Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria

  • Yacine Achour
  • Abderrahmane Boumezbeur
  • Riheb Hadji
  • Abdelmadjid Chouabbi
  • Victor Cavaleiro
  • El Amine Bendaoud
Original Paper


This research work deals with the landslide susceptibility assessment using Analytic hierarchy process (AHP) and information value (IV) methods along a highway road section in Constantine region, NE Algeria. The landslide inventory map which has a total of 29 single landslide locations was created based on historical information, aerial photo interpretation, remote sensing images, and extensive field surveys. The different landslide influencing geoenvironmental factors considered for this study are lithology, slope gradient, slope aspect, distance from faults, land use, distance from streams, and geotechnical parameters. A thematic layer map is generated for every geoenvironmental factor using Geographic Information System (GIS); the lithological units and the distance from faults maps were extracted from the geological database of the region. The slope gradient, slope aspect, and distance from streams were calculated from the Digital Elevation Model (DEM). Contemporary land use map was derived from satellite images and field study. Concerning the geotechnical parameters maps, they were determined making use of the geotechnical data from laboratory tests. The analysis of the relationships between the landslide-related factors and the landslide events was then carried out in GIS environment. The AUC plot showed that the susceptibility maps had a success rate of 77 and 66% for IV and AHP models, respectively. For that purpose, the IV model is better in predicting the occurrence of landslides than AHP one. Therefore, the information value method could be used as a landslide susceptibility mapping zonation method along other sections of the A1 highway.


Information value (IV) Landslide susceptibility index (LSI) Analytic hierarchy process (AHP) Remote sensing Algeria 



The authors would like to acknowledge the anonymous reviewers for their constructive suggestions. The authors are thankful to the National Highways Agency (ANA) of Algeria for providing data, and to the centre GeoBioTec|UA (UID/GEO/04035/2013), Portugal. They also want to express their gratitude to everyone who provided assistance in realizing this study.


