Statistical-based models for the production of landslide susceptibility maps and general risk analyses: a case study in Maçka, Turkey

Abstract

The district of Maçka in Trabzon, in the Eastern Black Sea Region of Turkey, frequently experiences landslides, resulting in the highest number of disaster victims. In this study, Landslide Susceptibility Maps (LSMs) were generated via the Statistical-based Frequency Ratio (FR) and Modified Information Value (MIV) models using 10 factors. Out of the 150 landslides in the region, 105 (70%) were utilized in creating the maps, and the remaining 45 (30%) were reserved for validation. The models demonstrated success rates of 87.5% and 84.9%, along with prediction rates of 84.8% and 83.1%, respectively, as determined by the receiver operating characteristics curve and area under the curve values. While both models achieved acceptable levels of accuracy, MIV outperformed FR. Additionally, the risk status of 5413 buildings and forested areas was examined. The results showed that 78.64% (FR) and 80.79% (MIV) of the buildings were situated in high landslide risk areas. Regarding forest areas, 39.30% (FR) and 41.35% (MIV) were observed in high-risk landslide areas. In the next step, neighborhood landslide risk statuses were examined, revealing risks ranging from 90 to 100% in some areas. The final step concentrated on risk analyses for construction plans in a chosen pilot neighborhood using two criteria. 88.75% of all parcels were observed in high-risk areas, with hazelnut groves at 79.67% in high-risk zones. Conversely, 71.89% of fruit trees were in low-risk areas. The results align with the literature, indicating that LSMs can serve as a versatile base map.