Abstract
In the last decades, several approaches were proposed accounting for early warning systems to manage in real time the risks due to fast slope failures where important elements, such as structures, infrastructures and cultural heritage are exposed. The challenge of these approaches is to forecast the slope evolution, thus providing alert levels suitable for managing infrastructures in order to mitigate the landslide risk and reduce the “response” time for interventions. Two different strategies can be defined in this regard: an observation-based approach (OBA) and a process-based approach (PBA), this last one comprehensive of semi-empirical approaches (SEA) and a statistical-based one (SBA). At this aim, some experiments are being performed at different scales in the framework of technical applications, consulting activities and research projects managed by the Research Centre for the Geological Risk (CERI) of the University of Rome “Sapienza”. These experiments are testing different kind of sensors including interferometers, optical cams connected to Artificial Intelligence (AI) systems, extensometers, distantiometers, rock-thermometers, for detecting changes in rock properties and detecting stress-strain changes, as well as pluviometers, anemometers, hygrometers, air-thermometers, micro- or nano- accelerometers and piezometers for detecting possible triggers. The results obtained up to now encourage improving the SBA, based on data clouding, and testing them more extensively, at a national scale, by selecting test sites for experiencing their suitability for intervention strategies/procedures. These test sites will be selected along railways or roadways (in co-operation with the responsible National Agencies) where man-cut trenches could predispose to rock slides or falls that involve the infrastructures, in order to experience the suitability of SBA versus OBA approaches for early warning in the framework of lifelines management.
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Amitrano D, Grasso JR, Senfaute G (2005) Seismic precursory patterns before a cliff collapse and critical point phenomena. Geophys Res Lett 32:L08314. doi:10.1029/2004GL022270
Antonello G, Casagli N, Farina P, Leva D, Nico G, Siebar AJ, Tarchi D (2004) Ground-based SAR interferometry for monitoring mass movements. Landslides 1:21–28
Bigarré P, Klein E, Gueniffey Y, Verdel T (2011) Cloud monitoring: an innovative approach for the prevention of landslide hazards. In: Proceedings of the second world landslide forum, 2011 Rome, Abstracts Book WLF2, L16, p 475
Bozzano F, Mazzanti P, Esposito C, Moretto S, Rocca A (2016) Potential of satellite InSAR monitoring for landslide failure forecasting. In: Aversa S et al (eds) Landslides and engineered slopes. Experience, theory and practice, pp 523–530
Cornelius RR, Voight B (1994) Graphical and PC-software analysis of volcano eruption precursors according to the materials failure forecast method (FFMS). J Volcanol Geoth Res 64:295–320
Cruden DM, Varnes DJ (1996) Landslides types and processes. Landslides investigation and mitigation. Transportation research board. In: Turner AK, Shuster RL (eds) National Research Council. Special Report 247. National Research Council: Washington, DC, pp 36–75
Fiorucci M, Iannucci R, Lenti L, Martino S, Paciello A, Prestininzi A, Rivellino S (2016) Nanoseismic monitoring of gravity-induced slope instabilities for the risk management of an aqueduct infrastructure in Central Apennines (Italy). Nat Hazard. doi:10.1007/s11069-016-2516-5
Fukuzono T (1985) A new method for predicting the failure time of a slope. In: Proceeding of 4th international conference and field workshop on landslides, Tokyo, pp 145–150
Gaffet S, Guglielmi Y, Cappa F, Pambrun C, Monfret T, Amitrano D (2010) Use of the simultaneous seismic, GPS and meteorological monitoring for the characterization of a large unstable mountain slope in the southern French Alps. Geophys J Int 182:1395–1410
Lai XP, Cai MF, Xie MW (2006) In situ monitoring and analysis of rock mass behavior prior to collapse of the main transport roadway in Linglong Gold Mine, China. Int J Rock Mech Min Sci 43:640–646
Lenti L, Martino S, Paciello A, Prestininzi A, Rivellino S (2012) Microseismicity within a karstified rock mass due to cracks and collapses triggered by earthquakes and gravitational deformations. Nat Hazards 64:359–379
Martino S, Mazzanti P (2014) Integrating geomechanical surveys and remote sensing for sea cliff slope stability analysis: the Mt. Pucci case study (Italy). Nat Hazards Earth Syst Sci 14:831–848
Mazzanti P, Bozzano F, Cipriani I, Prestininzi A (2014) New insights into the temporal prediction of landslides by a terrestrial SAR interferometry monitoring case study. Landslides 12:55–68
Prestininzi A, Milli S (2015) The hydrogeological instability. In: Treccani (ed) Italy and its regions, the republican age, 2° vol, pp 367–381 (in Italian)
Szwedzicki T (2003) Rock mass behaviour prior to failure. Int J Rock Mech Min Sci 40:573–584
Voight B (1989) A relation to describe rate-dependent material failure. Science 243(4888):200–203
Acknowledgements
The Authors wish to thank the Municipality of Acuto for the authorization provided to the experimental activities; CNR-ISTI of Pisa for providing the prototypal Optical Cams; Italian Rail Network (RFI) for providing the railway track used an original target for railway infrastructures.
This study is part of a Ph.D. research (Matteo Fiorucci) and of a research grant activity (Andrea Fantini) funded by the CERI Research Centre of the “Sapienza” University of Rome.
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Bozzano, F. et al. (2017). Multisensor Landslide Monitoring as a Challenge for Early Warning: From Process Based to Statistic Based Approaches. In: Mikoš, M., Arbanas, Ž., Yin, Y., Sassa, K. (eds) Advancing Culture of Living with Landslides. WLF 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-53487-9_3
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DOI: https://doi.org/10.1007/978-3-319-53487-9_3
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