Application of linear indexing model and GIS techniques for the slope movement susceptibility modeling in Bousselam upstream basin, Northeast Algeria

  • Riheb Hadji
  • Abdelmadjid Chouabi
  • Larbi Gadri
  • Khaled Raïs
  • Younes Hamed
  • Abderahmene Boumazbeur
Original Paper


The main objective of this study was to assess spatial prediction of slopes movement susceptibility in the Bousselam upstream basin, northeast of Algeria, using a linear indexing model and Geographic Information Systems. First, the locations of 1109 slope instabilities, which occurred in the last three decades, were mapped upon data from various sources such as follows: remote sensing, aerial photographs interpretation, and internal reports compilation. This slope movement inventory was randomly segmented into training and validation datasets (75 % of the known events locations were used for training and building the model and the remaining 25 % for its validation). Second, nine natural and anthropogenic causing factors were mapped as independent variables: geological factors (lithology and faults density), morphometric factors (slope, aspect, and elevations), environmental factors (precipitations, seism, and stream network density), and the land use factor (roads and rail network density). Third, the relative value of each categorical variable involved in the slope movements emergence was assessed (categorization of evaluation criteria, standardization of factors, and weighting of variables). Then, a global index value of slopes movement susceptibility was calculated for each cell in the study area by using a linear indexing model. Finally, the slopes movement susceptibility map was categorized into five hierarchic classes and validated using the validation dataset that was not used in the model building. The area under the curve was included to assess prediction capability of the adopted model (sensitivity = 0.83 and 1 − specificity = 0.74). The resulted susceptibility map may be used for preliminary land planning purposes.


