Abstract
Monitoring is essential to understand the mechanics of landslides, and predict their behavior in time and space. In this work we discuss the performance of multi-sensor monitoring techniques applied to measure the kinematics and the landslide hydrology of Portalet landslide complex, which is located in the SW-facing slopes of Petrasos peak at the border between Spain and France. In the summer 2004, the excavation of a parking lot at the foot of the slides triggered a secondary failure in the lower part of the slope, accelerating the dynamic of the landslide complex. The deployed hydro-meteorological network has been useful to understand that the greatest infiltration in the moving mass is produced in spring due to the combination of snow melt and seasonal rainfall. Landslide surface kinematics measured with differential GPS (D-GPS) were useful to measure the slower (<10 cm/year) and faster (20–30 cm/year) dynamic of the landslide complex. Advanced DInSAR was useful to monitor the slower ground displacements from long datasets of SAR images, providing a wider spatial coverage and measurement point density than the D-GPS. In addition, the NL-InSAR processing strategy was applied to monitor the faster motion using short datasets of TerraSAR-X images excluding the snow cover period. The installed horizontal extensometers were useful to study the extension of the head scarp and its relationship with landslide hydrology, which is affected by the retrogressive effect of the landslide due to the loss of lateral confining pressure. Finally, an inclinometric robot system (AIS) was the only technique capable of detecting 5–6 time faster motion after the snow melt, since it provides daily measurements with high accuracy even during the snow cover period. These data, even if expensive to gather, are necessary to improve the hydro-mechanical modeling of large slow landslides, such as those already proposed for Portalet landslide complex.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Albiol D, Iglesias R., Sánchez F, Duro J (2014) Improved characterization of slow-moving landslides by means of adaptive NL-InSAR filtering. Proceedings of the SPIE 9243, SAR image analysis, modeling, and techniques XIV, 924308 (21 Oct 2014). doi:10.1117/12.2067357
Casagli N, Catani F, Del Ventisette C, Luzi G (2010) Monitoring, prediction, and early warning using ground-based radar interferometry. Landslides 7(3):291–301
Corominas J, Moya J, Lloret A, Gili JA, Angeli MG, Pasuto A, Silvano S (2000) Measurement of landslide displacements using a wire extensometer. Eng Geol 55(3):149–166
Fernández-Merodo J, García-Davalillo J, Herrera G, Mira P, Pastor M (2014) 2D viscoplastic finite element modelling of slow landslides: the Portalet case study (Spain). Landslides 11:29–42. doi:10.1007/s10346-012-0370-4
Herrera G, Gutiérrez F, García-Davalillo JC, Guerrero J, Notti D, Galve JP, Fernández-Merodo JA, Cooksley G (2013) Multi-sensor advanced DInSAR monitoring of very slow landslides: the Tena Valley case study (Central Spanish Pyrenees). Remote Sens Environ 128:31–43
Herrera G, Fernández-Merodo JA, Mulas J, Pastor M, Luzi G, Monserrat O (2009) A landslide forecasting model using ground based SAR data: the Portalet case study. Eng Geol 105:220–230
Jaboyedoff M, Oppikofer T, Abellán A, Derron MH, Loye A, Metzger R, Pedrazzini A (2012) Use of LIDAR in landslide investigations: a review. Nat Hazards 61(1):5–28
Lollino G (1992) Automated inclinometric system. In: Bell David H (ed) Proceedings of the 6th international symposium on landslides, Christchurch, New Zealand, 10–14 Feb 1992. A.A. Balkema, Rotterdam, pp 1147–1150
Lollino G, Arattano M, Allasia P, Giordan D (2006) Time response of a landslide to meteorological events. Nat Hazards Earth Syst Sci, pp 179–184
Malet JP, Maquaire O, Calais E (2002) The use of global positioning system techniques for the continuous monitoring of landslides: application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France). Geomorphology 43(1):33–54
Mikkelsen PE (2003) Advances in inclinometer data analysis. In: Myrvoll (ed) Proceedings of the 6th international symposium on field measurements in geomechanics, Oslo, Norway, Sept 2003, pp 555–566
Niethammer U, James MR, Rothmund S, Travelletti J, Joswig M (2012) UAV-based remote sensing of the Super-Sauze landslide: evaluation and results. Eng Geol 128:2–11
Tofani V, Del Ventisette C, Moretti S, Casagli N (2014) Integration of remote sensing techniques for intensity zonation within a landslide area: a case study in the northern Apennines, Italy. Remote Sensing 6(2):907–924
Acknowledgements
This work has been funded by FP7 LAMPRE project GA no: 312384. Meteorological station data was acquired from the SAIH service from the Confederación Hidrográfica del Ebro.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Herrera, G. et al. (2017).
The Differential Slow Moving Dynamic of a Complex Landslide: Multi-sensor Monitoring
.
In: Mikos, M., Tiwari, B., Yin, Y., Sassa, K. (eds) Advancing Culture of Living with Landslides. WLF 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-53498-5_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-53498-5_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-53497-8
Online ISBN: 978-3-319-53498-5
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)