Ryan Kromer is PhD graduate of Queen’s University and a post doctoral researcher at the Colorado School of Mines. He was a visiting PhD student at the University of Lausanne during 2015 and 2016 and is now visiting the Risk group from April to June 2019. During his visit, he will be conducting research on automated monitoring of landslides using terrestrial LiDAR and photogrammetry. The research visit is supported by the Herbette Foundation. Ryan is looking forward to another fruitfull visit with the group.
The Risk Analysis Group (C. d’Almeida, F.Noël) spent a week in the principality of Andorra to carry out lidar survey. The city of Andorra-la-Vella, located in the hearth of the Pyrenees is a very dense city surrounded by landslides and active cliffs.
Lidar and photographs survey of 12 sites were performed. These sites were previously monitored by the Risk Analysis Group (Antonio Abellan) in 2009 and 2012. Exploiting the lidar scans will permit to quantify the erosion activity of the cliffs and detect potential instabilities. The Risk Analysis Group thanks the geo-hazard expert Joan Torrebadella from Georisk-international for his warm welcome, and accompanying during this week.
Director: Prof. Michel Jaboyedoff
Jury: Dr. Marc-Henri Derron, Dr. Greg M. Stock, Dr. Brian Collins, Prof. Giovanni B. Crosta, Dean François Bussy
Characterizing the geological features and structures in three dimensions over inaccessible rock cliffs is needed to assess natural hazards such as rockfalls and rockslides and also to perform investigations aimed at mapping geological contacts and building stratigraphy and fold models. Indeed, the detailed 3D data, such as LiDAR point clouds, allow to study accurately the hazard processes and the structure of geologic features, in particular in vertical and overhanging rock slopes. Thus, 3D geological models have a great potential of being applied to a wide range of geological investigations both in research and applied geology projects, such as mines, tunnels and reservoirs. Recent development of ground-based remote sensing techniques (LiDAR, photogrammetry and multispectral / hyperspectral images) are revolutionizing the acquisition of morphological and geological information. As a consequence, there is a great potential for improving the modeling of geological bodies as well as failure mechanisms and stability conditions by integrating detailed remote data.
During the past ten years several large rockfall events occurred along important transportation corridors where millions of people travel every year (Switzerland: Gotthard motorway and railway; Canada: Sea to sky highway between Vancouver and Whistler). These events show that there is still a lack of knowledge concerning the detection of potential rockfalls, making mountain residential settlements and roads highly risky. It is necessary to understand the main factors that destabilize rocky outcrops even if inventories are lacking and if no clear morphological evidences of rockfall activity are observed. In order to increase the possibilities of forecasting potential future landslides, it is crucial to understand the evolution of rock slope stability. Defining the areas theoretically most prone to rockfalls can be particularly useful to simulate trajectory profiles and to generate hazard maps, which are the basis for land use planning in mountainous regions. The most important questions to address in order to assess rockfall hazard are:
- Where are the most probable sources for future rockfalls located?
- What are the frequencies of occurrence of these rockfalls?
I characterized the fracturing patterns in the field and with LiDAR point clouds. Afterwards, I developed a model to compute the failure mechanisms on terrestrial point clouds in order to assess the susceptibility to rockfalls at the cliff scale. Similar procedures were already available to evaluate the susceptibility to rockfalls based on aerial digital elevation models. This new model gives the possibility to detect the most susceptible rockfall sources with unprecedented detail in the vertical and overhanging areas. The results of the computation of the most probable rockfall source areas in granitic cliffs of Yosemite Valley and Mont-Blanc massif were then compared to the inventoried rockfall events to validate the calculation methods. Yosemite Valley was chosen as a test area because it has a particularly strong rockfall activity (about one rockfall every week) which 2 leads to a high rockfall hazard. The west face of the Dru was also chosen for the relevant rockfall activity and especially because it was affected by some of the largest rockfalls that occurred in the Alps during the last 10 years. Moreover, both areas were suitable because of their huge vertical and overhanging cliffs that are difficult to study with classical methods. Limit equilibrium models have been applied to several case studies to evaluate the effects of different parameters on the stability of rockslope areas. The impact of the degradation of rockbridges on the stability of large compartments in the west face of the Dru was assessed using finite element modeling. In particular I conducted a back-analysis of the large rockfall event of 2005 (265’000 m3) by integrating field observations of joint conditions, characteristics of fracturing pattern and results of geomechanical tests on the intact rock. These analyses improved our understanding of the factors that influence the stability of rock compartments and were used to define the most probable future rockfall volumes at the Dru. Terrestrial laser scanning point clouds were also successfully employed to perform geological mapping in 3D, using the intensity of the backscattered signal. Another technique to obtain vertical geological maps is combining triangulated TLS mesh with 2D geological maps. At El Capitan (Yosemite Valley) we built a georeferenced vertical map of the main plutonic rocks that was used to investigate the reasons for preferential rockwall retreat rate. Additional efforts to characterize the erosion rate were made at Monte Generoso (Ticino, southern Switzerland) where I attempted to improve the estimation of long term erosion by taking into account also the volumes of the unstable rock compartments.
Eventually, the following points summarize the main out puts of my research:
- The new model to compute the failure mechanisms and the rockfall susceptibility with 3D point clouds allows to define accurately the most probable rockfall source areas at the cliff
- The analysis of the rockbridges at the Dru shows the potential of integrating detailed measurements of the fractures in geomechanical models of rockmass stability.
- The correction of the LiDAR intensity signal gives the possibility to classify a point cloud according to the rock type and then use this information to model complex geologic structures.
