Environmental Earth Sciences

, 77:805 | Cite as

Landslide susceptibility assessment of South Pars Special Zone, southwest Iran

  • Mohammad Azarafza
  • Akbar Ghazifard
  • Haluk Akgün
  • Ebrahim Asghari-Kaljahi
Original Article


This study assesses the landslide susceptibility of the South Pars Special Zone (SPSZ) region that is located in southwest Iran. For this purpose, a combinatorial method containing multi-criteria decision-making, likelihood ratio and fuzzy logic was applied in two levels (regional and local) at three critical zones (northwest, middle and southeast of the project area). The analysis parameters were categorised in seven main triggering factors such as climatology, geomorphology, geology, geo-structure, seismic activity, landslide prone areas and man-made activities which have different classes with multi-agent partnership correlations. Landslide susceptibility maps were prepared for these levels and zones after purified and enriched fuzzy trending runs were performed. According to the results of the risk-ability assessment of the landslide occurrences for SPSZ, the north part of the study area which includes the south edge of the Assalouyeh anticline and the southern part of the Kangan anticline were estimated as high-risk potential areas that were used in landslide hazard mitigation assessment and in land-use planning.


Landslide Geo-hazard Susceptibility analysis Risk-ability indices Weighted fuzzy evidence South Pars Special Zone 



The authors wish to thank the South Pars Gas Complex management for giving permission to perform field studies.

Compliance with ethical standards

Conflict of interest

There are no conflicts of interest.


