Detection and spatial prediction of rockfalls by means of terrestrial laser scanner monitoring
Introduction
Small scale rockfalls (up to several hundred m3) are the most frequent type of landslides on steep slopes such as rock walls in mountain areas (Copons and Vilaplana, 2008) and coastal cliffs (Rosser et al., 2005). Since rockfall is the fastest type of landslide (Varnes, 1978), its impact energy (and hence the geological hazard) can reach very high values (Agliardi and Crosta, 2003). When this natural phenomenon interacts with people, buildings and/or infrastructures, and when the value of the risk exceeds that of the acceptable risk (Fell et al., 2008), mitigation measurements should be applied to reduce the hazard, elements at risk and/or vulnerability. As long as effective corrective and/or preventive measures are not taken, rockfall will continue to be the primary cause of landslide fatalities in some countries such as Italy (Guzzetti, 2000).
A number of approaches have been developed to study rockfalls, including inventories (e.g. Malamud et al., 2004), susceptibility assessment (e.g. Frattini et al., 2008), frequency estimation (e.g. Stoffel et al., 2005) and hazard or risk assessment (e.g. Copons et al., 2005). A landslide hazard assessment should ideally predict where and when a slope failure is likely to occur (Guzzetti et al., 2004). As discussed by van Westen et al. (2006), it is difficult to provide reliable answers to these two questions. Both temporal and spatial predictions are usually based on the measurement of some precursory indicators before failure, e.g. crack opening, acoustic disturbances, micro-seismicity, and/or pre-failure deformation. Current works on large scale (from 104 to 106 m3) landslide forecasting (Crosta and Agliardi, 2003, Rose and Hungr, 2007, Oppikofer et al., 2008) are based on the detection of pre-failure deformation (Terzaghi, 1950, Saito, 1969, Voight, 1989, Leroueil, 2001). Similarly, some authors observed an increase in rockfall frequency as a precursory indicator of larger failures (Sartori et al., 2003, Cruden and Martin, 2007). Nevertheless, the literature on coupling spatial and temporal prediction of small scale rockfalls is very scarce (Rosser et al., 2007).
Most studies on landslide forecasting employ point-based instruments of measurement (e.g. DGPS, extensometers and total stations) to monitor displacements (e.g. Zvelebill and Moser, 2001, Crosta and Agliardi, 2003, Rose and Hungr, 2007). Despite their accuracy, these instruments suffer from certain disadvantages, such as the relatively low density of points. Moreover, since the location of the moving areas is often unknown, a method to detect the portions of a slope affected by displacement is still required. The possibility of acquiring topographic datasets with high accuracy and spatial resolution, using laser, optical and/or radar technologies, mounted on terrestrial, aerial and/or satellite instruments are currently opening up new ways to visualize, model and interpret surface processes (e.g. Abellán et al., 2006, Oppikofer et al., 2008, Dunning et al., 2009, Lim et al., 2006, Abellán, 2009). One of these new remote sensing tools, a Terrestrial Laser Scanner (TLS) was used in this study for the detection and spatial prediction of rockfall at the Puigcercós test site (Pallars Jussà, Catalonia, Spain, Fig. 1a). The first part of this research deals with the geomorphological evolution of the rock face: the main events that occurred between September 2007 and July 2008 are described. The second part focuses on the detection of pre-failure deformation as a precursory indicator of rockfall. In contrast to point-based measurements, we were able to detect deformation over the whole rock face. This approach could help answering the important question: where will rockfall occur?
Section snippets
Study area
The rock face studied (Fig. 1b,c) is the main scar of a landslide that took place on the night of 13 January 1881. According to Vidal (1881), the landslide was most likely triggered by continuous rainfall. This landslide was classified as a complex roto-translational slide (Varnes, 1978, Corominas and Alonso, 1984), which evolved into an earth flow in its zone of accumulation. The displaced material occupied an area of 78,520 m2.
The slope movement destroyed part of the old village of Puigcercós.
Terrestrial laser scanner (TLS)
The remote sensing tool employed in this study is a TLS. This instrument is also known as a ground-based LIDAR (Light Detection And Ranging). We used an Optech Intelligent Laser Ranging and Imaging System (ILRIS3D). The instrument consists of a transmitter/receiver of infrared laser pulses (1535 nm wavelength) and a scanning device. The laser beam is directly reflected on the land surface, obviating the need for the existence of intermediate prism reflectors. Distance measurement (range, ρ) is
Geomorphological evolution of the rock face
The five main rockfall events that occurred during the period of study (A to E) are shown in Fig. 3. This figure also shows the areas of deposition of events A and D. The greater the area with Di positive values, the greater the volume of the rockfall(s).
Event A has the largest magnitude (87 m3). Volumes of events B to E range from 1 to 10 m3. Events A, B, D and E were clearly controlled by open discontinuities, sub-parallel to the rock face and visible in the field. As many researchers have
Discussion
The first part of this research deals with the geomorphological evolution of the rock slope during the analyzed time span and evaluates the dimensions and geometry of the main events and rockfall frequency. After the 1881 landslide that created the scarped rock slope, tension cracks have been generated by the loss of lateral confining pressure. These discontinuities constitute the detachment surfaces for subsequent minor failures. Despite the occurrence of rockfall and rockslides, toppling is
Conclusions
A total of 42 rockfalls ranging from 10− 3 to 87 m3 were recorded during the 10-month study period. Dry/humid intervals correspond to lower/higher rockfall frequency, respectively. The detection of pre-failure deformation in area B enabled the prediction of a toppling event (event B). Moreover, an ongoing displacement of a few centimetres was observed in area F. The displacement is higher in the upper part of the moving block, allowing us to anticipate a toppling failure (event F). These results
Acknowledgements
Financial support from the Spanish Ministry of Science and Education (pre-doctoral grant AP-2007-1852) is gratefully acknowledged. This work was also funded by Geomodels Institute, the project TopoIberia CSD2006-0004/Consolider-Ingenio2010, SAFELAND European project (FP7-226479) and the MEC project CGL2006-06596 (DALMASA). The authors wish to acknowledge David Garcia for his support in the TLS data acquisition and IGAR group for it support during the review process of the manuscript. George von
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