The Susceptibility of Landslide Evaluation and Zoning by Statistical Methods

Keywords: Weight of Evidence, logistic regression, hazard, mass movements, Valle de Aburrá.


Evaluating and zoning mass movement landslide is a fundamental tool for land planning. There are different methods that help to establish in a regional scale landslide hazard. The most common methods are bivariate statistics and multivariate statistic, which need a landslide historical inventory. This study takes a place in the North of the Andes in a region of Colombia called Aburrá Valley, for evaluating and zoning landslide susceptibility by two methods, one of them is bivariate statistics called Weights of Evidence which is recommended by the Geological Service of Colombia for rural area, and the second one is a multivariate statistic method, called logistic regression, which is widely used worldwide. Both methods are supported in frequency histogram, Pearson correlation, Discriminant Analysis, and Principal Component Analysis. The accuracy of the landslide susceptibility maps produced from the two models is classified in high, medium and low by ROC analysis. The AUC plot estimation results showed that the susceptibility map using Logistic regression has a training accuracy of 76.5% and a prediction capacity of 77.5%. The Weights of evidence method has the highest training accuracy of 77.8% and a prediction of 77.5%. This result allows to include the methods in territorial planning studies.

Author Biographies

Edier Aristizábal-Giraldo, Universidad Nacional de Colombia, Colombia

Ingeniero geólogo, Departamento de Geociencias y Medio Ambiente, Universidad Nacional de Colombia, Medellín-Colombia,

Mariana Vásquez*, Universidad Nacional de Colombia, Colombia

Ingeniera geóloga, Departamento de Geociencias y Medio Ambiente, Universidad Nacional de Colombia, Medellín-Colombia,

Diana Ruíz, Universidad EAFIT, Colombia

Ingeniera Geóloga, Universidad EAFIT, Medellín-Colombia,


E. E. Brabb, “Innovative approaches to landslide hazard and risk mapping” conference paper in Proceedings of IVth International Conference and Field Workshop in Landslides, vol. 1, pp. 17-22, Tokyo, 1985.

R. Soeters, R and C. J.V. Westen, Slope instability recognition, analysis and zonation, In: Turner, A.K., Schuster, R.L., Eds., Landslides: Investigation and Mitigation: TRB Sp. Washington D.C.: National Academy Press, 1996.

P. Aleotti and R. Chowdhury, “Landslide hazard assessment: summary review and new perspectives,” Bull. Eng. Geol. Environ., vol. 58, no. 1, pp. 21–44, Aug. 1999.

R. Fell, J. Corominas, C. Bonnard, L. Cascini, E. Leroi, and W. Z. Savage, “Guidelines for landslide susceptibility, hazard and risk zoning for land use planning,” Eng. Geol., vol. 102, no. 3–4, pp. 85–98, Dec. 2008.

C. J. van Westen, T. W. J. van Asch, and R. Soeters, “Landslide hazard and risk zonation—why is it still so difficult,” Bull. Eng. Geol. Environ., vol. 65, no. 2, pp. 167–184, May 2006.

F. Guzzetti, A. Carrara, M. Cardinali, and P. Reichenbach, “Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy,” Geomorphology, vol. 31, no. 1–4, pp. 181–216, Dec. 1999.

E. F. García-Aristizábal, E. V. Aristizabal Giraldo, R. J. Marín Sánchez, and J. C. Guzman Martinez, “Implementación del modelo TRIGRS con análisis de confiabilidad para la evaluación de la amenaza a movimientos en masa superficiales detonados por lluvia,” TecnoLógicas, vol. 22, no. 44, pp. 111–129, Jan. 2019.

T. W. J. van Asch, J.-P. Malet, L. P. H. van Beek, and D. Amitrano, “Techniques, issues and advances in numerical modelling of landslide hazard,” Bull. la Soc. Geol. Fr., vol. 178, no. 2, pp. 65–88, Mar. 2007.

M. Casadei, W. E. Dietrich, and N. L. Miller, “Testing a model for predicting the timing and location of shallow landslide initiation in soil-mantled landscapes,” Earth Surf. Process. Landforms, vol. 28, no. 9, pp. 925–950, Aug. 2003.

S. Zhang, L. Zhao, R. Delgado-Tellez, and H. Bao, “A physics-based probabilistic forecasting model for rainfall-induced shallow landslides at regional scale,” Nat. Hazards Earth Syst. Sci., vol. 18, no. 3, pp. 969–982, Mar. 2018.