  1. Abdullah L (2013) Fuzzy multi criteria decision making and its applications: a brief review of category. Proc Soc Behav Sci 97:131–136Google Scholar
  2. Abrahamson NN, Silva WJ (2008) NGA ground motion relations for the geometric mean horizontal component of peak and spectral ground motion parameters. PEER Report Draft v2. Pacific Earthquake Engineering Research Center, Berkeley, p 380Google Scholar
  3. Aghanabati A (2004) Geology of Iran. Geological Survey of Iran press, Tehran, p 708Google Scholar
  4. Akgun A (2012) A comparison of landslide susceptibility maps produced by logistic regression, multi-criteria decision, and likelihood ratio methods: a case study at İzmir, Turkey. Landslides 9:93–106Google Scholar
  5. Akgun A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environ Geol 5(8):1377–1387Google Scholar
  6. Akgun A, Dag S, Bulut F (2008) Landslide susceptibility mapping for a landslide-prone area (Findikli, NE of Turkey) by likelihood frequency ratio and weighted linear combination models. Environ Geol 54(6):1127–1143Google Scholar
  7. Akgun A, Sezer EA, Nefeslioglu HA, Gokceoglu C, Pradhan B (2011) An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Comput Geosci. Google Scholar
  8. Ambraseys NN, Melville CP (1982) A history of Persian earthquakes. Cambridge earth science series. Cambridge Press, Cambridge, p 212Google Scholar
  9. Atkinson PM, Massari R (2011) Autologistic modelling of susceptibility to landsliding in the Central Apennines, Italy. Geomorphology 130:55–64Google Scholar
  10. 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 1:73–81Google Scholar
  11. Azarafza M, Yarahmadi-Bafghi AR, Asghari-Kaljahi E, Bahmannia GR, Moshrefy-Far MR (2013) Stability analysis of jointed rock slopes using the key block method (Case study: Gas Flare Site in 6, 7 and 8 phases of South Pars Gas Complex). J Geotech Geol 9(3):169–185 (in Persian) Google Scholar
  12. Azarafza M, Asghari-Kaljahi E, Moshrefy-Far MR (2014a) Determination of geomechanical parameters of rock mass structure of the gas flare site in 6, 7 and 8 phases of South Pars Gas Complex. In: 32nd national & 1st international geosciences congress, Sari, Iran (in Persian) Google Scholar
  13. Azarafza M, Asghari-Kaljahi E, Moshrefy-Far MR (2014b) Numerical modeling and stability analysis of shallow foundations located near slopes (case study: phase 8 gas flare foundations of South Pars gas complex). J Geotech Geol 10(2):92–99 (in Persian) Google Scholar
  14. Azarafza M, Nikoobakht S, Moshrefy-Far MR (2014c) Study of seismicity for Shahrekord quadrangle with emphasis on the seismic activation cause on an active fault in the studied area. J Tecton Struct 2(4):49–67 (in Persian) Google Scholar
  15. Azarafza M, Asghari-Kaljahi E, Akgün H (2017a) Assessment of discontinuous rock slope stability with block theory and numerical modeling: a case study for the South Pars Gas Complex, Assalouyeh, Iran. Environ Earth Sci 76(11):397Google Scholar
  16. Azarafza M, Asghari-Kaljahi E, Akgün H (2017b) Numerical modeling of discontinuous rock slope utilizing the 3DDGM (Three Dimensional Discontinuity Geometrical Modeling) method. Bull Eng Geol Environ 76(3):989–1007Google Scholar
  17. Berberian M (1995) Natural hazards and the first earthquake catalogue of Iran. Historical hazards in Iran prior to 1900, vol. 1. A UNESCO/IIEES Publication during UN/IDNDR, International Institute of Earthquake Engineering and Seismology, Tehran, p 603Google Scholar
  18. Boore DM, Atkinson GM (2008) Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and 10.0 s. Earthq Spectra 24(1):99–138Google Scholar
  19. Campbell KW, Bozorgnia Y (2012) 2012 update of the Campbell-Bozorgnia NGA ground motion prediction equations: a progress report. In: 15th WCEE, LisboaGoogle Scholar
  20. Cascini L (2008) Applicability of landslide susceptibility and hazard zoning at different scales. Eng Geol 102(3):164–177Google Scholar
  21. Castellanos Abella EA, Van Westen CJ (2007) Qualitative landslide susceptibility assessment by multicriteria analysis: a case study from San Antonio del Sur, Guantanamo, Cuba. Geomorphology 94(3–4):453–466Google Scholar
  22. Chalkias C, Ferentinou M, Polykretis C (2014) GIS supported landslide susceptibility modeling at regional scale: an expert-based fuzzy weighting method. ISPRS Int J Geo Inf 3:523–539Google Scholar
  23. Chiou BS, Youngs RR (2008) An NGA model for the average horizontal component of peak ground motion and response spectra. Earthq Spectra 24(1):173–215Google Scholar
  24. Chung CJF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30:451–472Google Scholar
  25. Dadios EP (2012) Fuzzy logic—algorithms, techniques and implementations. InTech press, London, p 294Google Scholar
