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Michel Jaboyedoff, Denis Demers, Jacques Locat, Ariane Locat, Pascal Locat,. Thierry Oppikofer, Denis Robitaille, and Dominique Turmel. Abstract: For more ...
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Use of terrestrial laser scanning for the characterization of retrogressive landslides in sensitive clay and rotational landslides in river banks Michel Jaboyedoff, Denis Demers, Jacques Locat, Ariane Locat, Pascal Locat, Thierry Oppikofer, Denis Robitaille, and Dominique Turmel

Abstract: For more than 10 years, digital elevation models (DEM) produced by light detection and ranging (LIDAR) technology have provided new tools for geomorphologic studies and especially for landslide studies. In particular, terrestrial laser scanning (TLS) provides a great versatility of use. TLS can be used either for monitoring purposes or in an emergency situation that necessitates a rapid DEM acquisition for assessing a hazard. Using three examples we demonstrate the usefulness of TLS for landslide volume quantification, profile creation, and time series analysis. These case studies are landslides located in sensitive clays of eastern Canada (Quebec, Canada) or small rotational slides in river banks (Switzerland). Key words: aerial and terrestrial laser scanning, landslide, digital elevation models (DEM), sensitive clays, rotational slide. Re´sume´ : Depuis plus de 10 ans les mode`les nume´riques d’altitude (MNA) produits par technologie de « light detection and ranging » (« LIDAR ») ont fourni de nouveaux outils tre`s utiles pour des e´tudes ge´omorphologiques, particulie`rement dans le cas des glissements de terrain. Le balayage laser terrestre (« TLS ») permet une utilisation tre`s souple. Le TLS peut eˆtre employe´ pour la surveillance ou dans des situations d’urgence qui ne´cessitent une acquisition rapide d’un MNA afin d’e´valuer l’ale´a. Au travers de trois exemples, nous de´montrons l’utilite´ du TLS pour la quantification de volumes de glissements de terrain, la cre´ation de profils et l’analyse de se´ries temporelles. Ces e´tudes de cas sont des glissements de terrain situe´s dans les argiles sensibles de l’est du Canada (Que´bec, Canada) ou de petits glissements rotationnels dans les berges d’une rivie`re (Suisse). Mots-cle´s : balayage laser ae´rien et terrestre, glissement de terrain, mode`les nume´riques d’altitude (MNA), argiles sensibles, rotationel slide.

Introduction Since the mid 1990s, light detection and ranging (LIDAR) techniques have been extensively used for topographic surveys in various regions. Data acquisition was first performed by airborne laser scanning (ALS) (Thomas et al. 1995) and more recently, since approximately 2000, by terrestrial laser scanning (TLS) (Lichti et al. 2000; Gordon et al. 2001). The development of ALS techniques was dependent mostly on Received 1 February 2008. Accepted 17 June 2009. Published on the NRC Research Press Web site at cgj.nrc.ca on 27 November 2009. M. Jaboyedoff1 and T. Oppikofer. Institut de Ge´omatique et d’Analyse du Risque – IGAR, AMPHIPOLE-338, University of Lausanne, CH-1015 Lausanne, Switzerland. D. Demers, P. Locat, and D. Robitaille. Service de la ge´otechnique et de la ge´ologie, Ministe`re des Transports du QC, 930, Chemin Sainte-Foy, Que´bec, QC G1S 4X9, Canada. J. Locat, A. Locat, and D. Turmel. Laboratoire d’e´tudes sur les risques naturels (LERN), Groupe de recheche en ge´oinge´nierie et en environnement (GREGI), De´partement de ge´ologie et de ge´nie ge´ologique, Universite´ Laval, Pavillon Pouliot, local 4317, Que´bec, QC G1K 7P4, Canada. 1Corresponding

author (e-mail: [email protected]).

