Landslide Susceptibility Evaluation of Southeastern Çanakkale Strait (NW Türkiye) Using Logistic Regression, Artificial Neural Network and Support Vector Machine

摘要: This study focuses on landslide susceptibility assessment of the area between Güzelyalı and Lapseki (Çanakkale, Türkiye) by using logistic regression, artificial neural network (ANN) and support vector machine methods. Nine input parameters such as topographic elevation, lithology, slope, land use, aspect, curvature, distance to streams, TWI, and NDVI were selected as the landslide conditioning parameters. The frequency ratio values were also calculated for the parameters and their subclasses and were assigned to express all continuous and categorical input parameters in the same scale for the considered prediction models. In addition, sensitivity (Recall), accuracy, precision, kappa indexes, F1-score and receiver operating characteristic based on area under curve approach were calculated to assess the performances of the so produced landslide susceptibility maps. Considering all performance indicators …