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Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia

Bulletin of Engineering Geology and the Environment volume 75, pages 63–87 (2016)Cite this article

Abstract

The purpose of the current study is to produce landslide susceptibility maps using different probabilistic and bivariate statistical approaches; namely, frequency ratio (FR), weights-of-evidence (WofE), index-of-entropy (IofE), and Dempster–Shafer (DS) models, at Wadi Itwad, Asir region, in the southwestern part of Saudi Arabia. Landslide locations were identified and mapped from interpretation of high-resolution satellite images, historical records, and extensive field surveys. In total, 326 landslide locations were mapped using ArcGIS and divided into two groups; 75 % and 25 % of landslide locations were used for training and validation of models, respectively. Twelve layers of landslide-related factors were prepared, including altitude, slope degree, slope length, topography wetness index, curvature, slope aspect, distance from lineaments, distance from roads, distance from streams, lithology, rainfall, and normalized difference vegetation index. The relationships between the landslide-related factors and the landslide inventory map were calculated using different statistical models (FR, WofE, IofE, and DS). The model results were verified with landslide locations, which were not used during the model training. In addition, receiver operating characteristic curves were applied, and area under the curve (AUC) was calculated for the different susceptibility maps using the success (training data) and prediction (validation data) rate curves. The results showed that the AUC for success rates are 0.813, 0.815, 0.800, and 0.777, while the prediction rates are 0.95, 0.952, 0.946, and 0.934 for FR, WofE, IofE, and DS models, respectively. Subsequently, landslide susceptibility maps were divided into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the percentage of training and validating landslides locations in high and very high landslide susceptibility classes in each map were calculated. The results revealed that the FR, WofE, IofE, and DS models produced reasonable accuracy. The outcomes will be useful for future general planned development activities and environmental protection.

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Acknowledgments

The authors would like to thank the Saudi Geological Survey for providing scientific and logistical support for this work. Also, we would like to thank the anonymous reviewers for their critical comments on the earlier version of the manuscript.

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Authors and Affiliations

  1. Geology Department, Faculty of Science, Sohag University, Sohag, Egypt

    Bosy A. El-Haddad

  2. Geological Hazards Department, Applied Geology Sector, Saudi Geological Survey, P.O. Box 54141, 21514, Jeddah, Kingdom of Saudi Arabia

    Ahmed Mohamed Youssef & Basem K. Dhahry

  3. Department of Natural Resources and Environment, College of Agriculture, Shiraz University, Shiraz, Iran

    Hamid Reza Pourghasemi

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  1. Ahmed Mohamed Youssef
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Youssef, A.M., Pourghasemi, H.R., El-Haddad, B.A. et al. Landslide susceptibility maps using different probabilistic and bivariate statistical models and comparison of their performance at Wadi Itwad Basin, Asir Region, Saudi Arabia. Bull Eng Geol Environ 75, 63–87 (2016). https://doi.org/10.1007/s10064-015-0734-9

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Keywords

  • Landslide
  • Susceptibility mapping
  • Frequency ratio
  • Weights of evidence
  • Index of entropy
  • Dempster–Shafer
  • GIS
  • Saudi Arabia

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