C. Chung, “Using likelihood ratio functions for modeling the conditional probability of occurrence of future landslides for risk assessment,” Comput. Geosci., vol. 32, no. 8, pp. 1052–1068, Oct. 2006.

T. Chen, R. Niu, and X. Jia, “A comparison of information value and logistic regression models in landslide susceptibility mapping by using GIS,” Environ. Earth Sci., vol. 75, no. 10, p. 867, May 2016.

C. J. Van Westen, “Application of geographic information systems to landslide hazard zonation,” ITC, Ensched 1993.

C.-J. F. Chung and A. G. Fabbri, “The representation of geoscience information for data integration,” Nonrenewable Resour., vol. 2, no. 2, pp. 122–139, Jun. 1993.

P. V. Gorsevski, P. Gessler, and R. B. Foltz, “Spatial Prediction of Landslide Hazard Using Discriminant Analysis and GIS.,” in GIS in the Rockies 2000 Conference and Workshop Applications for the 21st Century, 2000.

L. Ayalew and H. Yamagishi, “The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan,” Geomorphology, vol. 65, no. 1–2, pp. 15–31, Feb. 2005.

Organización de Estados Americanos (OEA) “Chapter 10: Landslide hazard assessment. In: Primer on natural hazard management in integrated regional development planning. Dept. of Regional Development and Environment, Executive Secretariat for Economic and Social Affairs (DRDE), General Secretariat, Washington, DC.,” Washington, 1991.

A. Clerici, S. Perego, C. Tellini, and P. Vescovi, “A procedure for landslide susceptibility zonation by the conditional analysis method,” Geomorphology, vol. 48, no. 4, pp. 349–364, Dec. 2002.

A. Brenning, “Spatial prediction models for landslide hazards: review, comparison and evaluation,” Nat. Hazards Earth Syst. Sci., vol. 5, no. 6, pp. 853–862, Nov. 2005.

S. Lee and B. Pradhan, “Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models,” Landslides, vol. 4, no. 1, pp. 33–41, Mar. 2007.

I. Cantarino, M. A. Carrion, F. Goerlich, and V. Martinez Ibañez, “A ROC analysis-based classification method for landslide susceptibility maps,” Landslides, vol. 16, no. 2, pp. 265–282, Feb. 2018.

D. Cheng, Y. Cui, F. Su, Y. Jia, and C. E. Choi, “The characteristics of the Mocoa compound disaster event, Colombia,” Landslides, vol. 15, no. 6, pp. 1223–1232, Jun. 2018.

R. J. Marín, J. C. Guzmán-Martínez, H. E. Martínez Carvajal, E. F. García-Aristizábal, J. D. Cadavid-Arango, and P. Agudelo-Vallejo, “Evaluación del riesgo de deslizamientos superficiales para proyectos de infraestructura: caso de análisis en vereda El Cabuyal,” Ing. y Cienc., vol. 14, no. 27, pp. 153–177, Jun. 2018.

E. Aristizábal and J. Gómez, “Inventario de emergencias y desastres en el Valle de Aburrá originados por fenómenos naturales y antrópicos en el período 1880-2007,” Rev. Gestión y Ambient., vol. 10, N, pp. 17–30,

É. Aristizábal, “Características, dinámica y causas del movimiento en masa del barrio el socorro (31 de mayo de 2008) en Medellín,” Rev. EIA, vol. 10, pp. 19--29., jun. 2008.

Integral S.A, U EAFIT, Universidad Nacional de Colombia, Intenisa. S.A, and Solingral. S.A, “Microzonificación sísmica detallada de los municipios de Barbosa, Girardota, Copacabana, Sabaneta, La Estrella, Caldas y Envigado.,” 2006.

G. Rodríguez, H. González, G. Zapata, U. Cossio, and A. M. C. Martínez, “Geología de la plancha 147 Medellín Oriental Escala 1:50.000 Versión 2016,” Medellín, 2016.

F. Guzzetti, P. Reichenbach, F. Ardizzone, M. Cardinali, and M. Galli, “Estimating the quality of landslide susceptibility models,” Geomorphology, vol. 81, no. 1–2, pp. 166–184, Nov. 2006.

Servicio Geológico Colombiano - SGC, “Guía Metodológica para estudios de Amenaza, Vulnerabilidad y Riesgo por movimientos en masa.,” 2015.

G. Herrera et al., “Landslide databases in the Geological Surveys of Europe,” Landslides, vol. 15, no. 2, pp. 359–379, Feb. 2018.

Corporación OSSO, “Que es DesInventar,” Sept, 2017.

Servicio Geológico Colombiano SGC, “SIMMA.,” 2017.

