Environmental Earth Sciences

, Volume 61, Issue 7, pp 1467–1472 | Cite as

Comparing the performance of base map scales in GIS-based avalanche simulation: a case study from Palandöken, Turkey

  • Abdurrahim AydınEmail author
Original Article


Snow avalanches are very complex and dynamic events that cause serious risk to human lives, infrastructure, and facilities in mountain environments. In this study, GIS-based avalanche simulations were investigated in terms of base map scale over the simulation sensitivity. Study area consisted of the avalanche region from Sultanseki Hill to Hodaklar Hill near the Palandöken skiing site in Erzurum, eastern part of Turkey. In analysis, 1:1,000 (field surveying), 1:5,000 (orthophoto) and 1:25,000 (standard topographic maps) scaled maps were used as base maps. The avalanche simulation was constructed by Triangulated Irregular Network (TIN) extracted from the base maps by using GIS-based ELBA+ simulation model. When 1:1,000-scaled map results were taken as reference simulations at 1:25,000-scaled maps, the best results for the potential area affected by avalanche and the maximum run-out distance were provided. Besides, using 1:5,000-scaled maps showed close correlation with the maximum track width, velocity, flow height, and pressure.


Avalanche simulation Base map GIS ELBA+ Palandöken 


  1. American Society of Photogrammetry, (1980) Manual of photogrammetry, 4th edn. Falls Church, VAGoogle Scholar
  2. Behbahani SMR, Ghajarnia HR, Bani-Habib ME (2006) The effect of base map scale on the accuracy of floodplain zoning using GIS. J Appl Sci 6(1):20–26CrossRefGoogle Scholar
  3. Cao C, Lam NSN (1997) Understanding the scale and resolution effects in remote sensing and GIS. In: Quattrochi DA, Goodchild MF (eds) Scale in remote sensing and GIS. CRC Lewis, Boca Raton, pp 57–72Google Scholar
  4. Cappabianca F, Barbolini M, Natale L (2008) Snow avalanche risk assessment and mapping: a new method based on combination of statistical analysis, avalanche dynamic simulation and empirically-based vulnerability relations integrated in a GIS platform. Cold Reg Sci Technol 54(3):193–205. doi: 10.1016/j.coldregions.2008.06.005 CrossRefGoogle Scholar
  5. Carrara A, Guzzetti F, Cardinali M, Reichenbach P (1999) Use of GIS technology in the prediction and monitoring landslide hazard. Nat Hazards 20(2–3):117–135CrossRefGoogle Scholar
  6. Chaubey I, Cotter AS, Costello TA, Soerens TS (2005) Effect of DEM data resolution on SWAT output uncertainty. Hydrol Process 19:621–628. doi: 10.1002/hyp.5607 CrossRefGoogle Scholar
  7. Dutta D, Herath S (2001) Effect of DEM accuracy in flood inundation simulation using distributed hydrological models. Seisan Kenkyu 53(11):602–605Google Scholar
  8. Formann E, Habersack HM, Schober St. (2007) Morphodynamic river processes and techniques for assessment of channel evolution in alpine gravel bed rivers. Geomorphology 90:340–355. doi: 10.1016/j.geomorph.2006.10.029 Google Scholar
  9. Gruber U (2001) Using GIS for avalanche hazard mapping in Switzerland. In: Proceedings of the 2001 ESRI international user conference, San Diego, USAGoogle Scholar
  10. Gruber U, Bartelt P (2007) Snow avalanche hazard modelling of large areas using shallow water numerical methods and GIS. Environ Model Softw 22:1472–1481. doi: 10.1016/j.envsoft.2007.01.001 CrossRefGoogle Scholar
  11. Guzzetti F, Crosta G, Detti R, Agliardi F (2002) STONE: a computer program for the three-dimensional simulation of rock-falls. Comput Geosci 28(9):1079–1093. doi: 10.1016/S0098-3004(02)00025-0 CrossRefGoogle Scholar
  12. Haile AT, Rientjes THM (2005) Effects of LIDAR DEM resolution in flood modelling: a model sensitivity study for the city of Tegucigalpa, Honduras. ISPRS WGIII/3, III/4, v/3 workshop Laser scanning 2005, 12–14 September 2005, Enschede, The NetherlandsGoogle Scholar
  13. Hay GJ, Goodenough DG, Niemann KO (1997) Spatial thresholds, image-objects, and upscaling: a multi-scale evaluation. Remote Sens Environ 62:1–19CrossRefGoogle Scholar
  14. Kleemayr K (2004) Modelling and simulation in snow science. Math Comput Simul 66:129–153. doi: 10.1016/j.matcom.2003.11.009 CrossRefGoogle Scholar
  15. Kleemayr K, Tartarotti T, Frandl T, Kessler J, Seer G (2000) Dynamically-statistical analysis of 124 catastrophic avalanches with the avalanche computation models of Voellmy, PCM, Lied and ELBA. In: International workshop hazard mapping in avalanching areas. 2–7 April 2000 Tyrol, AustriaGoogle Scholar
  16. Kriz K (2001) Using GIS and 3D Modeling for avalanche hazard mapping. In: ICA-CMC session of mountain cartography, Beijing, ChinaGoogle Scholar
  17. Marceau DJ (1999) The scale issue in social and natural sciences. Can J Remote Sens 25(4):347–356Google Scholar
  18. Mason D, Maidment DR (2000) An analysis of methodology for generating watershed parameters using GIS, CRWR Online Report, 00-3. Accessed 22 Feb 2009Google Scholar
  19. NiT (2005) ELBA+ Handbuch. NiT Technisches Büro GmbH, Vienna, Pressbaum, 24 May 2005, pp 1–98Google Scholar
  20. Oliviera F, Maidment D (1999) System of GIS based hydrologic and hydraulic applications for highway engineering: Summary Report. Center For Transportation Research, Bureau of Engineering Research, The University of Texas at Austin, USAGoogle Scholar
  21. Oller P, Muntan E, Marturia J, Garcia C, Garcia A, Martinez P (2006) The avalanche data in the Catalan Pyrenees. 20 years of avalanche mapping. In: Proceedings of the international snow science workshop, Colorado, USA, pp 305–313Google Scholar
  22. Peuquet DJ (1994) It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Ann Assoc Am Geogr 84:441–461CrossRefGoogle Scholar
  23. Renyi L, Nan L (2002) Flood area and damage estimation in Zhejiang, China. J Environ Manag. doi: 10.1006/jema.2002.0544
  24. Sauermoser S (2006) Avalanche hazard mapping—30 years experience in Austria. In: Proceedings of the international snow science workshop. Colorado, USA, pp 314–321Google Scholar
  25. Sauermoser S, Illmer D (2002) The use of different avalanche calculation models practical experiences. In: International congress INTERPRAEVENT. 2:741–750 (in the Pacific Rim-Matsumoto, Japan)Google Scholar
  26. Toppe R (1987) Terrain models—a tool for natural hazard mapping, avalanche formation, movement and effects. In: Proceedings of the Davos symposium, September 1986, IAHS publ. no. 162Google Scholar
  27. Trung TN (2004) The multi-resolution characteristics of spatial data in Vietnam Land Administration. In: Proceedings of ISPRS, Istanbul, Turkey, pp 238–243Google Scholar
  28. Volk G, Kleemayr K (1999) Lawinensimulationmodell ELBA. Wildbach und Lawinenverbau, 63. Jg. Heft 138Google Scholar
  29. Wang Y, Meng H (2008) A multi-scale road visualisation method in navigable database. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol 37, Part B4, BeijingGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.The Western Black Sea Forestry Research InstituteBoluTurkey

Personalised recommendations