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global positioning system (GPS) and inertial system improvements (Krabill et al. 1995); whereas, TLS can be considered as an enhancement of laser distancemeter technologies by scanning large fields of view and acquiring the XYZ position of the scanned points relative to the instrument. Modern laser scanners acquire several hundreds to several thousands of points per second (Point of Beginning 2008). ALS provides high resolution digital elevation models (HRDEM) that have changed the world of terrain analysis. Geomorphic and geological mapping has been greatly improved by ALS imaging (Carter et al. 2001; Haugerud et al. 2003; Borlat et al. 2007). HRDEM are widely used for landslide analysis and slope characterization (McKean and Roering 2004; Derron et al. 2005; Haneberg et al. 2005; Lim et al. 2005; Schulz 2007; Jaboyedoff et al. 2009). Agliardi and Crosta (2003) have shown the great improvement of rockfall modeling by using HRDEM. The Ministe`re des Transports du Que´bec (MTQ) method for sensitive clay hazard mapping (Lebuis et al. 1983; Locat et al. 1984; Robitaille et al. 2002) now includes the ALS HRDEM as a standard tool. Unfortunately, so far the ALS acquisition method has provided only 2.5-dimensional images, as the acquisition is generally performed in a vertical direction and thereby gives only very few points on vertical surfaces. On the other hand,

doi:10.1139/T09-073

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TLS produces full three-dimensional (3D) point clouds in several directions and thus provides a high point density in steep cliffs. This makes TLS complementary to ALS (Derron et al. 2005). The TLS monitoring and surveying of rock faces and rockslides are now well developed (Janeras et al. 2004; Rosser et al. 2005; Voyat 2005; Abella´n et al. 2006; Oppikofer et al. 2008), whereas the application of these techniques to landslides developed in soils have been less well documented (Collins et al. 2007; Travelletti et al. 2008). This paper presents three different types of landslide surveys in Canada and Switzerland (Figs. 1 and 2): (1) A fast TLS campaign of the landslide that occurred on 8 May 2006 along the Nicolet River (Quebec, Canada) for a quick assessment of landslide characteristics and for mitigation strategies. (2) The detailed comparison of TLS and ALS HRDEMs of the Saint-Barnabe´-Nord landslide (Quebec, Canada) to provide data on slope evolution and erosion processes of the landslide. (3) Multi-temporal TLS point clouds showing the slope evolution with time and the circular shape of the failure surface for several small landslides during the spring of 2006 along the Sorge River (Lausanne, Switzerland).

Method Terrestrial laser scanning technique The TLS is based on measuring the distance between the scanner device and an object using a laser. The monochromatic and nearly parallel laser pulse is sent out in a precisely known direction. The pulse gets reflected by various objects, such as vegetation, buildings, and the terrain. The back-scattered pulse, which is recorded by the scanner, is a complex wave that is longer than the emitted pulse, due to interaction with multiple objects along the flight path of the signal. The time-of-flight is converted into the distance between the scanner and the object. The XYZ position of each point is known by its distance and direction relative to the scanner. In principle, the maximum range distance increases with the wavelength from 500 to 1550 nm, but also depends on the laser class (Fig. 3). Most of the long-range scanners contain an eye-safe Class 1 infrared laser. The reflectivity of the scanned object also plays an important role; highly reflective objects, such as metal buildings or reflective targets, can be imaged up to or even at a larger distance than specified by the manufacturer; whereas even clean, bright rock walls reduce the range by approximately one-third due to the lower reflectivity of rocks. Instrument used and data treatment The TLS system used in this study was an ILRIS-3D laser scanning system from Optech Inc. with a wavelength of 1550 nm (Optech Inc. 2008). Two mirrors inside the scanner provide a 408 wide and 408 high window (field of view), which can be scanned in a single acquisition at a rate of about 2500 points per second. At a distance of 100 m, the instrument accuracy is approximately 7 mm for the distance and 8 mm for the position. The manufacturer indicates a

