Natural Hazards

, Volume 73, Issue 1, pp 97–110 | Cite as

Spatial pattern of landslides in Swiss Rhone Valley

  • Marj Tonini
  • Andrea Pedrazzini
  • Ivanna Penna
  • Michel Jaboyedoff
Original Paper

Abstract

The present study analyses the spatial pattern of quaternary gravitational slope deformations (GSD) and historical/present-day instabilities (HPI) inventoried in the Swiss Rhone Valley. The main objective is to test if these events are clustered (spatial attraction) or randomly distributed (spatial independency). Moreover, analogies with the cluster behaviour of earthquakes inventoried in the same area were examined. The Ripley’s K-function was applied to measure and test for randomness. This indicator allows describing the spatial pattern of a point process at increasing distance values. To account for the non-constant intensity of the geological phenomena, a modification of the K-function for inhomogeneous point processes was adopted. The specific goal is to explore the spatial attraction (i.e. cluster behaviour) among landslide events and between gravitational slope deformations and earthquakes. To discover if the two classes of instabilities (GSD and HPI) are spatially independently distributed, the cross K-function was computed. The results show that all the geological events under study are spatially clustered at a well-defined distance range. GSD and HPI show a similar pattern distribution with clusters in the range 0.75–9 km. The cross K-function reveals an attraction between the two classes of instabilities in the range 0–4 km confirming that HPI are more prone to occur within large-scale slope deformations. The K-function computed for GSD and earthquakes indicates that both present a cluster tendency in the range 0–10 km, suggesting that earthquakes could represent a potential predisposing factor which could influence the GSD distribution.

Keywords

Ripley’s K-function Landslides Cluster Spatial pattern Swiss Alps 

Notes

Acknowledgments

This work was partly supported by the SNFS project No. 200021-140658: “Analysis and modelling of space–time patterns in complex regions.”

