Tag Archives: mapping


Clément Michoud: From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Clément Michoud
Directors: Prof. Michel Jaboyedoff and Dr. Marc-Henri Derron
Jury: Dr. François J. Baillifard, Prof. Lars H. Blikra, Prof. Jacques Locat, Dean François Bussy

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales.

At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale.

At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures.

To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Download the PhD manuscript

Rockfall susceptibility mapping

Advanced Susceptibility Mapping for Natural Hazards in the Swiss Alpine Valley of Bagnes

Alpine municipalities are exposed to numerous natural hazards, such as snow avalanches, rockfalls, landslides and debris flows. The Bagnes and Vollèges municipalities in Valais (Switzerland) lie between 600 m and 4200 m m.s.l. with an area of 300 km2. The anthropization is rapid because of the fast growing ski resort of Verbier. In such situation the municipalities needs to have global overview of the natural hazards for landplaning purpose and decision making. The susceptibility mapping at regional scale allows the detection of the areas that are exposed to natural hazards, without considering the intensity and the frequency of the phenomena.

The aim of this study is to provide susceptibility maps at 1:25’000 for the following natural hazards: landslides, shallow landslides, rockfalls, debris flows, snow avalanches, flooding and river overflowing.

The present method was first developed for the Canton of Vaud (2’800 km2). Because it is applied to a smaller area, more numerical models on High Resolution DEM and field investigations were performed. In addition historical event were included in the study.

  1. The landslide mapping identifies deep-seated slope gravitational deformations, landslides and shallow landslides. It is based on the observations of geomorphological criteria on HR-EM, orthophotos and field work. Finally, the activity of each landslide is described by the knowledge of local guides.
  2. The shallow landslide susceptibility mapping is realized thanks to the software SInMap, calculating Security Factor (FS) and Stability Index (SI) according to the land use, the topography and the climatic conditions. The model is calibrated on the basis of the 67 shallow landslides already identified for the first map.
  3. The rockfall susceptibility mapping is a two steps process. First, the potential source areas of blocks are detected using a statistical analysis of the slope angle distribution, including external knowledge on the geology and land cover. Then the run-out is assessed with numerical methods based on the shallow angle method (software Conefall) and on an energy-based run-out calculation (software Flow-R).
  4. The debris flow susceptibility mapping is based on Flow-R to map debris flow sources and spreading. Slope, flow accumulation, contributive surfaces, plan curvature, geological and land use dataset are used to detect the source areas. The spreading is simulated by a multiple flow algorithm (rule the path that the debris flow will follow) coupled to a run-out distance calculation (energy-based).
  5. The snow avalanches susceptibility mapping is again based on Flow-R, to map sources areas and spreading. Slope, altitude, land use and one minimum surface are needed to detect the sources areas. The spreading is simulated with the “Perla” methodology using Flow-R. A second simulation of the spreading with RAS is performed by means of the alpha-beta methodology.
  6. Regarding to the river overflowing along the Dranse de Bagnes, the hotspots which could create blockages (bridges, pipes, etc.) are identified on the field. The propagations of the overflowing are simulated with Flow-R from the spots recognized earlier.

Finally, results show good concordances with past events and the knowledge of the local geologist and guides. The susceptibility maps will help the decision-makers of the Bagnes valley to prioritize area of interest for the creation of more expensive hazard maps.

For more information, please read Jaboyedoff M., Choffet M., Derron M.-H., Horton P., Loye A., Longchamp C., Mazotti B., Michoud C. and Pedrazzini A.: Preliminary slope mass movements susceptibility mapping using DEM and LiDAR DEM. In: Terrigenous Mass Mouvements, Pradhan and Buchroithner (Eds.), Springer-Verlag Berlin Heidelberg, 109-170, 2012

Featured image: rockfall susceptibility mapping (hillshade: copyright swisstopo)

SafeLand – Living with landslide risk in Europe

SafeLand was a Large-scale integrating Collaborative research project funded by the The Seventh Framework Programme for research and technological development (FP7) of the European Commission. The project team, composed of 27 institutions from 13 European countries, was coordinated by Norwegian Geotechnical Institute (NGI).

SafeLand aimed at developing generic quantitative risk assessment and management tools and strategies for landslides at local, regional, European scales. It also established the baseline for the risk associated with landslides in Europe, and improved our ability to forecast landslide and detect hazard and risk zones.

During this 3-years project, our group mainly contributed to the following deliverables:

  • D 1.6: Analysis of landslides triggered by anthropogenic factors in Europe
  • D 2.10: Identification of landslide hazard and risk “hotspots” in Europe
  • D 4.1: Review of Techniques for Landslide Detection, Fast Characterization, Rapid Mapping and Long-Term Monitoring (as Editor)
  • D 4.4: Guidelines for the selection of appropriate remote sensing technologies for monitoring different types of landslides
  • D 4.8: Guidelines for landslide monitoring and early warning systems in Europe – Design and required technology
  • D 5.1: Compendium of tested and innovative structural, non-structural and risk-transfer mitigation measures for different landslide types

All deliverables and more information about the SafeLand project can be found on www.safeland-fp7.eu.

Featured image: Landslide in Namsos, Norway (copyright SafeLand)