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scanning range from 3 to 1500 m (for an 80% reflectivity target) (Optech Inc. 2008). The range decreases to 800 m for clean, dry rock walls (20% reflectivity) or to 350 m for vegetated slopes (4% reflectivity). The target reflectivity is not easy to estimate in the field because of terrain humidity, which can strongly diminish the reflectivity (Rosser et al. 2007). The resolution depends on the distance between the scanner and the object and the chosen angular spacing between two spots (point spacing). TLS data from different viewpoints are acquired to avoid shadowing and to obtain a complete 3D model of an object. The occlusions are avoided by creating overlaps between scans. Nevertheless, it is not always possible to get a continuous point cloud, because of limited site accessibility, especially in landslide studies. As LIDAR imagery provides point clouds of the surface, including the terrain, but also vegetation, buildings, and other unwanted objects, these raw scans need to be treated and unwanted objects removed from the data. The registration of the last pulse of the returned signal discards some reflections due to the vegetation; this does not, however, completely remove all the vegetation in the scan window. The vegetation and buildings can be removed from a TLS point cloud either manually using suitable software (e.g., InnovMetric PolyWorks; InnovMetric 2008) or automatically using various filtering routines (Kraus and Pfeifer 2001; Jaboyedoff et al. 2007). The individual scans are then unified using a surface-to-surface iterative closest-point (ICP) (Besl and McKay 1992) algorithm implemented in PolyWorks on overlapping areas and finally georeferenced using an ALS HRDEM or differential global positioning system (DGPS) ground control points. Landslide survey and monitoring Sequential TLS point clouds, taken at different times, allow the computation of differences in PolyWorks software directly between two point clouds or between interpolated meshes. Interpolated surfaces are especially useful for comparisons of TLS data with ALS data, as their spatial resolution or point spacing is very different (10 times bigger point spacing for ALS point clouds relative to TLS datasets) and the interpolation provides a continuous mesh for both point clouds. The differences between sequential TLS datasets are generally expressed as the shortest distance between two point clouds and can be related to slope movements. Landslides generally lead to an advance (positive differences) of the terrain relative to the initial state at the toe and to negative differences at the head. Erosion processes also lead to negative differences. Such TLS time series are useful for the monitoring of slope movements, both before and after a landslide event. Pre-landslide monitoring enables the prediction of the most active parts within a larger scale landslide and eventually facilitates failure prediction (Oppikofer et al. 2008), while post-landslide surveys permit the detection of ongoing slope movements. The differences between the pre- and post-landslide topography also allow the calculation of the displaced or eroded volumes, either by means of interpolated 3D surfaces, differences between HRDEMs or on the basis of cross sections. Published by NRC Research Press

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Fig. 1. Location map of the Nicolet and Saint Barnabe´-Nord landslides in Quebec (Canada).

Fig. 2. Location map of the Sorge River and picture of the remodeled river bank (taken on 16 March 2006), where one of the circular landslide scarps is indicated. The river flows from west to east.

Site settings and data Nicolet (Quebec, Canada) The small municipality of Nicolet (Quebec) is located in the center of the St-Lawrence Lowland and is built on the Champlain Sea sensitive clays of eastern Canada (Lefebvre 1986). It has a well-documented history of landslides, with the most well-known event occurring on 12 November 1955 — killing 3 people and destroying several buildings including the bishop’s palace and the trade academy (Be´land 1956; Hurtubise and Rochette 1957). On 8 May 2006 a landslide occurred along the southwestern Nicolet River (Fig. 1). This landslide occurred on a 16 m high slope, was 80 m wide, and the crest of the river bank retrogressed up to 15 m. The landslide affected a former flow slide deposit as shown in Fig. 4. The debris slid into the river, almost completely blocking its course.