The integration of these results, on rockmass fracturing and composition, with existing methods can improve rockfall hazard assessments and enhance the interpretation of the evolution of steep rockslopes.
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.
Hello to everyone,
We will be presenting a Short Course at the European Geosciences Union General Assembly. The course is entitled “Use of 3D point clouds in Geosciences: Acquisition, Processing and Applications” and the pdf of the Powerpoint presentations can be downloaded here.
DATE AND PLACE: Monday 13th of April, from 17:30 to 19:30 in room B7. If you are a PhD student or an Early Stage Researcher, you are welcome to assist.
CONTENTS OF THE COURSE
|Introduction to course + speakers (AA+MJ)||5’|
|1. Short introduction to LiDAR sensors + photogrammetry (MHD)||15’ (20’)|
|2. Point cloud acquisition, pre-processing and available software (AA)||15’ (35’)|
|3. 3D geological mapping (FH)||15’ (50’)|
|——10 min. Pause ——||10’ (1h)|
|4. Rock structural characterisation (AG)||15’ (1h 15)|
|5. Monitoring: Change detection + Deformation (DC)||15’ (1h 30)|
|6. Perspectives and discussion (AA)||15’ (1h 45)|
The PowerPoints of the course and some RAW 3D point clouds will be uploaded here some days before the beginning of the course. Some other information can be found here: http://meetingorganizer.copernicus.org/EGU2015/session/19506
Also, we want to account with your vision, in case you’ll be interested in contributing for the last part of our course (“6. Perspectives and discussion”), you can contact us and send us your contribution.
We have been invited for edit a special issue at Remote Sensing journal entitled: “Use of LiDAR and 3D point clouds in Geohazards”
Deadline for manuscript submissions: 31 May 2015
SPECIAL ISSUE CONTENTS:
Contributions aiming to use 3D point clouds for investigating natural phenomena (including ground deformation, landslides, floods, earthquakes, volcanoes, soil erosion, etc.) that pose serious risks to human beings or infrastructures will be much appreciated in this special issue. We aim to put together innovative contributions about novel processing techniques and original applications of three-dimensional techniques in Geohazards. Some examples include, but are not limited to:
- Novel technologies or procedures for dynamic acquisition of 3D point clouds
- New computational methods related with the monitoring of natural phenomena
- Semi-automatic extraction of terrain features related with the characterization of geological hazard
- Integration of very high quality data for improving the modeling of geohazards
- Recent case studies: innovative analysis and interpretation of Geohazards
- Use of three-dimensional systems in laboratory scale experiments (micro scale)
- Improvements in regional mapping derived from high quality 3D data
- Pioneering initiatives for the creation of 3D databases, web visualization and data sharing
- Further related topics.
Authors are required to check and follow specific Instructions to Authors, see https://dl.dropboxusercontent.com/u/165068305/Remote_Sensing-Additional_Instructions.pdf.
Prof. Michel Jaboyedoff, Dr. Antonio Abellan, Dr. Marc-Henri Derron (Guest Editors)
More information here: http://www.mdpi.com/journal/remotesensing/special_issues/geohazards
Good news! The number of citations that we are receiving concerning Natural Hazards related journals is considerably increasing… For the past five years we have had the 2nd most cited paper in Natural Hazards journal (Springer) …
We also obtained not bad results concerning Natural Hazards and Earth System Sciences journal (Copernicus): have a look at the 4th and 5th most cited papers in the last five years
NATURAL HAZARDS & EARTH SYSTEM SCIENCE: http://scholar.google.ch/citations?hl=fr&view_op=list_hcore&venue=EKUCyVlF5DoJ.2014
A new approach for semi-automatic rock mass joints recognition from 3D point clouds
Riquelme, A., Abellan, A., Tomás, R., Jaboyedoff, M (2014). A new approach for semi-automatic rock mass joints recognition from 3D point clouds. Computers & Geosciences, 68(0), pp.38–52. DOI: 10.1016/j.cageo.2014.03.014
In this paper we present a semi-authomatic methodology for the identification and analysis of flat surfaces outcropping in rocky slopes from 3D point clouds. The method is based on a three steps process: (i) to carry out a nearest neighbour points coplanarity test and to computate the normal vector; (ii) to find the principal orientation families by Kernel Density Estimation; and (iii) to identify and extract clusters of points belonging to the same discontinuity.
Different sources of information – synthetic and 3D scanned data – were employed in this study, being raw source files and obtained results freely provided aiming to a more reproducible research.
Abellán, A., Oppikofer, T., Jaboyedoff, M., Rosser, N. J., Lim, M. and Lato, M. J. (2014), Terrestrial laser scanning of rock slope instabilities. Earth Surf. Process. Landforms. DOI: 10.1002/esp.3493
This manuscript presents a review on the application of a remote sensing technique (terrestrial laser scanning, TLS) to a rock slope characterization and monitoring. Key insights into the use of TLS in rock slope investigations include: (a) the capability of remotely obtaining the orientation of slope discontinuities, which constitutes a great step forward in rock mechanics; (b) the possibility to monitor rock slopes which allows not only the accurate quantification of rockfall rates across wide areas but also the spatio-temporal modelling of rock slope deformation with an unprecedented level of detail.
Further investigation on the development of new algorithms for point cloud filtering, segmentation, feature extraction, deformation tracking and change detection will significantly improve our understanding on how rock slopes behave and evolve.
Perspectives include the use of new 3D sensing devices and the adaptation of techniques and methods recently developed in other disciplines as robotics and 3D computer-vision to rock slope instabilities research.
More information and full paper on the ESPL website.