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Environmental Geology

, Volume 55, Issue 2, pp 441–452 | Cite as

Susceptibility analysis for slides and rockfall: an example from the Northern Calcareous Alps (Vorarlberg, Austria)

  • Michael RuffEmail author
  • Joachim Rohn
Original Article

Abstract

In this paper a tool for semi-quantitative susceptibility assessment at a regional scale is presented which is applicable at areas with complex geological setting. At a study area within the Northern Calcareous Alps geotechnical mappings were implemented into a Geographical Information System and analysed as grid data with a cell size of 25 m. The susceptibility to sliding and falling processes was considered according to five classes (very low, low, medium, high, very high). Susceptibility to sliding was analysed using an index method. The layers of lithology, bedding conditions, tectonic faults, slope angle, slope aspect, vegetation and erosion were combined iteratively. Dropout zones of rockfall material were determined with help of a Digital Elevation Model. The movement of rolling rock samples was modelled by a cost analysis of all potential rockfall trajectories. These trajectories were also divided into five susceptibility classes. The susceptibility maps are presented in a general way to be used by communities and spatial planners. Conflict areas of susceptibility and landuse were located and can be presented destinctively.

Keywords

Susceptibility Landslides Rockfall GIS Northern Calcareous Alps Vorarlberg Austria 

Notes

Acknowledgments

The studies were financed by the Federal Government of Vorarlberg and the INATURA Museum Dornbirn. Special thanks go to the field workers Nadine Hawelka, Georg Hils, Christian Schanz and Marcel Fulde. Furthermore we would like to thank the Federal Surveying Office of Austria (BEV) for providing the data.

References

  1. Acharya G, De Smedt F, Long NT (2006) Assessing landslide hazard in GIS: a case study from Rasuwa, Nepal. Bull Eng Geol Environ 65:99–107CrossRefGoogle Scholar
  2. Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44CrossRefGoogle Scholar
  3. Ayalew L, Yamagishi H, Ugawa N (2004) Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides 1:73–82CrossRefGoogle Scholar
  4. Ayalew L, Yamagishi H, Marui H, Kanno T (2005) Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications. Eng Geol 81:432–445CrossRefGoogle Scholar
  5. Azzoni A, Rossi PP, Drigo E, Giani GP, Zaninetti A (1991) In situ observation of rockfall analysis parameters. In: Bell H (ed) Landslides, Proceedings of the 6th international symposium on landslides in Christchurch vol 1, New Zealand, pp 307–314Google Scholar
  6. Barredo JI, Benavides A, Hervas J, Van Westen CJ (2000) Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain. Int J Appl Earth Obs Geoinf 2(1):9–23CrossRefGoogle Scholar
  7. Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS-technology in mapping landslide hazards. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards, pp 135–176Google Scholar
  8. Cruden DM, Varnes DJ (1996) Landslide types and processes. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation. Special Report 257, Transportation Research Board, National Research Council, pp 36–75Google Scholar
  9. Eisbacher GH, Linzer HG, Meier L, Polinski R (1990) A depth extrapolated structural transect across the Northern Calcareous Alps of western Tirol. Ecol Geol Helv 83(3):711–725Google Scholar
  10. Jenson SK, Domingue JO (1988) Extracting topographic structure from digital elevation data for geographic information system analysis. Photo Eng Remote Sens 54(11):1593–1600Google Scholar
  11. Juang CH, Lee DH, Scheu C (1992) Mapping slope failure potential using fuzzy sets. J Geot Eng 118:475–494CrossRefGoogle Scholar
  12. Lee S, Ryu JH, Won JS, Park HJ (2004) Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Eng Geol 71:289–302CrossRefGoogle Scholar
  13. Linzer HG, Ratschbacher L, Frisch W (1995) Transpressional collision structures in the upper crust: the fold-thrust belt of the Northern Calcareous Alps. Tectonophysics 242:41–61CrossRefGoogle Scholar
  14. Kassebeer W, Ruff M (2003) Georisikokarte Vorarlberg—Analyse geogener Gefährdungen mit GIS im regionalen Maßstab. In: Strobl J, Blaschke Th, Griesebner G (Eds) Angewandte Geographische Informationsverarbeitung XV, pp 186–195Google Scholar
  15. Moser M, Üblagger G (1984) Vorschläge zur Erstellung von geotechnischen Karten und Erhebungen im Rahmen von Gefahrenzonenplänen in Hangbereichen. Int Symp Interpraevent Villach Vol II:275–287Google Scholar
  16. Ohlmacher GC, Davis J (2003) Using Multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343CrossRefGoogle Scholar
  17. Ruff M (2005) GIS-gestützte Risikoanalyse für Rutschungen und Felsstürze in den Ostalpen (Vorarlberg, Österreich). PhD. Thesis Department of Bau-, Geo- and Umweltwissenschaften, University of Karlsruhe (TH) 144 p; Karlsruhe University Press (in german) http://www.uvka.de/univerlag/volltexte/2005/46/
  18. Ruff M, Czurda K (2007) Landslide Susceptibility Analysis with a Heuristic Approach at the Eastern Alps (Vorarlberg, Austria). Geomorphology, review (in press)Google Scholar
  19. Scheidegger E (1975) Physical aspects of natural catastrophes. Elsevier, Amsterdam, p 289Google Scholar
  20. Thierry P, Vinet L (2003) Mapping an urban area prone to slope instability: Greater Lyons—Bull. Env Geol Env 62:135–143Google Scholar
  21. Turrini MC, Visintainer P (1998) Proposal of method to define areas of landslide hazard and application to an area of the Dolomites, Italy. Eng Geol 49:255–265CrossRefGoogle Scholar
  22. Van Westen CJ, van Asch TWJ, Soeters R (2005): Landslide hazard and risk zonation—why is it still so difficult? Bull Eng Geol Env 65/2:167–184Google Scholar
  23. Zhou G, Esaki T, Mitani M, Xie M, Mori J (2003) Spatial probabilistic modelling of slope failure using integrated GIS Monet Carlo simulation approach. Eng Geol 68:373–386CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.Ingenieure Bart AGSt GallenSwitzerland
  2. 2.Department of Applied Geology (AGK)University of Karlsruhe (TH)KarlsruheGermany
  3. 3.Department of Applied GeologyUniversity of Erlangen-NürnbergErlangenGermany

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