The area wetted by the run-up wave is visible on the aerial photograph, taken soon after the event, suggesting that the sliding mass moved quite rapidly (Fig. 4). The back scarp of the landslide was approximately 308 steep within the upper 12 m. Such a high angle is well above the average slope angle in the area (258 to 288), so the slope here is considered unstable. In addition, cracks adjacent to the landslide provide further evidence that the slope was potentially unstable. For this reason, a 60 000 m2 area, which included seven houses, was delimited as a safety perimeter. The restricted area was maintained for 10 days, thus allowing for a full evaluation of the site conditions and the design of mitigation measures. As part of this effort, the landslide scar was scanned with the TLS technique on 11 May 2006. The survey was made from three viewpoints situated on the opposite river flank at Published by NRC Research Press

1382 Fig. 3. Maximum range of TLS from various manufacturers with different wavelengths and laser classes (data from Point of Beginning 2008). R2, correlation coefficient.

Fig. 4. Aerial view on 9 May 2006 of the Nicolet Landslide. The lines with triangles indicate the former slide scars and the white line delimits the 2006 landslide. The landslide is located at the extrados of a meander. The change on the field on the other bank of the river in front of the landslide is likely the trace of the run-up wave induced by the landslide (darker colour in the field to the right of the river).

distances of 220 to 290 m. The composite TLS point cloud was generated with 2.1 million points having an effective point spacing of 5.0 to 7.8 cm. The point cloud was georeferenced using the ALS point cloud acquired on 8 December 2003 with a density of 2 to 4 points/m2. After the treatment and vegetation removal, the density of the digital elevation models (DEM) was around 0.8 points/m2. The resulting grid of the DEM has a cell size of 0.5 m. In our experience, this resolution is suitable for comparison with the TLS dataset. Saint-Barnabe´-Nord (Quebec, Canada) The Saint-Barnabe´-Nord slide, whose location is shown in

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Fig. 1, is a spread that occurred on 10 December 2005 along the Yamachiche River, 20 km northwest of Trois-Rivie`res (Quebec, Canada). The valley wall in which the slide took place was 30 m high with a slope angle of 258 (Locat 2007; Locat et al. 2008). It is located within fine grained Champlain Sea sediments. Before the slide, the slope had already been disturbed by a very large landslide with a width of more than 600 m approximately 2000 years B.P. (dated by the Carbon 14 method by the MTQ, in Locat 2007). The 2005 slide involved a part of the debris left by the older slide that covers the upper 15 m of the slope. At the toe of the slope the erosive side of a river meander is visible in Fig. 5a as well as a plain created by the river. The 2005 slide had 180 m of retrogression and was 160 m wide, involving fine-grained sediments that flowed in the river valley and obstructed its course (Fig. 5b). The debris caused a temporary lake that flooded the river valley. The displaced mass was dislocated in horsts and grabens, typical of spreads. No obvious triggering causes were found that explain this recent failure. There were no records of significant precipitation events or seismic activity in the days prior to the slide. Therefore, Locat (2007) and Locat et al. (2008) suppose that the concept of progressive failure could explain how erosion at the toe of the slope could have triggered this retrogressive slide. An ALS dataset was acquired by the MTQ 5 days after the event (5 points/m2) and an ALS HRDEM (0.5 m cell size) was created. Five months later, on 4 May 2006, 11 TLS scans were made around the scar and the deposits of the Saint-Barnabe´-Nord landslide to obtain a complete highresolution point cloud of the landslide (25–400 points/m2), especially in the area where the river was dammed by the landslide. The total point cloud with 6.2 millions points (mean point spacing between 4.5 and 7.5 cm) was georeferenced using the ALS point cloud. Sorge River (Lausanne, Switzerland) The Sorge River is located in the region of Lausanne, southwestern Switzerland (Fig. 2). In this region, the glaciers deposited moraine 13 200 years ago covering the underlying fluvial and marine sandstones that belong to the molasses of the Tertiary age (Gabus et al. 1987). Glacier lakes formed in many of the topographic depressions, which were filled by up to 25 m of varved sediments (clayey or sandy silts), and subsequently incised by the Sorge River. As the region of Lausanne is densely populated and developed, the river course is constrained due to channeling. Bank erosion is observed in many places. This erosive process becomes especially active during and after heavy rainfalls. To mitigate this problem, remedial works were carried out on the banks of a 150 m long river section between the spring and autumn of 2005. The river bed was enlarged (from between 3 and 5 m to between 5 and 11 m) and its banks were smoothed (3 to 4 m high banks with a slope angle of about 258). In narrow and in sinuous sections, stone embankments (up to 2.5 m in height) were constructed to stabilize the slope. We observed that two heavy rainfall events in March and April 2006 led to a rapid increase of the river flow rate. Published by NRC Research Press