  1. Akgun A, Türk N (2010) Landslide susceptibility mapping for Ayvalik (Western Turkey) and its vicinity by multicriteria decision analysis. Environ Earth Sci 61(3):595–611CrossRefGoogle Scholar
  2. Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58(1):21–44CrossRefGoogle Scholar
  3. 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):15–31CrossRefGoogle 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(4):432–445CrossRefGoogle Scholar
  5. Bourenane H, Bouhadad Y, Guettouche MS, Braham M (2015) GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (Northeast Algeria). Bull Eng Geol Environ 74(2):337–355CrossRefGoogle Scholar
  6. Chen W, Chai H, Zhao Z, Wang Q, Hong H (2016) Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China. Environ Earth Sci 75(6):1–13Google Scholar
  7. Choi J, Oh HJ, Lee HJ, Lee C, Lee S (2012) Combining landslide susceptibility maps obtained from frequency ratio, logistic regression, and artificial neural network models using ASTER images and GIS. Eng Geol 124:12–23CrossRefGoogle Scholar
  8. Cruden DM, Varnes DJ (1996) Landslide types and processes, special report, transportation research board, national academy of sciences 247:36–75Google Scholar
  9. Dai FC, Lee CF (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42(3):213–228CrossRefGoogle Scholar
  10. Dai FC, Lee CF, Li J, Xu ZW (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40(3):381–391CrossRefGoogle Scholar
  11. Das I, Sahoo S, van Westen C, Stein A, Hack R (2010) Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India). Geomorphology 114(4):627–637CrossRefGoogle Scholar
  12. Das I, Stein A, Kerle N, Dadhwal VK (2012) Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models. Geomorphology 179:116–125CrossRefGoogle Scholar
  13. 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
  14. Galli M, Ardizzone F, Cardinali M, Guzzetti F, Reichenbach P (2008) Comparing landslide inventory maps. Geomorphology 94(3):268–289CrossRefGoogle Scholar
  15. Guiraud R (1973) Évolution post-triasique de l’avant-pays de la chaîne alpine en Algérie, d’après l’étude du bassin de Hodna et des régions voisines. Thèse de Science, Université Nice, 270 pGoogle Scholar
  16. 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):181–216CrossRefGoogle Scholar
  17. Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72(1):272–299CrossRefGoogle Scholar
  18. Hadji R, Errahmane Boumazbeur A, Limani Y, Baghem M, el Madjid Chouabi A, Demdoum A (2013) Geologic, topographic and climatic controls in landslide hazard assessment using GIS modeling: a case study of Souk Ahras region, NE Algeria. Quat Int 302:224–237CrossRefGoogle Scholar
  19. Hadji R, Rais K, Gadri L, Chouabi A, Hamed Y (2017) Slope failure characteristics and slope movement susceptibility assessment using GIS in a medium scale: a case study from Ouled Driss and Machroha municipalities, Northeast Algeria. Arab J Sci Eng 42(1):281–300Google Scholar
  20. Kayastha P, Dhital MR, De Smedt F (2013) Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: a case study from the Tinau watershed, west Nepal. Comput Geosci 52:398–408CrossRefGoogle Scholar
  21. 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
  22. Lee S, Evangelista DG (2006) Earthquake-induced landslide-susceptibility mapping using an artificial neural network. Nat Hazards Earth Syst Sci 6(5):687–695CrossRefGoogle Scholar
  23. Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40(9):1095–1113CrossRefGoogle Scholar
  24. Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4(1):33–41CrossRefGoogle Scholar
  25. 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(3):289–302CrossRefGoogle Scholar
  26. Lee S, Ryu JH, Kim IS (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):327–338CrossRefGoogle Scholar
  27. Lee S, Hwang J, Park I (2013) Application of data-driven evidential belief functions to landslide susceptibility mapping in Jinbu, Korea. Catena 100:15–30CrossRefGoogle Scholar
  28. Leir M, Michell A, Ramsay S (2004) Regional landslide hazard susceptibility mapping for pipelines in British Columbia. Geo-engineering for the society and its environment. In: 57th Canadian geotechnical conference and the 5th joint CGS-IAH conference, pp. 1–9Google Scholar
  29. Malczewski J (1999) GIS and multicriteria decision analysis. Wiley, New YorkGoogle Scholar
  30. Meinhardt M, Fink M, Tünschel H (2015) Landslide susceptibility analysis in central Vietnam based on an incomplete landslide inventory: comparison of a new method to calculate weighting factors by means of bivariate statistics. Geomorphology 234:80–97CrossRefGoogle Scholar
  31. Melchiorre C, Matteucci M, Azzoni A, Zanchi A (2008) Artificial neural networks and cluster analysis in landslide susceptibility zonation. Geomorphology 94(3):379–400CrossRefGoogle Scholar