  26. Dahal RK, Hasegawa S, Nonomura S, Yamanaka M, Masuda T, Nishino K (2008) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping. Environ Geol 54:311–324Google Scholar
  27. Duman TY, Can T, Gokceoglu C, Nefeslioglu HA, Sonmez H (2006) Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey. Environ Geol 51:241–256Google Scholar
  28. Einstein HH (2003) Uncertainty in rock mechanics and rock engineering-then and now. In: 10th ISRM congress, Sandton, South AfricaGoogle Scholar
  29. Eker AM, Dikmen M, Cambazoğlu S, Düzgün HSB, Akgün H (2012) Application of artificial neural network and logistic regression methods to landslide susceptibility mapping and comparison of the results for the Ulus District, Bartın. J Fac Eng Architect Gazi Univ 27(1):163–173Google Scholar
  30. Eker AM, Dikmen M, Cambazoğlu S, Düzgün HSB, Akgün H (2015) Evaluation and comparison of landslide susceptibility mapping methods: a case study for the Ulus District, Bartın, Northern Turkey. Int J Geogr Inf Sci 29(1):132–158Google Scholar
  31. Ercanoğlu M, Gökçeoğlu C (2004) Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng Geol 75(3):229–250Google Scholar
  32. ESRI (2017) ArcGIS software version 10.4, international supplier of geographic information system software, web GIS and geodatabase management applications. Accessed 1 May 2017
  33. Geological Survey of Iran (2009) Geological map of Kangan and Assalouyeh-scale: 1:250.000. Geological Survey of Iran Press, Tehran (in Persian) Google Scholar
  34. Harrison JF, Chang C, Liu C (2017) Identification of inventory-based susceptibility models for assessing landslide probability: a case study of the Gaoping River Basin, Taiwan. Geomatics Nat Hazards Risk 8(2):1730–1751. Google Scholar
  35. Highland LM, Bobrowsky P (2008) The landslide handbook—a guide to understanding landslides: Reston, Virginia, U.S. Geological Survey Circular 1325, p 129Google Scholar
  36. Idriss IM (2008) An NGA empirical model for estimating the horizontal spectra values generated by shallow crustal earthquakes. Earthq Spectra 24(1):217–242Google Scholar
  37. International Institute of Earthquake Engineering and Seismology, IIEES (2017) Earthquake data from Assalouyeh Station for 100 Km radial. International Institute of Earthquake Engineering and Seismology. Accessed 5 Oct 2017
  38. Iran Meteorological Organization, IMO (2017) Climatological data from Assalouyeh station. The Iran Meteorological Organization. Accessed 5 Oct 2017
  39. Jing C, Yiliang L, Qingjie Z (2015) GIS-based geostatistics and multi-criteria evaluation of steel casing failure. In: 3rd international conference on material, mechanical and manufacturing engineering (IC3ME), pp 1506–1511Google Scholar
  40. Komac M (2006) A landslide susceptibility model using the analytical hierarchy process method and multivariate statistics in perialpine Slovenia. Geomorphology 74(1):17–28Google Scholar
  41. Lee WHK, Meyers H, Shimazaki K (1988) Historical seismograms and earthquakes of the world. Academic, San Diego, p 527Google Scholar
  42. Lee S, Ryu JH, Kim LS (2007) Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin. Korea Landslides 4(4):327–338Google Scholar
  43. Malamud BD, Turcotte DL, Guzzetti F, Reichenbach P (2004) Landslides, earthquakes, and erosion. Earth Planet Sci Lett 229(1–2):45–59Google Scholar
  44. Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New York, p 408Google Scholar
  45. Mamdani EH (1977) Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Trans Comput 26(12):1182–1191Google Scholar
  46. Mamdani EH, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7:1–13Google Scholar
  47. MathWorks (2014) MATLAB, version R2014b. The MathWorks Inc., NatickGoogle Scholar
  48. Melchiorre C, Matteucci M, Azzoni A, Zanchi A (2008) Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology 94:379–400Google Scholar
  49. Nefeslioglu HA, Duman TY, Durmaz S (2008) Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Eastern Black Sea region of Turkey). Geomorphology 94(3–4):401–418Google Scholar
  50. Nefeslioglu HA, Sezer E, Gokceoglu C, Bozkır AS, Duman TY (2010) Assessment of landslide susceptibility by decision trees in the metropolitan area of Istanbul, Turkey. Math Probl Eng 2010:901095. Google Scholar
  51. Neuhäuser B, Damm B, Terhorst B (2012) GIS-based assessment of landslide susceptibility on the base of the weights-of-evidence model. Landslides 9:511–528Google Scholar
  52. Nikoobakht S, Azarafza M (2016) Stability analysis and numerical modelling of toppling failure of discontinuous rock slope (a case study). J Geotech Geol 12(2):169–178Google Scholar
  53. Nogol-Sadat MA, Almasian A (1993) Tectonic map of Iran 1:1,000,000 treatise on the geology of Iran. Geological Survey of Iran, Tehran (in Persian) Google Scholar