Jaboyedoff et al. Fig. 5. Aerial photographs of the Saint-Barnabe´-Nord spread taken (a) in 1977 and (b) on 14 December 2005, 4 days after the slide. The rectangle in part (b) indicates the extent of Fig. 11 (source: MTQ, with permission).

Heavy precipitation between 8 and 10 April 2006 caused the rise of the river level of approximately 90 cm for several days. The increased energy of the Sorge River likely led to intense bank erosion and several landslides on the river banks were induced. TLS datasets acquired on 16 March and 12 April 2006 were used to follow the temporal and spatial evolution of the Sorge River banks. The river section was scanned from 12 viewpoints at distances between 24 and 55 m with a resolution (point spacing) on the landslides varying between 0.7 and 3.2 cm. Two superficial landslides with circular failure surfaces were analyzed in detail to better understand their geometry. Georeferencing of the TLS point clouds was achieved by DGPS ground control points.

Results Example of a quick survey: Nicolet (Quebec, Canada) The Nicolet landslide provides a good application of TLS in an emergency situation, including data acquisition, treatment, and interpretation within a few days. To avoid the danger posed by the landslide on the west bank, the land-

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slide was scanned from a safe position on the other side of the river. Figure 6 shows the differences between the post-slide TLS point cloud and the pre-slide ALS point cloud. In the scar area, the differences (up to 26 m) are measured parallel to the axis of the landslide body, which is close to the view direction. In the surroundings and the landslide deposits, the shortest distance is computed between the TLS and ALS point clouds (up to 6 m). This comparison also reveals that the landslide scarp is composed of a main slide (red lines in Fig. 6) and a secondary slide (yellow scarp in Fig. 6), which leads to higher horizontal differences in the left central part of the landslide. This difference is also put in evidence on the orthophoto and the very accurate HRDEM of the landslide back scarp (Fig. 7), which was obtained quickly from the TLS data. The TLS proved to be a very useful tool to rapidly create profiles across the new slope (Fig. 8). The collected data were used to design the new slope profile, allowing calculation of the volume of material required to be excavated to stabilize the slope (Fig. 9). In May 2006, this procedure allowed the rehabilitation of the houses as soon as possible. In the winter of 2007, a complete slope stabilization of the river banks was performed within the area of the 2006 landslide (Fig. 9b). The TLS point cloud of the Nicolet landslide allows also for the determination of the landslide volume by comparison of the pre- and post-slide HRDEM. Therefore, an HRDEM was created using the TLS point cloud and was compared to the pre-event ALS HRDEM. The missing volume in the departure zone of the landslide equaled 13 200 m3 and the actual mass flow deposit, above the river level, was 9250 m3. The volume of the landslide deposits below the water level and the eroded deposits cannot be assessed by TLS, but should be at least equal to 3950 m3 (13 200– 9250 m3). Example of a monitoring survey: Saint-Barnabe´-Nord (Quebec, Canada) ALS scans performed only a few days after the 2005 event gave a rare opportunity to study a recent spread and its failure mechanism (Locat 2007; Locat et al. 2008). Cross sections based on the ALS HRDEM were used to estimate the stability of the slope where the actual slide took place. Post-slide TLS point clouds provide a high-resolution 3D model of the Saint-Barnabe´-Nord landslide, which enables a study of the evolution of the morphology altered by weathering and erosion through time. As an example of those data, Fig. 10 shows a part of the debris of the SaintBarnabe´-Nord slide. In the middle of the picture, the principal horst is visible (grey in the photograph). It is 6 m in height, 78 m in width, and has a dip of 578. Ploughed furrows are visible on the TLS point cloud on the top of the graben (lower left of Fig. 10). These details were not detected on the ALS HRDEM as its cell size (0.5 m) is larger than these furrows. Small rivers and ponds left by precipitations are also clearly visible. Post-slide relief evolution in the slide scar After the main event on 10 December 2005, several minor slides occurred within the main scar. Their volumes can be Published by NRC Research Press

