Advertisement

Frontiers of Earth Science

, Volume 5, Issue 1, pp 70–81 | Cite as

Landslide hazard zonation assessment using GIS analysis at Golmakan Watershed, northeast of Iran

  • Mohammad Reza Mansouri Daneshvar
  • Ali Bagherzadeh
Research Article

Abstract

Landslide hazard is one of the major environmental hazards in geomorphic studies in mountainous areas. For helping the planners in selection of suitable locations to implement development projects, a landslide hazard zonation map has been produced for the Golmakan Watershed as part of Binaloud northern hillsides (northeast of Iran). For this purpose, after preparation of a landslide inventory of the study area, some 15 major parameters were examined for integrated analysis of landslide hazard in the region. The analyses of parameters were done by geo-referencing and lateral model making, satellite imaging of the study area, and spatial analyses by using geographical information system (GIS). The produced factor maps were weighted with analytic hierarchy process (AHP) method and then classified. The study area was classified into four classes of relative landslide hazards: negligible, low, moderate, and high. The final produced map for landslide hazard zonation in Golmakan Watershed revealed that: 1) the parameters of land slope and geologic formation have strong correlation (R 2 = 0.79 and 0.83, respectively) with the dependent variable landslide hazard (p<0.05). 2) About 18.8% of the study area has low and negligible hazards to future landslides, while 81.2% of the land area of Golmakan Watershed falls into the high and moderate categories.

Keywords

landslide hazard zonation map geographical information system (GIS) analytic hierarchy process (AHP) Golmakan Watershed 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Akgün A, Bulut F (2007). GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environmental Geology, 51(8): 1377–1387CrossRefGoogle Scholar
  2. Ayalew L, Yamagishi H (2005). The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, central Japan. Geomorphology, 65(1–2): 15–31CrossRefGoogle Scholar
  3. Ayalew L, Yamagishi H, Marui H, Kano T (2005). Landslides in Sado Island of Japan: Part II. GIS-based hazard mapping with comparisons of results from two methods and verifications. Geomorphology, 81:432–445Google Scholar
  4. 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(1): 73–81CrossRefGoogle Scholar
  5. Barredo J, Benavides A, Hervás J, van Westen C J (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
  6. Brabb E E (1984). Innovative approaches to landslide hazard mapping. In: Proceedings of 5th International Symposium on Landslides, Rotterdam.1059–1074Google Scholar
  7. Carrara A, Crosta G, Frattini P (2008). Comparing models of debris-flow susceptibility in the alpine environment. Geomorphology, 94(3–4): 353–378CrossRefGoogle Scholar
  8. Cevik E, Topal T (2003). GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environmental Geology, 44(8): 949–962CrossRefGoogle Scholar
  9. Chi K, Lee K, Park N (2002). Landslide stability analysis and prediction modeling with landslide occurrences on KOMPSAT EOC imagery. Korean J Remote Sensing, 18(1): 1–12Google Scholar
  10. Clerici A, Perego S, Tellini C, Vescovi P (2002). A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology, 48(4): 349–364CrossRefGoogle Scholar
  11. Dai F C, Lee C F, Li J, Xu Z W (2001). Assessment of landslide hazard on the natural terrain of Lantau Island, Hong Kong. Environmental Geology, 43(3): 381–391Google Scholar
  12. Dai F C, Lee C F, Ngai Y Y (2002). Landslide risk assessment and management: An overview. Eng Geol, 64(1): 65–87CrossRefGoogle Scholar
  13. Eastman J R, Jin W, Kyem P A K, Toledano J (1995). Raster procedures for multi-criteria/multiobjective decisions. Photogramm Eng Remote Sensing, 61(5): 539–547Google Scholar
  14. Ercanoglu M, Gokceoglu C, Van Asch T HWJ (2004). Landslide hazard zoning north of Yenice (NW Turkey) by multivariate statistical techniques. Nat Hazards, 32(1): 1–23CrossRefGoogle Scholar
  15. Fall M, Azzam R, Noubactep C (2006). A multi-method approach to study the stability of natural slopes and landslide susceptibility mapping. Eng Geol, 82(4): 241–263CrossRefGoogle Scholar
  16. Griffiths J S, Mather A E, Hart A B (2002). Landslide susceptibility in the Rio Aguas catchment, SE Spain. Q J Eng Geol Hydrogeol, 35(1): 9–17CrossRefGoogle Scholar
  17. Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999). Landslide hazard evaluation: A review of current techniques and their application in a multi-scale study, central Italy. Geomorphology, 31(1–4): 181–216CrossRefGoogle Scholar
  18. Jiang H, Eastman J R (2000). Application of fuzzy measures in multicriteria evaluation in GIS. Int J Geogr Inf Sci, 14(2): 173–184CrossRefGoogle Scholar
  19. Lee S (2005). Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens, 26(7): 1477–1491CrossRefGoogle Scholar
  20. Lee S, Choi J, Min K (2004). Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. Int J Remote Sens, 25(11): 2037–2052CrossRefGoogle Scholar
  21. Malczewski J (1999). GIS and Multicriteria Decision Analysis. New York: John Wiley & Sons, 408Google Scholar
  22. Parise M (2001). Landslide mapping techniques and their use in the assessment of the landslide hazard. Phys Chem Earth (C), 26(9): 697–703Google Scholar
  23. Roth R A (1983). Factors affecting landslide susceptibility in San Mateo County, California. Bull Assoc Eng Geol, 4: 353–372Google Scholar
  24. Saaty T L (1980). The Analytical Hierarchy Process. New York: McGraw Hill, 350Google Scholar
  25. Saaty T, Vargas L G (2001). Models, Methods, Concepts, and Applications of the Analytic Hierarchy Process. Boston: Kluwer Academic, 333Google Scholar
  26. Saaty T L (1990). The Analytic Hierarchy Process. 2nd ed. Pittsburg: RWS Publications, 286Google Scholar
  27. Saaty T L (1994). How to make a decision: The analytic hierarchy process. Interfaces, 24(6): 19–43CrossRefGoogle Scholar
  28. Saha A K, Gupta R P, Arora M K (2002). GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens, 23(2): 357–369CrossRefGoogle Scholar
  29. Temesgen B, Mohammed M U, Korme T (2001). Natural hazard assessment using GIS and remote sensing methods, with particular references to the landslides in the Wondogenet area, Ethiopia. Phys Chem Earth (C), 26: 665–675Google Scholar
  30. Tsaparas I, Rahardjo H, Toll D G, Leong E C (2002). Controlling parameters for rainfall-induced landslides. Comput Geotech, 29(1): 1–27CrossRefGoogle Scholar
  31. Yagi H (2003). Development of assessment method for landslide hazardness by AHP. In: Abstract Volume of the 42nd Annual Meeting of the Japan Landslide Society, 209–212Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mohammad Reza Mansouri Daneshvar
    • 1
  • Ali Bagherzadeh
    • 2
  1. 1.Department of Geography, Emamyeh BoulevardIslamic Azad University-Mashhad BranchMashhadIran
  2. 2.Department of Agriculture, Emamyeh BoulevardIslamic Azad University-Mashhad BranchMashhadIran

Personalised recommendations