  32. Melo R, Vieira G, Caselli A, Ramos M (2012) Susceptibility modelling of hummocky terrain distribution using the information value method (Deception Island, Antarctic Peninsula). Geomorphology 155:88–95CrossRefGoogle Scholar
  33. Neuhäuser B, Terhorst B (2007) Landslide susceptibility assessment using “weights-of-evidence” applied to a study area at the Jurassic escarpment (SW-Germany). Geomorphology 86(1):12–24CrossRefGoogle Scholar
  34. Poudyal CP, Chang C, Oh HJ, Lee S (2010) Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya. Environ Earth Sci 61(5):1049–1064CrossRefGoogle Scholar
  35. Pourghasemi HR, Pradhan B, Gokceoglu C (2012) Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Nat Hazards 63(2):965–996CrossRefGoogle Scholar
  36. Pradhan B, Lee S (2010) Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models. Environ Earth Sci 60(5):1037–1054CrossRefGoogle Scholar
  37. Raoult A (1974) Géologie du centre de la chaîne Numidique (Nord du Constantinois, Algérie). Mem Soc Géol France 53:121–163PGoogle Scholar
  38. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281CrossRefGoogle Scholar
  39. Saaty TL (1980) The analytic hierarchy process: planning, priority setting and resource allocation. McGraw-Hill, New YorkGoogle Scholar
  40. Saaty TL (2003) Decision-making with the AHP: Why is the principal eigenvector necessary. Eur J Oper Res 145(1):85–91Google Scholar
  41. Saaty TL, Vargas LG (2012) Models, methods, concepts & applications of the analytic hierarchy process (vol. 175). Springer Science & Business Media, HeidelbergCrossRefGoogle Scholar
  42. Saha AK, Gupta RP, Arora MK (2002) GIS-based landslide hazard zonation in the Bhagirathi (Ganga) valley, Himalayas. Int J Remote Sens 23(2):357–369CrossRefGoogle Scholar
  43. Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E (2005) An approach for GIS-based statistical landslide susceptibility zonation—with a case study in the Himalayas. Landslides 2(1):61–69CrossRefGoogle Scholar
  44. Süzen ML, Doyuran V (2004) Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey. Eng Geol 71(3):303–321CrossRefGoogle Scholar
  45. Van Westen CJ (1993) Application of geographic information systems to landslide hazard zonation. ITC Publication, vol. 15. International Institute for Aerospace and Earth Resources Survey, Enschede 245 ppGoogle Scholar
  46. Van Westen CJ, Rengers N, Terlien MTJ, Soeters R (1997) Prediction of the occurrence of slope instability phenomenal through GIS-based hazard zonation. Geol Rundsch 86(2):404–414CrossRefGoogle Scholar
  47. Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419CrossRefGoogle Scholar
  48. Varnes DJ (1984) Landslide hazard zonation: A review of principles and practice. Natural hazard, 3. United nations educational, scientific and cultural organization 63 pGoogle Scholar
  49. Vila JM (1980) La chaîne alpine d’Algérie orientale et des confins algérotunisiens. Thèse Doctorat, Université Paris, Travaux du département de géotectonique, Laboratoire de géologie structurale, Paris 665 pGoogle Scholar
  50. Wu CH, Chen SC (2009) Determining landslide susceptibility in Central Taiwan from rainfall and six site factors using the analytical hierarchy process method. Geomorphology 112(3):190–204CrossRefGoogle Scholar
  51. Yalcin A, Reis S, Aydinoglu AC, Yomralioglu T (2011) A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena 85(3):274–287CrossRefGoogle Scholar
  52. Yin KL, Yan TZ (1988) Statistical prediction model for slope instability of metamorphosed rocks. In: Bonnard C (ed) Proc., Fifth International Symposium in Landslides, Lausanne, vol. 2. A.A. Balkema, Rotterdam, pp 1269–1272Google Scholar
  53. 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(1/2):73–82CrossRefGoogle Scholar
  54. Zhou G, Esaki T, Mitani Y, Xie M, Mori J (2003) Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach. Eng Geol 68(3):373–386CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2017

Authors and Affiliations

  • Yacine Achour
    • 1
    • 4
  • Abderrahmane Boumezbeur
    • 2
  • Riheb Hadji
    • 3
  • Abdelmadjid Chouabbi
    • 4
  • Victor Cavaleiro
    • 5
  • El Amine Bendaoud
    • 6
  1. 1.Department of Civil EngineeringBordj Bou Arreridj UniversityEl AnnasserAlgeria
  2. 2.Department of Earth SciencesTebessa UniversityTebessaAlgeria
  3. 3.Department of Earth Sciences, Institute of Architecture and Earth SciencesSetif UniversitySétifAlgeria
  4. 4.Laboratory of Geodynamics and Natural ResourcesBadji Mokhtar UniversitySidi AmarAlgeria
  5. 5.Department of Civil EngineeringBeira Interior UniversityCovilhãPortugal
  6. 6.Department of Civil EngineeringSetif UniversitySétifAlgeria

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