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Fig. 6. Comparison between the pre-landslide ALS HRDEM and the TLS point clouds of the Nicolet landslide made on 11 May 2006. In the scar area, the differences are measured horizontally parallel to the sliding direction. This gives an estimate of the landslide retrogression and enables the identification of a secondary slide scarp (yellow line). Shortest (oblique) differences are used to compare the surroundings of the landslide and the deposits. The line of the cross section in Fig. 8 is indicated.

Fig. 7. Orthophoto obtained from the aerial photograph taken on 9 May 2006 and the TLS HRDEM at Nicolet. Contour lines with a vertical spacing of 1 m (white lines) were derived from the TLS data. The main and secondary landslide scarps are shown as red and yellow lines, respectively (dark grey and light grey lines (both outlined in black), respectively, in the print version of this paper).

obtained by comparison of the TLS HRDEM with the ALS HRDEM (Fig. 11). The volume of these collapses range from 31 to 445 m3 with a total volume of approximately 1940 m3. The deposits of these minor slides are found as accumulations on the landslide body. Figure 12 show an example of such a minor landslide within the main scar. A compartment with a thickness of up to 4 m (volume of 358 m3) collapsed and led to a 3 to 3.5 m thick deposit (volume of 372 m3). Some areas were not visible by any of the TLS scans (shadowing), and some surfaces are thus not represented. This does not significantly affect the computation of vol-

umes and surfaces because for the calculation, interpolated surfaces were used. River erosion A few weeks after the damming of the river by the landslide, the river started to create a new path across the landslide toe. During the 5 months between the landslide and the TLS campaign, the river excavated an approximately 13 m deep channel (Fig. 11). The volume eroded by the river since the acquisition of the aerial ALS HRDEM is assessed by two methods. First, the differences between the ALS and the TLS HRDEMs were computed on a 67 m long river segPublished by NRC Research Press

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Fig. 8. Pre- and post-landslide slope profiles in the middle part of the Nicolet landslide (see text). See section location in Fig. 6.

Fig. 9. (a) View of the Nicolet landslide on 13 May 2006. The scale bar indicates the distances at the scar level. (b) View of the slope after first and second remediation on 25 October 2007. (Numbers above black dots indicate identical positions in both pictures.)

ment. Along this leg, the eroded volume equals 30 100 m3 for an average section of 450 m2. The second method is based on a cross section perpendicular to the river channel. Thirteen cross sections with a horizontal spacing of 5 m were created in PolyWorks using the ALS HRDEM and the TLS point cloud. The area eroded by the river is determined on each profile (Fig. 13). The section varies between 369 and 498 m2 with an average area of 438 m2. Both methods lead to a similar average bed cross section. Thus, the values can be used to extrapolate the eroded volume along the whole river path across the landslide, which has a length of approximately 285 m. Using a mean cross section of 438 m2,

Fig. 10. (a) TLS point cloud and (b) picture taken from the same viewpoint showing part of the displaced mass of the Saint-Barnabe´Nord spread on 4 May 2006. Similar features (pond, ploughed furrows) are linked by dashed lines.

the volume of river erosion reaches 125 000 m3, which does not include the actual bed of the river below the water level. Example of a time series: Sorge River (Lausanne, Switzerland) Bank destabilization The first landslide within the remodeled banks of the Published by NRC Research Press

1386 Fig. 11. Comparison between ALS (16 December 2005) and TLS HRDEMs (4 May 2006), showing the slope evolution with several small landslides and related deposits all around the main slide scar and the erosion of the Yamachiche River.

