Landslide susceptibility mapping of Gdynia using geographic information system-based statistical models

Abstract This work aims to prepare a reliable landslide susceptibility model and analyse the factors contributing landslides in dynamic environment by considering city of Gdynia, Poland as case study. Geological, geomorphological, hydrological, hydrogeological, anthropogenic predisposing are considered using geographic information systems. Ground types at different depths (1 m 4 b.g.l.) used statistical assessment for first time. Landslide maps developed two techniques presenting landslides, 13 conditioning factors, three methods: index, weight evidence, logistic regression. The have an influence on mass movement formation, but their roles different. Many these passive interrelated some them also related active i.e. triggers. Consideration many thematic layers approach allows selection most appropriate geo-environmental variables. significant that affect likelihood landsliding include land use cover well topography. generated index appear be over-predicted. regression only independent controlling (slope angle, slope aspect, lithology) sufficient compile map Gdynia. Prediction rate curve plots show produced exhibits highest prediction accuracy. results emphasize need check independence instability subset validation.