railway. A risk mitigation plan has been launched, and its first phase during 2014-2016 has been focused largely on testing several monitoring techniques for their later implementation. The results of the pilot tests, performed as a development from previous sparse experiences and data, are presented together with the first insights obtained. These tests combine four monitoring techniques under different conditions of continuity in space and time domains, which are: displacement monitoring with Ground-based Synthetic Aperture Radar and characterization at slope scale, with an extremely non-uniform atmospheric phase screen due to the stepped topography and atmosphere stratification; Terrestrial Laser Scanner surveys quantifying the frequency of small or even previously unnoticed rockfalls, and monitoring rock block centimetre scale displacements; the monitoring of rock joints implemented through a wireless sensor network with an ad hoc design of ZigBee loggers developed by ICGC; and, finally, monitoring singular rock needles with Total Station.Peer ReviewedPostprint (author's final draft

show abstract

Comparing Satellite Based and Ground Based Radar Interferometry and Field Observations at the Canillo Landslide (Pyrenees)

Cited by 8 publications

References 5 publications

Forecasting landslides by taking their temperature: Combining mathematical and experimental modeling with field data on the case of the El Forn landslide (Andorra)

Forecasting landslides by taking their temperature: Combining mathematical and experimental modeling with field data on the case of the El Forn landslide (Andorra)

Landslide Monitoring Using Multi-Temporal SAR Interferometry with Advanced Persistent Scatterers Identification Methods and Super High-Spatial Resolution TerraSAR-X Images

Multi-technique approach to rockfall monitoring in the Montserrat massif (Catalonia, NE Spain)

Contact Info

Product

Resources

About