The south-western part of Croatia, i.e. the area of central Istria, comprises the research area, (approximately 500 km 2 ). It is characterized by a fl ysch complex with a great number of isolated relief landforms, termed badlands. The importance of badlands (areas with sparse or no vegetation) lies in the fact that sediment production from these areas is 8000 times higher than from areas with vegetation. Here, the badland inventory presents 5568 distinguishable badlands (polygons) with a total badland area of 10.7 km 2 . Spatial analysis of the badland inventory showed that erosive channel fl ow at the steep slope foot is the most important factor in badland formation and development for the area of central Istria.
In this paper, for the first time, a regional-scale 1:100,000 landslide-susceptibility map (LSM) is presented for Sisak-Moslavina County in Croatia. The spatial relationship between landslide occurrence and landslide predictive factors (engineering geological units, relief, roughness, and distance to streams) is assessed using the integration of a statistically based frequency ratio (FR) into the analytical hierarchy process (AHP). Due to the lack of landslide inventory for the county, LiDAR-based inventories are completed for an area of 132 km2. From 1238 landslides, 549 are chosen to calculate the LSM and 689 for its verification. Additionally, landslides digitized from available geological maps and reported via the web portal “Report a landslide” are used for verification. The county is classified into four susceptibility classes, covering 36% with very-high and high and 64% with moderate and low susceptibility zones. The presented approach, using limited LiDAR data and the extrapolation of the correlation results to the entire county, is encouraging for primary regional-level studies, justifying the cost-benefit ratio. Still, the positioning of LiDAR polygons prerequires a basic statistical analysis of predictive factors.
The Gajevo landslide in the Kravarsko area (Vukomeričke Gorice hilly area, northern Croatia) was chosen for investigation due to the existing landslide risk for the households at the landslide crown. Available data are limited, but a new landslide map and cross-section was developed within the presented research, mostly based on detailed light detection and ranging (LiDAR) data and field mapping. By comparing available orthophotos of the landslide, resident testimonies, precipitation data, and media releases, it was concluded that the landslide was activated in February 2014. The landslide was primarily triggered by increased precipitation (its measured variations could be in direct connection with ongoing global climate changes), but natural terrain features and anthropogenic factors also affected slope stability. New findings have led to the conclusion that the existing landslide area is large and complex and the crown and head scarp area should be stabilized by urgent remediation measures.
In this paper, a preliminary analysis of the landslide inventory is presented for the wider area of the municipalities of Glina and Dvor, within Sisak-Moslavina County in Croatia, where LiDAR scanning for 45.85 km2 was conducted. Landslide polygons were outlined based on the visual interpretation of HRDEM derivates. In total, 477 landslides were contoured with an average landslide density of 9.85 per km2. Most of the landslides are characterised as moderate, shallow, and not recent. The spatial relationship between landslides and geological units is expressed with the landslide index. Subsequently, the geological units were grouped into four engineering geological units representing different susceptibilities to landslides. The geological units most prone to landslides are the Eocene, Oligocene, Palaeocene and Jurassic sandstones. Even though all geological units were analysed here, the majority of landslides are within sandstones. A particular emphasis was on landslide occurrence in metamorphic and igneous rocks of the ophiolite sequence, a distinctive characteristic of the research area where less susceptibility to landslide processes was observed. Moreover, to further distinguish the differences between the units in the area a morphometric characteristic (relief) and drainage network was also analysed. The purpose of this analysis was to additionally confirm the landslide susceptibility assessment and the division of geological units into engineering geological units, which again implied the different behaviours between landslides in igneous and metamorphic rocks compared to sandstones. Because the research area is poorly studied regarding landslide susceptibility, relief, and drainage networks, these findings will be a step forward in recognising the relationship between them and creating a base for the development of a landslide susceptibility map for this area.
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