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the total displacement of the landslide (Fig. 15). Negative differences in the scar area were up to –0.5 m. At the foot of the slide, the accumulated materials caused positive altitude differences of up to +0.4 m. The overall geometry and morphology of the landslide suggested that the main slide (red line in Fig. 15) occurred before the secondary slide (orange line). The minor scarps (yellow lines) are probably caused by the displacement of the main body, which destabilized the entire slope. Simple geometric model A vertical cross section through the central part of the second landslide confirmed the rotational sliding mechanism (Fig. 16). The initially planar surface was rotated around an axis perpendicular to the cross section. The sliding surface was modeled with a sphere inscribed in the scar area using the TLS point cloud in PolyWorks software. It has a radius of 2.5 m and a centre point, corresponding to the rotation axis, located approximately 1.5 m above the river bank. Knowing the angle between the initial surface and the landslide head (a = 11.28) and the mean height of the scar measured as a straight line (h = 0.53 m), it is possible to calculate the radius (R) of the circular failure surface ½1

Sorge River section occurred before the first TLS campaign (16 March 2006) (Fig. 2). The scarp of this landslide was perfectly circular and had a maximal height of 1.3 m. The body of the landslide showed a typical morphology of a rotational landslide with a planar head and an accumulation of soil material at the toe. The landslide appeared to be caused by the heavy rainfall increasing river erosion and saturating the sediments with water. The TLS data were compared with a plane fitted through the nondislocated points of the flank, which represents the likely pre-landslide topography (Fig. 14). The computed differences clearly showed the scar area and the head of the slide (negative differences, up to –0.8 m), as well as the toe of the landslide (positive differences, up to +0.45 m). The missing volume in the head area was larger than the one deposited in the foot of the slide. This discrepancy can be explained by erosion of the toe during the high water conditions. Some of the displaced volume is also likely submerged and thus, not detectable by TLS. The comparison between the first and second TLS point cloud revealed minor movements in the main scarp with some small collapses. Saturation of the sediments caused by heavy rainfalls in April 2006 led to water outflows at the bottom of the landslide scar. These induced small earth flows eroding the landslide foot and depositing the material next to the river. A second landslide initiated during the intense rainfall event of 8 to 10 April 2006, but movement continued after the decrease of the river level. The landslide was composed of a main rotational slide and a smaller secondary rotational slide. Small scarps were also observable on both sides of the landslide. The main scarp was circular and reached a height of 0.6 m in the central part. The lateral extent of the landslide was approximately 5.5 m. The differences between the two scans directly revealed



h ¼ 2:72 m 2 sinða=2Þ

This radius (R = 2.72 m) is in good agreement with the radius of the best-fit sphere (2.5 m). A profile across the first landslide also confirmed a rotational sliding mechanism. The sphere fitted through the points of the main scar has a radius of 6.3 m. On the basis of the mean height of the scarp (h = 1.15 m) and the angle between the initial and rotated surface (a = 10.28), the radius of the failure surface sphere equals 6.5 m, which matches well with the best-fit sphere.

Discussion and conclusions The three case studies presented in this paper show the possibility of obtaining accurate topographic information from quick TLS surveys of landslides. Only a few hours are potentially necessary between data acquisition and their interpretation. In the case of the 2006 Nicolet landslide, the TLS HRDEM provided a fast assessment of the volume and a geometric characterization of the post-landslide slope. Not more than 3 h were necessary to perform the scans, and approximately the same amount of time was needed to create a first HRDEM, which was georeferenced using the prelandslide ALS HRDEM survey. In the case of the SaintBarnabe´-Nord landslide, the TLS scans enabled the study of the type and mechanism of failure through a detailed study of the debris morphology. The evolution of landslide movements and of erosion can be monitored by periodic scans as shown in the Sorge and Saint-Barnabe´-Nord case studies. Volumes and vectors of displacements can be obtained very accurately and can contribute to a detailed understanding of the failure mechanisms (Oppikofer et al. 2008). In addition, TLS time series are very interesting for the understanding of processes. The geometry of failure surfaces can be determined based on TLS measurements and the volume of a landslide can be calculated, as shown for the Sorge Published by NRC Research Press