Setif Analytic-heuristic Susceptibility Natural breaks Land use planning 


  1. Abul Hasanat MH, Ramachandram D, Mandava R (2010) Bayesian belief network learning algorithms for modeling contextual relationships in natural imagery: a comparative study. Artif Intell Rev 34(4):291–308CrossRefGoogle Scholar
  2. 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 9:93–106CrossRefGoogle Scholar
  3. Akgun A, Kincal C, Pradhan B (2012) Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir City (West Turkey). Environ Monit Assess 184:5453–5470CrossRefGoogle Scholar
  4. Anbalagan R (1992) Landslide hazard assessment and zonation mapping in mountainous terrain. Eng Geol 32:269–277CrossRefGoogle Scholar
  5. 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 1:73–81CrossRefGoogle Scholar
  6. Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Process Landf 26:1251–1263CrossRefGoogle Scholar
  7. Bouhadad Y (2008) Seismic hazard assessment in Algeria: a case study of Oran region, Northwest of Algeria. The 14th World Conference on Earthquake Engineering October 12–17, 2008, Beijing, ChinaGoogle Scholar
  8. Bouhadad Y, Nour A, Laouami N, Belhai D (2003) The Beni-Ourtilane-Tachaouaft fault and seismotectonic aspects of the Babors region (NE of Algeria). J Seismol 7:79–88CrossRefGoogle Scholar
  9. Bourenane H, Bouhadad Y, Guettouche MS, Braham M (2014) GIS-based landslide susceptibility zonation using bivariate statistical and expert approaches in the city of Constantine (NE Algeria). Bull Eng Geol Environ:1–19Google Scholar
  10. Chung CJF, Fabbri AG (1999) Reasonning prediction models for landslide hazard mapping. Photogramm Eng Remote Sens 65(12):1389–1399Google Scholar
  11. Conforti M, Aucelli PP, Robustelli G, Scarciglia F (2011) Geomorphology and GIS analysis for mapping gully erosion susceptibility in the Turbolo stream catchment (Northern Calabria, Italy). Nat Hazards 56(3):881–898CrossRefGoogle Scholar
  12. Cornell CA, Van Marke EH (1969) The major influence on seismic risk. Proceedings of the third conference on earthquake engineering. Santiago, Chile. V: A-1, 69–93Google Scholar
  13. Demir G, Aytekin M, Akgun A (2014) Landslide susceptibility mapping by frequency ratio and logistic regression methods: an example from Niksar–Resadiye (Tokat, Turkey). Arab J Geosci 8:1801–1812CrossRefGoogle Scholar
  14. Djerbal L, Melbouci B (2013) Contribution to the mapping of the landslide of Aїn El Hammam (Algeria). Adv Mater Res 601:332–336CrossRefGoogle Scholar
  15. Djerbal L, Alimrina N, Melbouci B, Bahar R (2014) Mapping and management of landslide risk in the city of Azazga (Algeria). In: Sassa K et al. (eds.) Landslide Science for a Safer Geoenvironment, Vol. 2Google Scholar
  16. Domzig A (2006) Active and recent deformation and tectonosedimentaire structuring of the Algerian margin underwater. PHD Thesis Bretagne occidentale, Brest University, FranceGoogle Scholar
  17. England K (2011) A GIS approach to landslide hazard management for the West Coast region, New Zealand. A thesis of Master of Science in Hazard and Disaster Management, Canterbury University, 169pGoogle Scholar
  18. Goovaerts P (2010) Geostatistical software. Handbook of applied spatial analysis: software tools methods and applications. In: Fischer MM, Getis A (eds), Springer, Berlin, pp. 129–138Google Scholar
  19. Grozavu A, Plescan S, Patriche CV, Margarint MC, Rosca B (2013) Landslide susceptibility assessment: GIS application to a complex mountainous environment, the carpathians: integrating nature and society towards sustainability. Environ Sci Eng:31–44Google Scholar
  20. Guadri L, Hadji R, Zahri F, Raїs K (2015) The quarries edges stability in opencast mines: a case study of the Jebel Onk phosphate mine, NE Algeria. Arab J Geosci-D-14-01383. doi: 10.1007/s12517-015-1887-3
  21. Guettouche MS (2013) Modeling and risk assessment of landslides using fuzzy logic. Application on the slopes of the Algerian Tell (Algeria). Arab J Geosci 6:3163–3173CrossRefGoogle Scholar
  22. Guzzetti F (2005) Landslide hazard and risk assessment. Unpublished PhD Thesis. PP. 389. University of Bonn, 11/2005Google Scholar
  23. Hadji R (2013) Control of geological and climatic factors on landslides in the region of Souk Ahras and Guelma, Northeast Algerian. PhD thesis University of Badji Mokhtar-Annaba, 198 pGoogle Scholar
  24. Hadji R, Baghem M, Boumazbeur A, Limani Y (2012) Landslides risk mapping study and their impact on the territory of Souk Ahras Province, N-E Algeria. In: Proceedings of the Sixth International Conference Geo-Tunis, Tunis, 26–30 March 2012, pp. 116–125Google Scholar
  25. Hadji R, Boumazbeur A, Limani Y, Baghem M, Chouabi 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
  26. Hadji R, Boumazbeur A, Demdoum A, Limani Y (2014) Climate change and their influence on shrinkage-swelling clays susceptibility in a semi-arid zone: a case study of Souk Ahras Municipality, NE-Algeria. Desalin Water Treat 52:10–12CrossRefGoogle Scholar
  27. Haneberg WC, Gokce AO, (1994) Rapid water-level fluctuationsin a thin colluvium landslide west of Cincinnati. U.S. Geological Survey Bulletin 2059-C (16 p)Google Scholar
  28. Harbi A, Maouche S, Ayadi H (1999) Neotectonics and associated seismicity in the Eastern Tellian Atlas of Algeria. J Seismol 3:95–104CrossRefGoogle Scholar
  29. Harbi A, Maouche S, Benhallou H (2003) Re-appraisal of seismicity and seismotectonics in the North-Eastern Algeria Part II: 20th century seismicity and seismotectonics analysis. J Seismol 7:221–234CrossRefGoogle Scholar
  30. Jaupaj O, Lateltin O, Lamaj M (2014) Landslide susceptibility of Kavaja, Albania. In: Landslide science for a safer geoenvironment. p 351–356Google Scholar
  31. Jibson RW (1996) Use of landslides for paleoseismic analysis. Eng Geol 43(4):291–323CrossRefGoogle Scholar
  32. Kamp U, Growley B, Khattak G, Ghazanfar A, Owen L (2008) GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region. Geomorphology 101:631–642CrossRefGoogle Scholar
