Due to global warming and changing weather conditions, landslide hazards are increasingly threatening global populations. This is particularly concerning for Västra Götaland, Sweden, which has experienced significant material losses from several major landslides. Therefore, there is a need for landslide susceptibility maps (LSM) to identify highly susceptible areas for further implementation of detailed investigations. This study compares the accuracy of three GIS-based methods. Spatial Multi Criteria Decision Analysis (SMCDA), Frequency Ratio (FR), and Random Forest (RF) in delineating susceptible areas in a landslide hazard analysis in Västra Götaland. The accuracy of each LSM is evaluated using three validation methods. Area Under the Receiver Operating Characteristics Curve (AUC) using historical landslide events, how each LSM identify the area affected by the Stenungsund landslide as susceptible, and how well each LSM fits the classification of an existing detailed landslide susceptibility map. This study also evaluates eleven factors for their importance in landslide hazard analysis through a comparative analysis between expert opinions and feature importance from the RF method.

Results show significant differences between the models in both accuracy and delineation of susceptible areas. The RF model was the most accurate, with an AUC of 81.59, compared with 72.75 for SMCDA and 60.75 for FR. RF identified the Stenungsund area as highly susceptible, while SMCDA and FR indicated lower susceptibility. RF also had the best agreement with the small-scale LSM. Despite FR’s better agreement with the small-scale LSM, SMCDA is considered the second-best method due to its higher AUC and greater similarity to RF compared with FR. Soil type and soil depth were identified as the most important factors, particularly for excluding non-susceptible areas. However, due to the complex geological composition of the study area, soil depth is preferred over soil type. Proximity to water bodies, slope, proximity to infrastructure, and Topographic Wetness Index (TWI) are useful for predicting degrees of susceptibility in areas not excluded by soil depth. Lineament density, NDVI, curvature, Land Use Land Cover, and precipitation were found to be less significant for the analysis in Västra Götaland. 

In conclusion, the study recommends RF method for landslide hazard analysis in Västra Götaland due to its higher accuracy. Soil depth should be used instead of soil type due to the geological complexity of the area. Because of the rather poor agreement between the highly accurate RF map and small-scale LSM, the regional maps produced in this study should primarily be used as screening tools to identify areas for further detailed investigations.