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Natural Hazards

, Volume 41, Issue 1, pp 61–79 | Cite as

Evaluation and validation of landslide-susceptibility maps obtained by a GIS matrix method: examples from the Betic Cordillera (southern Spain)

  • C. Irigaray
  • T. Fernández
  • R. El Hamdouni
  • J. Chacón
Original Paper

Abstract

This work presents the results of applying the matrix method in a Geographic Information System (GIS) to the drawing of maps of susceptibility to slope movements in different sectors of the Betic Cordillera (southern Spain). In addition, the susceptibility models built by the matrix method were compared with a multivariate statistical method, and the first method gave the best results. The susceptibility maps drawn by the GIS matrix method were validated by calculating the coefficients of association with the degree of fit between recent slope movements registered in 1997 and the different levels of susceptibility of previously drawn maps (1995–1996) in different representative zones of the Betic Cordillera (southern Spain). The first sector studied showed excellent degrees of fit, with an error of less than 10% for all the slope failures and 3% when considering only failures of natural origin. In the second sector, the relative errors were less than 5%. In the third sector, the error hardly exceeded 6%. The results are discussed in the different zones and for each type of slope movement. In any case, these results evidence the predictive capacity of susceptibility maps drawn in GIS by the matrix method, for a great number of slope movements.

Keywords

GIS matrix method Susceptibility evaluation Landslide Validation Betic Cordillera Southern Spain 

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Notes

Acknowledgements

This research was financed by the project CICYT REN2002-03366 and by the Group RNM 121 of the Andalusian Plan of Research (Plan Andaluz de Investigación, Junta de Andalucía).