J. Corominas et al., “Recommendations for the quantitative analysis of landslide risk,” Bull. Eng. Geol. Environ., no 2. vol. 73, pp. 209-- 263., Nov. 2013.

T. Glade and M. J. Crozier, “A Review of Scale Dependency in Landslide Hazard and Risk Analysis,” in Landslide Hazard and Risk, vol. 75, Chichester, West Sussex, England: John Wiley & Sons, Ltd, 2012. pp. 75 -138.

C.-T. Lee, C.-C. Huang, J.-F. Lee, K.-L. Pan, M.-L. Lin, and J.-J. Dong, “Statistical approach to storm event-induced landslides susceptibility,” Nat. Hazards Earth Syst. Sci., vol. 8, no. 4, pp. 941–960, Aug. 2008.

M. L. Süzen and V. Doyuran, “Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey,” Eng. Geol., vol. 71, no. 3–4, pp. 303–321, Feb. 2004.

P. Atkinson, H. Jiskoot, R. Massari, and T. Murray, “Generalized linear modelling in geomorphology,” Earth Surf. Process. Landforms, vol. 23, no. 13, pp. 1185–1195, Dec. 1998.<1185::AID-ESP928>3.0.CO;2-W

B. A. Olshausen, “Bayesian probability theory.” pp. 1–6, 2004.

E. R. Sujatha, P. Kumaravel, and G. V. Rajamanickam, “Assessing landslide susceptibility using Bayesian probability-based weight of evidence model,” Bull. Eng. Geol. Environ., vol. 73, no. 1, pp. 147–161, Feb. 2014.

N. R. Regmi, J. R. Giardino, and J. D. Vitek, “Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA,” Geomorphology, vol. 115, no. 1–2, pp. 172–187, Feb. 2010.

C. J. van Westen, N. Rengers, and R. Soeters, “Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment,” Nat. Hazards, vol. 30, no. 3, pp. 399–419, Nov. 2003.

H.-J. Oh and S. Lee, “Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system,” Environ. Earth Sci., vol. 62, no. 5, pp. 935–951, Mar. 2011.

R. K. Dahal and S. Hasegawa, “Representative rainfall thresholds for landslides in the Nepal Himalaya,” Geomorphology, vol. 100, no. 3–4, pp. 429–443, Aug. 2008.

A. Ozdemir and T. Altural, “A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey,” J. Asian Earth Sci., vol. 64, no. 5, pp. 180–197, Mar. 2013.

Servicio Geológico Colombiano - SGC, “Guía Metodológica para Zonificación de Amenaza por Movimientos en Masa a escala 1:25.000.,” Bogotá, 2017.

P. M. Atkinson and R. Massari, “Generalised linear modelling of susceptibility to landsliding in the central apennines, italy,” Comput. Geosci., vol. 24, no. 4, pp. 373–385, May 1998.

Australian Geomechanics Society, “Australian Geomechanics,” Australia. 2007.

M. T. Davis, P.A, Goodrich, “A proposed strategy for the validation of ground-water flow and solute transport models”., vol. 23, no. 9. Albuquerque, NM,Nuclear Energy Agency of the OECD (NEA), 1991.

C.-J. F. Chung and A. G. Fabbri, “Validation of Spatial Prediction Models for Landslide Hazard Mapping,” Nat. Hazards, vol. 30, no. 3, pp. 451–472, Nov. 2003.

T. Fawcett, “An introduction to ROC analysis,” Pattern Recognit. Lett., vol. 27, no. 8, pp. 861–874, Jun. 2006.

G. G. Chevalier, V. Medina, M. Hürlimann, and A. Bateman, “Debris-flow susceptibility analysis using fluvio-morphological parameters and data mining: application to the Central-Eastern Pyrenees,” Nat. Hazards, vol. 67, no. 2, pp. 213–238, Jun. 2013.

D. J. Cruden, D. M., & Varnes, “Landslides: investigation and mitigation. Chapter 3-Landslide types and processes.,” in Transportation research board special report, vol. 247, Transportation Research Board,washington 1996, pp. 36–75.

Z. Jing, G. Wang, , S. Zhang, & C. Qiu, “Building Tianjin driving cycle based on linear discriminant analysis”.Transportation Research Part D: Transport and Environment, 53, 78-87, Jun. 2017.

How to Cite
Aristizábal-Giraldo, E., Vasquez Guarin, M., & Ruíz, D. (2019). The Susceptibility of Landslide Evaluation and Zoning by Statistical Methods. TecnoLógicas, 22(46), 39-60.


Download data is not yet available.
Research Papers