A Combined Method for Preparation of Landslide Susceptibility Map in Izmir (Türkiye)

Landslide susceptibility maps (LSMs) have been used frequently by researchers for manyyears in prediction of the occurrence of landslides. Since many landslides have occurred there inthe past, Izmir, which is the third largest city of Türkiye, was selected for landslide susceptibilityassessment using geographical information systems (GIS) and remote sensing (RS) techniques. Theaim of this study is to create a better landslide susceptibility map (LSM) for the Izmir metropolitanarea and its surroundings by minimizing the shortcomings of some of the commonly used methods.For this purpose, four different LSMs were prepared using the logistic regression (LR), analyticalhierarchy process (AHP), frequency ratio (FR) and index of entropy (IOE) methods with susceptibilityclasses ranging from extremely low to extremely high. These four maps were then overlaid. Thehighest susceptibility class was chosen for each pixel to form a combined landslide susceptibility map(CLSM). The final CLSM is a thematic map presenting landslide susceptibility using five differentclasses. The geo-environmental factors selected for use in this analysis were slope angle, slope aspect,lithology, slope curvature, elevation, density of discontinuity, stream power index (SPI), land useand distance from stream. Finally, the areas under receiver-operating characteristic (ROC) curveswere employed to compare the predictive capability of the five models used. Overall, the CombinedMethod (CM) (AUC = 0.887) performed very well for landslide susceptibility assessment. Out of allthe models, the IOE model (AUC = 0.841) had a slightly lower predictive capability than the CMmodel, and AHP (AUC = 0.816) was better than FR (AUC = 0.738) and LR (AUC = 0.727). It wasobserved that, compared to rural areas, residential areas of Izmir city are particularly susceptible tolandslides.