  33. Kundu S, Saha AK, Sharma DC, Pant CC (2013) Remote sensing and GIS based landslide susceptibility assessment using binary logistic regression model: a case study in the Ganeshganga Watershed, Himalayas. J Indian Soc Remote Sens 41(3):697–709CrossRefGoogle Scholar
  34. Lee S, Choi U (2003) Development of GIS-based geological hazard information system and its application for landslide analysis in Korea. Geosci J 7:243–252CrossRefGoogle Scholar
  35. Mair A, Fares A (2010) Assessing rainfall data homogeneity and estimating missing records in Makaha Valley, O‘ahu, Hawai. J Hydrol Eng 15(1):61–66CrossRefGoogle Scholar
  36. Malet JP, Maquaire O (2008) Risk assessment methods of landslides, RAMSOIL report 2.2. Accessible via
  37. Mastere M (2011) Mass movements susceptibility in the Chefchaouen Province (central Rif, Morocco): spatial analysis, multi-scale probabilistic modeling and impact on development and planning. PhD thesis, University of Western Brittany, 316 pGoogle Scholar
  38. Mastere M, Van Vliet LB, Mansour M, Aїt Brahim L (2011) Spatiotemporal analysis of landslides using digital photogrammetry and DEM. Remote Sens Rev 10:147–156Google Scholar
  39. Mastere M, Van Vliet Lanoë B, Aїt Brahim L, El Moulat M (2014) A linear indexing approach to mass movements susceptibility mapping: a case of the Chefchaouen Province (Morocco). Revue internationale de géomatique 05/2015; 25(2):245–265Google Scholar
  40. Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Eng Geol 69:331–343CrossRefGoogle Scholar
  41. Pallás R, Manuel J, Marta V, Ester Falgása G, Alemanya X, Muñoz AA (2004) Pragmatic approach to debris flow hazard mapping in areas affected by Hurricane Mitch: example from NW Nicaragua. Eng Geol 72:57–72CrossRefGoogle Scholar
  42. Pareek N, Sharma ML, Arora MK (2010) Impact of seismic factors on landslide susceptibility zonation: a case study in part of Indian Himalayas. Landslides 7(2):191–201CrossRefGoogle Scholar
  43. Parise M, Jibson WR (2000) A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake. Eng Geol 58:251–270CrossRefGoogle Scholar
  44. Park S, Choi C, Kim B, Kim J (2013) Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea. Environ Earth Sci 68:1443–1464CrossRefGoogle Scholar
  45. Phillips JD (2006) Evolutionary geomorphology: thresholds and nonlinearity in landform response to environmental change. Hydrol Earth Syst Sci Discuss 3(2):365–394CrossRefGoogle Scholar
  46. 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 63:965–996CrossRefGoogle Scholar
  47. Pourghasemi HR, Pradhan B, Gokceoglu C, Mohammadi M, Moradi HR (2013) Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran. Arab J Geosci 6:2351–2365CrossRefGoogle Scholar
  48. Pradhan B (2013) A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS. Comput Geosci 51:350–365CrossRefGoogle Scholar
  49. Pradhan B, Lee S (2010) Landslide susceptibility assessment and factor effect analysis: back-propagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling. Environ Model Software 25(6):747–759CrossRefGoogle Scholar
  50. Regmi AD, Devkota KC, Yoshida K, Pradhan B, Pourghasemi HR, Kumamoto T, Akgun A (2014) Application of frequency ratio, statistical index, and weights of evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya. Arab J Geosci 7(2):725–742CrossRefGoogle Scholar
  51. Sadigh K, Chang CY, Abrahamson NA, Chiou SJ, Power MS (1993) Specification of long period ground motion. Updated attenuation relationships for rock site conditions and adjustment factors for near fault effects. Proceedings of ATC-17-1 seminar on seismic isolation, passive energy dissipation, and active control. March 11–12 San Francisco, California, pp. 59–70Google Scholar
  52. Saunders W, Glassey P (2007). Guidelines for assessing planning, policy and consent requirements for landslide prone land. GNS Science Miscellaneous Series 7, Feb. 2007Google Scholar
  53. Schumm SA (1979) Geomorphic thresholds: the concept and its applications transactions of the Institute of British Geographers, NS4: 4, 485–515Google Scholar
  54. Schumm SA (1991) To interpret the earthten ways to be wrong. Cambridge University Press, New YorkGoogle Scholar
  55. Schumm SA, Dumont JF, Holbrook JM (2000) Active tectonics and alluvial rivers. Cambridge University Press, New YorkGoogle Scholar
  56. Sharma LP, Nilanchal P, Ghose MK, Debnath P (2013) Synergistic application of fuzzy logic and geo-informatics for landslide vulnerability zonation—a case study in Sikkim Himalayas. India Appl Geomat 5:271–284CrossRefGoogle Scholar
  57. Thibault S (2011) Barycentre d’un reseau fractal, lagtime et temps de concentration. HAL Id: hal-00655526
  58. Thiery Y, Malet JP, Sterlacchini S, Puissant A, Maquaire O (2007) A landslide susceptibility assessment by bivariate methods at large scales: application to a complex mountainous environment. Geomorphology 92:38–59CrossRefGoogle Scholar
  59. Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Special report 176: landslides: analysis and control. Transportation and Road Research Board, National Academy of Science, Washington D. C, pp 11–33Google Scholar
  60. Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. UNESCO, France, pp 1–63Google Scholar
  61. Vila JM (1980) La chaine alpine nord-orientale et des confins algéro-tunisiens. Thèse Doctorat, Université P. et M. Curie, Paris VIGoogle Scholar
  62. Wells DL, Coppersmith KJ (1994) Updated empirical relationships among magnitude, rupture length, rupture area, and surface displacement. Bull Seismol Soc Am 84:974–1002Google Scholar
  63. Youssef AM, Pradhan B, Tarabees E (2010) Integrated evaluation of urban development 550 suitability based on remote sensing and GIS techniques: contribution from analytic 551 hierarchy process. Arab J Geosci 4(3–4):463–473Google Scholar
  64. Zhou CH, Lee CF, Li J, Xu ZW (2002) On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong. Geomorphology 43:197–207CrossRefGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2016