References

  1. Abele G (1974) Bergstürze in den Alpen: Wissenschaftliche Alpenvereinshefte. Münche Ausschüsse des Deutschen und Österreichischen Alpenvereins 25:231Google Scholar
  2. Ansari A, Noorzad A, Zafarani H (2009) Clustering analysis of the seismic catalog of Iran. Comput Geosci 35(3):475–486CrossRefGoogle Scholar
  3. Baddeley A, Turner R (2005) Spatstat: an R package for analyzing spatial point patterns. J Stat Softw 12(6):1–42Google Scholar
  4. Baddeley A, Moller J, Waagepetersen R (2000) Non- and semiparametric estimation of interaction in inhomogeneous point patterns. Stat Neerl 54:329–350CrossRefGoogle Scholar
  5. Bai SB, Wang J, Lü G, Zhou P, Hou SS, Xu SN (2010) GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the three Gorges area, China. Geomorphology 115:23–31CrossRefGoogle Scholar
  6. Bertolini G, Guida M, Pizziolo M (2005) Landslides in Emilia-Romagna region (Italy): strategies for hazard assessment and risk management. Landslides 2(4):302–312. doi: 10.1007/s10346-005-0020-1 CrossRefGoogle Scholar
  7. Besag J (1977) Discussion of Dr Ripley’s paper. J Roy Stat Soc B 39:193–195Google Scholar
  8. Bonnard C, Forlati F, Scavia C (2004) Identification and mitigation of large landslide risks in Europe: advances in risk assessment. Balkema, Amsterdam, p 317Google Scholar
  9. Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statistical models in evaluating landslide hazard. Earth Surf Process Landf 16:427–445CrossRefGoogle Scholar
  10. Conoscenti C, Di Maggio C, Rotigliano E (2008) GIS analysis to assess landslide susceptibility in a fluvial basin of NW Sicily (Italy). Geomorphology 94(3–4):325–339CrossRefGoogle Scholar
  11. Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Shuster RL (eds) Landslides: investigation and mitigation, Transportation Research Board, Special Report 247, pp 36–75Google Scholar
  12. Diggle PJ (2003) Statistical analyses of spatial point patterns, 2nd edn. Arnold, LondonGoogle Scholar
  13. Dixon PM (2002) Ripley’s K function. In: El-Shaarawi AH, Piergorsch WW (eds) The encyclopedia of environmetrics. Wiley, New York, pp 1796–1803Google Scholar
  14. Erener A, Düzgün HSB (2012) Landslide susceptibility assessment: what are the effects of mapping unit and mapping method? Environmental Earth Sciences 66(3):859–877CrossRefGoogle Scholar
  15. Faeh D, Giardini D, Bay F, Bernardi F, Braunmiller J, Deichmann N, Furrer M, Gantner L, Gisler M, Isenegger D, Jimenez MJ, Kästli P, Koglin R, Masciadri V, Rutz M, Scheidegger C, Schibler R, Schorlemmer D, Schwarz-Zanetti G, Steimen S, Sellami S, Wiemer S, Wössner J (2003) Earthquake catalogue of Switzerland (ECOS) and the related macroseismic database. Eclog Geol Helv Swiss J Geosci 96(2):219–236Google Scholar
  16. Faenza L, Pierdominici S (2007) Statistical occurrence analysis and spatio-temporal distribution of earthquakes in the Apennines (Italy). Tectonophysics 439(1–4):13–31CrossRefGoogle Scholar
  17. Fischer T, Horálek J (2003) Space-time distribution of earthquake swarms in the principal focal zone of the NW Bohemia/Vogtland seismoactive region: period 1985–2001. J Geodyn 35(1–2):125–144CrossRefGoogle Scholar
  18. Guzzetti F, Carrara A, Cardinaly M, Reichenbach P (1999) Landslide hazard evaluation: a review if current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31:181–216CrossRefGoogle Scholar
  19. Hering AS, Bell CL, Genton MG (2009) Modeling spatio-temporal wildfire ignition point patterns. Environ ad Ecol Stat 16:225–250CrossRefGoogle Scholar
  20. Hermanns RL, Strecker MR (1999) Structural and lithological controls on large Quaternary rock avalanches (sturzstroms) in arid northwestern Argentina. Geol Soc Am Bull 111(6):934–948CrossRefGoogle Scholar
  21. Hinderer M (2001) Late quaternary denudation of the Alps, valley and lake fillings and modern river loads. Geodin Acta 14:231–263CrossRefGoogle Scholar
  22. Hutchinson JN (1988) General report: morphological and geotechnical parameters of landslides in relation to geology and hydrogeology. In: Bonnard C (ed) Proceedings of the fifth international symposium on landslides. Balkema, Rotterdam, pp 3–35Google Scholar
  23. Jarman D (2006) Large rock slope failures in the Highlands of Scotland: characterisation, causes and spatial distribution. Eng Geol 83:161–182CrossRefGoogle Scholar
  24. Keefer DK (1984) Landslides caused by earthquakes. Geol Soc Am Bull 95:406–421CrossRefGoogle Scholar
  25. Korup O (2005) Distribution of landslides in southwest New Zealand. Landslides 2(1):43–51CrossRefGoogle Scholar
  26. Lee S, Ryu J-H, Kim I-S (2007) Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea. Landslides 4:327–338CrossRefGoogle Scholar
  27. Lotwick HW, Silverman BW (1982) Methods for analysing spatial processes of several types of points. J R Statist Soc Ser B 44:406–413Google Scholar
  28. Maurer HR, Burkhard M, Deichmann N, Green AG (1997) Active tectonism in the central Alps: contrasting stress regimes north and south of Rhone Valley. Terra Nova 9:91–94CrossRefGoogle Scholar
  29. Mosar J, Stampfli GM, Girod F (1996) Western Prealpes Medianes Romandes; timing and structure; a review. Eclogae Geol Helv 89:389–425Google Scholar
  30. Mukhopadhyay B, Dasgupta S, Dasgupta S (2004) Clustering of earthquake events in the Himalaya—its relevance to regional tectonic set-up. Gondwana Res 7(4):1242–1247CrossRefGoogle Scholar
  31. Nandi A, Shakoor AA (2010) GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110:11–20CrossRefGoogle Scholar
  32. Oh HJ, Lee S (2011) Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system. Environ Earth Sci 62:935–951CrossRefGoogle Scholar
  33. Pedrazzini A (2012) Characterization of gravitational rock slope deformations at different spatial scales based on field, remote sensing and numerical approaches. PhD Thesis. Institute of Geomatics and Analysis of Risk, University of LausanneGoogle Scholar
  34. Preusser F, Reitner J, Schlüchter C (2010) Distribution, geometry, age and origin of overdeepened valleys and basins in the Alps and their foreland. Swiss J Geosci 103:407–427CrossRefGoogle Scholar
  35. R Development Core Team (2012) A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/
  36. Ripley BD (1976) The second-order analyses of stationary point processes. J Allied Probab 13:255–266Google Scholar
  37. Ripley BD (1988) Statistical inference for spatial processes. Cambridge University Press, Cambridge, MACrossRefGoogle Scholar
  38. Steck A (1984) Structures de deformations tertiaires dans les Alpes centrales (transversale Aar-Simplon-Ossola). Eclogae Geol Helv 77(1):55–100Google Scholar
  39. Stoyan D (2006) Fundamentals of point process statistics. In: Case studies in spatial point process modeling. Lecture Notes in Statistics 185, Springer, BerlinGoogle Scholar
  40. Tsai CY, Shieh CF (2008) A study of the time distribution of inter-cluster earthquakes in Taiwan. Phys A 387(22):5561–5566CrossRefGoogle Scholar
  41. Varga P, Krumm F, Riguzzi F, Doglioni C, Süle B, Wang K, Panza GF (2012) Global pattern of earthquakes and seismic energy distributions: Insights for the mechanisms of plate tectonics. Tectonophysics 530–531:80–86CrossRefGoogle Scholar
  42. Zuo R, Agterberg FP, Cheng Q, Yao L (2009) Fractal characterization of the spatial distribution of geological point processes. Int J Appl Earth Obs Geoinf 1:394–402CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Marj Tonini
    • 1
  • Andrea Pedrazzini
    • 1
  • Ivanna Penna
    • 1
  • Michel Jaboyedoff
    • 1
  1. 1.Faculté des Géosciences et de l’Environnement, Centre de Recherche en Environnement Terrestre (CRET)Université de LausanneLausanneSwitzerland

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