  54. Okalp K, Akgün H (2016) National level landslide susceptibility assessment of Turkey utilizing public domain dataset. Environ Earth Sci 75(9):847Google Scholar
  55. Othman AN, Wan Mohd Naim WM, Noraini S (2012) GIS based multi-criteria decision making for landslide hazard zonation. Proc Soc Behav Sci 35:595–602Google Scholar
  56. Papathanassiou G, Valkaniotis S, Ganas A, Pavlides S (2013) GIS-based statistical analysis of the spatial distribution of earthquake-induced landslides in the island of Lefkada, Ionian Islands. Greece Landslides 10:771–783Google Scholar
  57. Pereira S, Garcia RAC, Zêzere J, Oliveira S, Silva M (2016) Landslide quantitative risk analysis of buildings at the municipal scale based on a rainfall triggering scenario. Geomat Nat Hazards Risk 8(2):624–648. Google Scholar
  58. Porkermani M, Arian M (1988) Seismicity of Iran. Shahid Beheshti University Press, Tehran, p 279Google Scholar
  59. Rossi M, Guzzetti F, Reichenbach P, Mondini AC, Peruccacci S (2010) Optimal landslide susceptibility zonation based on multiple forecasts. Geomorphology 114(3):129–142Google Scholar
  60. Ruff M, Czurda K (2008) Landslide susceptibility analysis with a heuristic approach in the Eastern Alps (Vorarlberg, Austria). Geomorphology 94:314–324Google Scholar
  61. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281Google Scholar
  62. Saaty TL (1980) The analytic hierarchy process: planning, priority setting, resource allocation (decision making series). McGraw-Hill, New York, p 287Google Scholar
  63. Saaty TL (2000) Fundamentals of decision making and priority theory, 1st edn. RWS Publications, Pittsburgh, p 477Google Scholar
  64. Saaty TL, Peniwati K (2007) Group decision making: drawing out and reconciling differences. RWS Publications, Pittsburgh, p 385Google Scholar
  65. Saaty T, Vargas LLG (2012) Models, methods, concepts & applications of the analytic hierarchy process (international series in operations research & management science), 2nd edn. p 346Google Scholar
  66. Shearer PM (2009) Introduction to seismology, 2nd edn. Cambridge University Press, Cambridge, p 412Google Scholar
  67. Sivanandam SN, Sumathi S, Deepa SN (2007) Introduction to fuzzy logic using MATLAB. Springer, Berlin, p 430Google Scholar
  68. Soeters R, Van Westen CJ (1996) Slope instability recognition, analysis and zonation (Chap. 8). In: Turner AK, Schuster RL (eds) Landslides: investigations and mitigation, National Academy Press. Transportation Research Board Special Report, vol 247. National Research Council, WashingtonGoogle Scholar
  69. Terlien MT, Van Westen CJ, Van Asch TW (1995) Deterministic modelling in GIS-based landslide hazard assessment. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer Academic Publishers, Dordrecht, pp 57–77Google Scholar
  70. Vahidnia MH, Alesheikh AA, Alimohammadi A, Hosseinali F (2010) A GIS-based neurofuzzy procedure for integrating knowledge and data in landslide susceptibility mapping. Comput Geosci 36(9):101–1114Google Scholar
  71. Varnes DJ (1978) Slope movement types and processes. Landslide analysis and control. Transportation Research Board, National Academy Sciences, WashingtonGoogle Scholar
  72. Voogd H (1983) Multicriteria evaluation for urban and regional planning. Pion Ltd, London, p 370Google Scholar
  73. Wyllie DC, Mah CW (2004) Rock slope engineering: civil and mining, 4th edn. Spon Press, Taylor & Francis Group, New York, p 456Google Scholar
  74. Yager RR, Zadeh LA (1992) An Introduction to fuzzy logic applications in intelligent systems. Springer Science + Business Media, New York, p 357Google Scholar
  75. Yilmaz I (2009) Landslide susceptibility using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). Comput Geosci 35(6):1125–1138Google Scholar
  76. Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353Google Scholar
  77. Zêzere JL (2002) Landslide susceptibility assessment considering landslide typology, a case study in the area north of Lisbon (Portugal). Nat Hazards Earth Syst Sci 2:73–82Google Scholar
  78. Zêzere JL, Pereira S, Melo R, Oliveira SC, Garcia RAC (2017) Mapping landslide susceptibility using data-driven methods. Sci Total Environ 589:250–267Google Scholar
  79. Zůvala R, Fišerová E, Marek L (2016) Mathematical aspects of the kriging applied on landslide in Halenkovice (Czech Republic). Open Geosci 8:275–288Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of GeologyUniversity of IsfahanIsfahanIran
  2. 2.Geotechnology Unit, Department of Geological EngineeringMiddle East Technical UniversityAnkaraTurkey
  3. 3.Department of Earth SciencesUniversity of TabrizTabrizIran

Personalised recommendations