Authors and Affiliations

  • Riheb Hadji
    • 1
    • 2
  • Abdelmadjid Chouabi
    • 3
  • Larbi Gadri
    • 4
  • Khaled Raïs
    • 5
  • Younes Hamed
    • 6
  • Abderahmene Boumazbeur
    • 7
    • 8
  1. 1.Department of Earth Sciences, Institute of Architecture and Earth SciencesFerhat Abbas Setif 1 UniversitySetifAlgeria
  2. 2.Laboratory of sedimentary environment, mineral and hydro resources, LESRMHAOTebessa UniversityTebessaAlgeria
  3. 3.Laboratory of Geodynamics and Natural Resources LGRNBadji Mokhtar UniversityAnnabaAlgeria
  4. 4.Mining Engineering Department and Mines LaboratoryChieckh Larbi Tebessi UniversityTebessaAlgeria
  5. 5.Electro-Mechanical DepartmentUniversity of SkikdaSkikdaAlgeria
  6. 6.Department of Earth Sciences, Faculty of SciencesGabes UniversityGabesTunisia
  7. 7.Department of Earth Sciences, Faculty of SciencesTebessa UniversityTebessaAlgeria
  8. 8.LESRMHAO LaboratoryTebessa UniversityTebessaAlgeria

Personalised recommendations