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This article presents a Geographic Information System (GIS) assessment of Landslide Susceptibility Zonation (LSZ) in North Macedonia. Because of the weak landslide inventory, statistical method (frequency ratio) is combined with Analytical Hierarchy Process (AHP). In this study, lithology, slope, plan curvature, precipitations, land cover, distance from streams, and distance from roads were selected as precondition factors for landslide occurrence. There are two advantages of the approach used. The first is the possibility of comparing of the results and cross-validation between the statistical and expert based methods with an indication of the advantages and drawbacks of each of them. The second is the possibility of better weighting of precondition factors for landslide occurrence, which can be useful in cases of weak landslide inventory. The final result shows that in the case of weak landslide inventory, LSZmap created with the combination of both models provide better overall results than each model separately.

In order to assess the rainfall erosivity in the Pannonian basin, several parameters which describe distribution, concentration and variability of precipitation were used, as well as 9 extreme precipitation indices. The precipitation data is obtained from the European Climate Assessment and Dataset project for the period 1961-2014, for 8 meteorological stations in northern Serbia, 5 in Hungary and 1 in eastern Croatia. The extreme values of precipitation were calculated following the indices developed by the ETCCDI. RclimDex software package was used for indices calculation. Based on statistical analysis and the calculated values, the results have been presented with Geographic Information System (GIS) to point out the most vulnerable parts of the Pannonian basin, with regard to pluvial erosion. This study presents the first result of combined rainfall erosivity and extreme precipitation indices for the investigated area. Results of PCI indicate presence of moderate precipitation concentration (mean value 11.6). Trend analysis of FI (mean value 22.7) and MFI (mean value 70.2) implies a shift from being largely in the low erosivity class, to being completely in the moderate erosivity class in the future, thus indicating an increase in rainfall erosivity for most of the investigated area (except in the northwestern parts). Furthermore, the observed precipitation extremes suggest that both the amount and the intensity of precipitation are increasing. The knowledge about the areas affected by strong soil erosion could lead to introducing effective measures in order to reduce it. Long term analysis of rainfall erosivity is a significant step concerning flood prevention, hazard mitigation, ecosystem services, land use change and agricultural production.

In the topography of war landscapes the remains of war are found in the form of trenches, bombing craters and remnants of war infrastructure. Today war landscapes are “overlaid” by post-war “layers” of cultural landscapes. It requires non-invasive remote-sensing methods, e.g. time series of aerial photographs and high-resolution terrain models (LiDAR digital terrain model) to recognize these landscapes.