Abstract
The model used statistical analysis for eight causal factors (slope, curvature, elevation, TWI, NDVI, NDSI, land cover, precipitation) of landslide occurrence. All factors were weighted to apply two-dimensional statistical method of a knowledge-based analytic hierarchical process with data extracted from the spatial database and then converted into a map. Final susceptibility maps showed a close agreement between the two models. The models predicted 72.1% and 69% of the empirical data used for the analysis respectively. These maps can be used to demonstrate the effectiveness of two-dimensional statistical model through the relationship between each factor with a resultant landslide susceptibility. The proposed model can be used to reproduce the relationship between each conditional factor without having to resort to multivariate statistics. The models are a powerful tool for assessing natural hazards, and to produce landslide probability maps for a better definition of risk zones.
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