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Comparative review of data-driven landslide susceptibility models: case study in the Eastern Andes mountain range of Colombia

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Abstract

Estimating the likelihood of landslides has proven to be critical for development and protection of infrastructure (e.g. pipelines, roads) and urban settlements. Currently, for regional studies of landslide susceptibility only qualitative or statistical evaluations are possible due to the large spatial variability of geological properties, topography, rainfall patterns, etc. In this paper, we explore an alternative to these approaches using data-driven methodologies to determine landslide susceptibility. We give special attention to the use of geographical information systems, machine learning and statistical techniques to build landslide susceptibility maps. These methods have input as fourteen key causative factors that might influence landslides occurrence. Additionally, feature extraction and feature selection are performed to evaluate if dimensionality reduction increases the prediction accuracy of the machine learning models. The models were compared using a case study in the Eastern Cordillera of Colombia, where the best performing model achieved a predictive performance of \(93.07\%\).

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Acknowledgements

The authors would like to thank the anonymous reviewer who provided numerous comments and suggestions, resulting in an improved manuscript.

Funding

This work was supported by Universidad de los Andes (FAPA fund PR.3.2020.7367 granted to Dr. Nitescu).

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Universidad de los Andes, Bogotá, Colombia

    Wilmar Calderón-Guevara, Mauricio Sánchez-Silva & Daniel F. Villarraga

  2. Department of Geosciences, Universidad de los Andes, Bogotá, Colombia

    Wilmar Calderón-Guevara & Bogdan Nitescu

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  1. Wilmar Calderón-Guevara
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  2. Mauricio Sánchez-Silva
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Wilmar Calderón Guevara prepared, processed the data, and executed the GBM, RF and WOE methods. Daniel Villarraga executed the ANN method. Mauricio Sánchez-Silva, Bogdan Nitescu and Wilmar Calderón-Guevara wrote the manuscript and supported the analysis and discussion. All authors have checked and revised the manuscript.

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Calderón-Guevara, W., Sánchez-Silva, M., Nitescu, B. et al. Comparative review of data-driven landslide susceptibility models: case study in the Eastern Andes mountain range of Colombia. Nat Hazards 113, 1105–1132 (2022). https://doi.org/10.1007/s11069-022-05339-2

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