Podatność osuwiskowa obszaru Krakowa

Abstract

Landslide susceptibility of Kraków city area.A b s t r a c t. Due to the differentiation of landslides in Kraków city area, an artificial neural network method (multilayer perceptron) was used to determine the landslide susceptibility (LS). The calculations were performed in the r.landslide module. The network learning was carried out on the basis of 8 thematic layers (slopes, slope exposure, absolute height, relative height, convergence index, surface lithology, sub Quaternary lithology, distance from tectonic discontinuities). For modelling, 434 points representing landslides and the same number of points of locations without landslides were used. Among the set of points, 70% was allocated to the training phase, 15% to the validation phase, and 15% to the phase. In order to assess the network performance, based on the results of the test phase, a confusion matrix was made. Approximately 22% of the city’s area is susceptible to landslide occurrence (LS > 0.05 ). It overlap existing landslides and cover areas where they have not occurred yet. The greatest number of areas susceptible to landslide occurrence is located in districts X (54% of the district area) and VII (47%). There are also the most susceptible areas (LS > 0.95). The sensitivity analysis implemented in the module showed that among the thematic layers used for modelling the slopes, convergence index, distance from tectonic discontinuities and sub-Quaternary lithology have the greatest impact on the landslide susceptibility.