References

  1. Avidad JY, García-Dueñas V, Gallegos J, González-Donoso JM (1981) Mapa Geológico de España a escala 1:50.000, Durcal (1041). Mapa y memoria explicativa, IGME, MadridGoogle 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. Brabb EE, Pampeyan EH, Bonilla MG (1972) Landslide susceptibility in San Mateo County, California. U.S. Geol. Survey Misc.Field Studies, Map MF-360, scale 1:62,500Google Scholar
  4. Cano F (1990) Mapa Geológico de España a escala 1:50.000, Rute (1007). Mapa y memoria explicativa, IGME, MadridGoogle Scholar
  5. Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS technology in mapping landslide hazard. In: Carrara A, Guzzetti F (eds) Geographical information system in assessing natural hazards. Kluwer Academic Publisher, The Netherlands, pp 135–175Google Scholar
  6. Chacón J (2005) Mapas de zonas inestables i Sistemas de Información Geográfica (SIG). In: Corominas J, Alonso E, Romana M, Hürlimann (eds) VI Simposio Nacional sobre Taludes y Laderas Inestables, vol III, Artes Gráficas Torres SA, Barcelona, pp 1196–1271Google Scholar
  7. Chacón J, Corominas J (2003) (eds) Special issue on Landslides and GIS. Natural Hazards, 30:3, 263–512. Kluwer Academic Publishers, The NetherlandsGoogle Scholar
  8. Chacón J, Irigaray C, El Hamdouni R, Fernández T (1996) From the inventory to the risk analysis: improvements to a large scale G.I.S. method. In: Chacón J, Irigaray C, Fernández T (eds) Landslides. Balkema, Rotterdam, pp 335–342Google Scholar
  9. Chacón J, Irigaray C, Fernández T (1993) Methodology for large scale landslide hazard mapping in a G.I.S. In: Novosad S, Wagner P (eds) Landslides, Seventh International Conference & Field Workshop. Balkema, Rotterdam, pp 77–82Google Scholar
  10. Chacón J, Irigaray C, Fernández T (1994) Large to middle scale landslides inventory, analysis and mapping with modelling and assessment of derived susceptibility, hazards and risks in a GIS, In: Oliveira R, Rodrigues LF, Coelho AG, Cunha AP (eds) Proceedings Seventh International Congress International Association of Engineering Geology, vol VI, Balkema, Rotterdam, pp 4669–4678Google Scholar
  11. Chacón J., Irigaray C, Fernández T, El Hamdouni R (2003) Susceptibilidad a los movimientos de ladera en el sector central de la Cordillera Bética. In: Ayala-Carcedo FJ, Corominas J (eds) Mapas de susceptibilidad a los movimientos de ladera con técnicas SIG. IGME, serie Medio Ambiente, N°4, Madrid Spain, pp 83–96Google Scholar
  12. Chung CF, Fabbri AG, Van Westen CJ (1995) Multivariate regression analysis for landslide hazards zonation. In: Carrara A, Guzzetti F (eds) Geographical information system in assessing natural hazards. Kluwer Academic Publishers, Dordrecht, The Netherlands, pp 107–134Google Scholar
  13. 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
  14. Cross M (1998) Landslide susceptibility mapping using the Matrix Assessment approach: a Derbyshire case study. In: Maund JG, Eddlestonb M (eds) Geohazards in engineering geology. The Geological Society, vol 15. Engineering Geology Special Publications, London, UK, pp 247–261Google Scholar
  15. Cross M (2002) Landslide susceptibility mapping using the Matrix Assessment approach: a Derbyshire case study. In: Griffiths JS (ed) Mapping in engineering geology, vol 15. The Geological Society, Key Issue in Earth Sciences, London UK, pp 247–261Google Scholar
  16. Davis JC (1986) Statistical and data analysis in geology, 2nd edn. John Wiley & Sons, Inc., New York, 646 pGoogle Scholar
  17. DeGraff JV, Romesburg HC (1980) Regional landslide-susceptibility assessment for wildland management: a matrix approach. In: Coates DR, Vitek JD (eds) Thersholds in geomorphology. Alien & Unwin, Boston, Chap 19, pp 401–414Google Scholar
  18. El Hamdouni R (2001) Estudio de movimientos de ladera en la cuenca del río ízbor mediante un SIG: contribución al conocimiento de la relación entre tectónica activa e inestabilidad de vertientes. 429 pp and 10 maps 1:25.000, Unpublished PhD Thesis. Department of Civil Engineering, University of Granada, SpainGoogle Scholar
  19. El Hamdouni R, Irigaray C, Fernández T, Sanz de Galdeano C, Chacón J (2000) Slope movements and active tectonics in the I´zbor River Basin (Granada, Spain). In: Bromhead E, Dixon N, Ibsen ML (eds) Landslide in research, theory and practice. Proceedings of the 8th ISL, Cardif, vol 1, Thomas Telford, London, pp 501–506Google Scholar
  20. Ercanoglu M, Gokceoglu C (2004) Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng Geol 75:229–250CrossRefGoogle Scholar
  21. Fernández T (2001) Cartografía, análisis y modelado de la susceptibilidad a los movimientos de ladera en macizos rocosos mediante SIG: aplicación a diversos sectores del Sur de la provincia de Granada. 648 p. 9 maps, Unpublished PhD Thesis, Department of Civil Engineering, University of Granada, SpainGoogle Scholar
  22. Fernández T, Irigaray C, Chacón J (1996) Inventory and analysis of landslides determinant factors in Los Guajares Mountains, Granada (Southern Spain). In: Senneset K (ed) Landslides. Proceedings of the International Symposium on Landslides, vol 3. Balkema, Rotterdam, pp 1891–1896Google Scholar
  23. Fernández T, Irigaray C, El Hamdouni R, Chacón J (2003) Methodology for landslide susceptibility mapping by means of a GIS. Application to the contraviesa area (Granada, Spain), Nat Hazards 30(3):297–308CrossRefGoogle Scholar
  24. Good IJ (1965) Categorization of classification. In: Mathematics and computer science in biology and medicine, HMSO (ed) London, pp 115–125Google Scholar
  25. Goodman LA (1954) Kolmogorov–Smirnov test for psychological research. Psychol Bull 51:31–45CrossRefGoogle Scholar
  26. Goodman LA, Kruskal WH (1954) Measures of association for cross classifications. J Am Statist Assoc 49:732–764CrossRefGoogle Scholar
  27. 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 31:181–216CrossRefGoogle Scholar
  28. Irigaray C (1995) Movimientos de ladera: inventario, análisis y cartografía de susceptibilidad mediante un Sistema de Información Geográfica. Aplicación a las zonas de Colmenar (Ma), Rute (Co) y Montefrío (Gr), Unpublished PhD Thesis, Department of Civil Engineering, University of Granada, SpainGoogle Scholar
  29. Irigaray C, Fernández T, Chacón J (2003) Preliminary rock-slope-susceptibility assessment using GIS and the SMR classification. Nat Hazards 30(3):309–324CrossRefGoogle Scholar
  30. Irigaray C, Fernández T, El Hamdouni R, Chacón J (1999) Verification of landslide susceptibility mapping. A case study. Earth Surf Proc Land 24:537–544CrossRefGoogle Scholar
  31. Irigaray C, Lamas F, El Hamdouni R, Fernández T, Chacón J (2000) The importance of the precipitation and the susceptibility of the slopes for the triggering of landslides along the roads. Nat Hazards 21:65–81CrossRefGoogle Scholar
  32. Lee S, Ryu JH (2004) Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression and artificial neural network methods: case study of Yongin, Korea. In: Lacerda WA, Ehrlich M, Fontoura SAB, Sayao ASF (eds) Landslides: evaluation and stabilization, Taylor and Francis Group, London, pp 91–96Google Scholar
  33. Lee S, Ryu JH, Lee M-J, Won JS (2003) Use of an artificial neural network for analysis of the susceptibility to landslides at Boun, Korea. Environ Geol 44(7):820–833CrossRefGoogle Scholar
  34. Maharaj RJ (1993) Landslide processes and landslide susceptibility analysis from an upland watershed – a case study from St. Andrew, Jamaica, West Indies. Eng Geol 34(1–2):53–79CrossRefGoogle Scholar
  35. Nilsen TH, Wright RH, Vlasic TC, Spangle WE (1979) Relative slope stability and land-use planning in the San Francisco Bay Region, California. US Geol. Surv. Prof. Paper, 944, 104 pGoogle Scholar
  36. Remondo J, González A, Díaz de Terán JR, Cendrero A, Fabbri A, Cheng CF (2003) Validation of landslide susceptibility maps: examples and applications from a case study in Northern Spain. Nat Hazards 30(3):437–449CrossRefGoogle Scholar
  37. 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(3–4):303–321CrossRefGoogle Scholar
  38. Van Westen CJ, Rengers N, Terlien MTJ, Soeters R (1997) Prediction of the occurrence of slope instability phenomena through GIS-based hazard zonation. Geologische Rundschau 86(2):404–414CrossRefGoogle Scholar
  39. Varnes DJ (1978) Slope movement types and processes. In: Schuster RL, Krizek RJ (eds) Landslides: analysis and control. National Academy of Sciences, Transportation Research Board. Washington, DC. Special Report 176, 2, 11–33Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2006

Authors and Affiliations

  • C. Irigaray
    • 1
  • T. Fernández
    • 2
  • R. El Hamdouni
    • 1
  • J. Chacón
    • 1
  1. 1.Departamento de Ingeniería Civil, Escuela Técnica Superior de Ingeniería de Caminos, Canales y PuertosUniversidad de GranadaGranadaSpain
  2. 2.Departamento de Ingeniería Cartográfica, Geodésica y Fotogrametría, Escuela Politécnica Superior de JaénUniversidad de JaénJaenSpain

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