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Fig. 12. Comparison of the ALS HRDEM with the TLS point cloud showing the shortest difference between the two surfaces at SaintBarnabe´-Nord and indicating volumes (V) removed and deposited. The blue to violet colors represent the landslide scar area (up to –4 m), whereas yellow to red colors indicate the deposit areas of this secondary landslide (up to +4 m).

Fig. 13. Cross section perpendicular to the new Yamachiche River course compared with the early post-landslide topography (vertical exaggeration 2). The bed topography is not considered, but it does not make a great difference for computation. The new river banks have a slope angle close to 158 on both sides.

Fig. 14. Comparison of the reference point cloud (acquired on 16 March 2006) with a primitive plane corresponding to the initial bank surface. The colors indicate the shortest distance between the point and the plane. Positive differences (green to red colors: 0 to +0.4 m) correspond to the foot of the slide, whereas the negative differences (light blue to violet colors: 0 to –0.8 m) correspond to the scar area and the head of the slide. The depression in the west side of the foot of the slide is due to a drainage pipe.

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Fig. 15. Altitude differences between the TLS point clouds of 16 March and 12 April 2006. The main and secondary rotational landslides are clearly visible (red and orange dashed lines). The small lateral scarps (yellow dashed lines) also show some displacement. The head of the main body (light blue to violet colors: 0 to –0.6 m) and the foot of the landslide (green to red colors: 0 to +0.4 m) can be identified.

Fig. 16. Cross section through the second landslide. The scan made on 16 March 2006 shows no traces of potential landsliding (dark grey line). The scan of 12 April 2006 (black line) shows the rotational displacement of the initial planar surface. The sphere inscribed in the main scarp is shown as a dashed line and the corresponding radius, scarp height, and rotation angle are featured.

River banks, with the circular failure surface of the two investigated landslides. This opens new perspectives into computation of stability. The main problems linked with the TLS data acquisition and treatment are vegetation, reflectivity, maximum range, and site accessibility. Site accessibility can be the source of shadowing, which can be a problem for interpretation. Nevertheless, depending on the goal of a survey, only a few points are necessary to model surfaces and thus enable the survey of slope movements, and usually the available data are sufficient to determine the landslide characteristics. In addition, the new generation of TLS will certainly greatly increase the maximum scanning range. This paper did not discuss the problem of accuracy, but the error in comparisons between TLS datasets is approximately 3 to 6 cm on single points (Oppikofer et al. 2008). The measured differences are all larger than this error and the errors

are significantly reduced by taking advantage of the high point density, i.e., by interpolated surfaces (Lindenbergh and Pfeifer 2005; Abella´n et al. 2009). Besides vegetation, changes in atmospheric conditions could lead to misalignments between sequential TLS point clouds. Such problems can be reduced by aligning the point clouds on the immediate surroundings of a landslide and separating them from ground surface displacements, because atmospheric influences lead to a continuous displacement field, i.e., increasing differences with increasing distance from the TLS device. In the future, the analysis of wave form and intensity of the back-scattered laser pulse will certainly provide some information on saturation of soils, giving more information for stability analysis. Last but not least, the precision of TLS will allow analysis of soil slopes prior to failure by showing small displacements, becoming a very useful tool in landslide detection and failure prediction. Published by NRC Research Press

Jaboyedoff et al.

Acknowledgements The authors would like to acknowledge the contribution to the paper of several individuals and to Romain Minoia who processed most of the data on the Nicolet and SaintBarnabe´-Nord sites. We thank the Ministe`re des Transports du Que´bec for providing the ALS and TLS data on the Nicolet slide. We would like to thank the two anonymous reviewers who improved the manuscript greatly.

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