Biljana Abolmasov

The ICL Adriatic-Balkan Network: analysis of current state and planned activities

International Consortium on Landslides (ICL) Adriatic-Balkan Network was established in January 2012 as one of eight regional and thematic ICL networks to promote activities of the International Consortium on Landslides and the International Programme on Landslides. This paper presents the annual report of the ICL Adriatic-Balkan Network for the year 2012. The main activity of the regional network was to complete an overview of publicly available data and sources about landslides in the region, scientific and professional practices related to evaluation and mitigation of landslide hazard, as well as related legislative framework. Recommendations for the discussion and endorsement in the course of the ICL Adriatic-Balkan Network activities will be derived from the analysis of strengths, weaknesses, opportunities, and threats related to landslide issues which are present at the national level in Croatia, Slovenia, and Serbia and at the regional level. Discussion and endorsement of the recommendations are planned as a further activity which will be held in March 2013 in Zagreb (Croatia), during the planned first regional symposium on landslides in the Adriatic-Balkan Region.

A geotechnical model of the Umka landslide with reference to landslides in weathered Neogene marls in Serbia

This paper describes a characteristic landslide model for landslides typically hosted in Neogene formations in Serbia, especially along the right banks of the Sava and Danube Rivers. It is focussed on the particular landslide Umka near Belgrade, which is a paradigm for numerous landslides in that area. Various field investigations and laboratory tests carried out in several campaigns, including 1979, 1991–1993 and 2005, underpinned the conception of a general model for this typological landslide. Additionally, a new landslide monitoring campaign started in 2010 provided supplementary data support for the model development. Landslide characteristics, sliding mechanism and material properties based on all these data are first summarised and discussed and then featured in a general model. It is assumed that the landslide is hosted in the weathered zone of grey marls and that the main sliding surface typically propagates along the contact between the fresh and weathered marls. Furthermore, the triggering is principally associated with lateral river erosion in the landslide toe, although heavy precipitation and snow melting have been witnessed to be important indirect triggers. Their correlation to the recorded displacements was difficult to determine due to complex hydrogeological relations and an isolated groundwater system, which is another common characteristic of this landslide type. Back analysis on the basis of the adopted model and the determined geotechnical parameters has been performed. The latter analysis is of particular interest because the Umka landslide is currently under consideration for a mitigation and stabilisation plan related to the construction of a new motorway route.

GIS application for landfill site selection: a case study in Pančevo, Serbia

Landfill site selection is a complex process because it requires knowledge about a large number of criteria, parameters, and regulations. The aim of this study was to describe a methodology for landfill site selection and relevant criteria from a geological engineering point of view. To determine landfill suitability in the municipality of Pančevo, Serbia, we used the geographic information system (GIS) and analytical hierarchical method (AHP). Seven criteria and eighteen subcriteria are discussed, compared, and evaluated. The final map was obtained by overlaying and is reclassified into four classes: unsuitable, poorly suitable, moderately suitable, and most suitable. The results obtained show that 62.31 % of locations are unsuitable, 13.49 % are poorly suitable, 12.08 % are moderately suitable, and 12.12 % are most suitable. The analysis revealed geological engineering criteria as the most important, followed by hydrogeological and hydrological criteria. Geomorphological criteria were the least important.

Using multiresolution and multitemporal satellite data for post-disaster landslide inventory in the Republic of Serbia

This paper focuses on a specific event-based landslide inventory compiled after the May 2014 heavy rainfall episode in Serbia as a part of the post-disaster recovery actions. The inventory was completed for a total of 23 affected municipalities, and the municipality of Krupanj was selected as the location for a more detailed study. Three sources of data collection and analysis were used: a visual analysis of the post-event very high and high (VHR-HR) resolution images (Pléiades, WorldView-2 and SPOT 6), semi-automatic landslide recognition in pre- and post-event coarse resolution images (Landsat 8) and a landslide mapping field campaign. The results suggest that the visual and semi-automated analyses significantly contributed to the quality of the final inventory, including the associated planning strategies for conducting future field campaigns (as a final stage of the inventorying process), all the more so because the field-based and image-based inventories were focused on different types of landslides. In the most affected municipalities that had very high resolution satellite image coverage (19.52% of the whole study area), the density of the recognized landslides was approximately three times higher than that in those municipalities without satellite image coverage (where only field data were available). The total number of field-mapped landslides for the 23 municipalities was 1785, while image-based inventories, which were available only for the municipalities with satellite image coverage (77.43% of the study area), showed 1298 landslide records. The semi-automated landslide inventory in the test area (Krupanj municipality), which was based on coarse resolution multitemporal images (Landsat 8), counted 490 landslide instances and was in agreement with the visual analysis of the higher resolution images, with an overlap of approximately 40%. These results justify the use of preliminary inventorying via satellite image analysis and suggest a considerable potential use for preliminary visual and semi-automated landslide inventorying as an important supplement to field mapping.

Landslide Umka: The First Automated Monitoring Project in Serbia

In the past decade, there has been a gradual introduction of systematic monitoring on the largest landslides in Serbia by establishing a network of monitoring facilities. The first manual monitoring system was installed near Belgrade on Umka landslide including survey points, inclinometers, piezometers, triaxial deformeters etc. As the rapid adoption of new technologies continues – the natural evolution of equipment for landslide monitoring has started. The technological evolution of GPS based systems creates the potential for automated remote collection of accurate, high resolution data and represents step forward that will increase speed, precision, cost effectiveness and overall quality of landslide investigations. This paper presents first results, features and benefits of introducing automated approach in order to provide high quality data as a base for detailed landslide investigations.

The Analysis of Landslide Dynamics Based on Automated GNSS Monitoring—A Case Study

In the past decade, there has been a gradual introduction of systematic monitoring on the largest landslides in Serbia by establishing a network of monitoring facilities. Umka landslide is complex active landslide whose activity intensifies in the periods of saturation by precipitation as well as sudden changes in the water levels of the Sava river. Course, direction and speed of displacement have been analysed based on automated GNSS monitoring results completed in the more than three years. Based on the results, Umka landslide is classified as complex, active, slow to very slow moving landslide.

Rockfall Monitoring Based on Surface Models

This research addresses surface analysis based on the Terrestrial Laser Scanning data exampled on rockslope site along M-22 highroad near Ljig in Serbia. The slope is about 100 m wide and over 20 m high. The scanning was performed in three epochs 2011, 2013 and 2014, but only the latter two were involved in the analysis due to insufficient quality of the pilot epoch. Gap between the latter two epochs coincided whit local rockfall events detected in the middle section of the slope. Scanning was performed by Leica ScanStation P20 instrument. Two consecutive point clouds were produced and gridded to 3 cm resolution. Comparative assessment of both point clouds and related surface models revealed the volumes and spatial extents of the anticipated rockfalls. Data were analyzed in two software packages: CloudCompare and GeomagicStudio, that have different modeling approaches based on direct point cloud analysis and mashed surface comparison, respectively. We compared advantages and disadvantages of each approach. Finally, we addressed how LiDAR technology can contribute qualitatively and quantitatively for research and monitoring of rockslopes.

IPL Project 181: Study of Slow Moving Landslide Umka Near Belgrade, Serbia

Serbia is well known for numerous landslide phenomena. Landslides are particularly notable for the valley walls of the rivers Sava and Danube and their respective tributaries. They have in common the fact that they all originated in complexes of Neogene sediments made of different lithological elements, and most often clays, sands, and marls with pronounced zones of weathering up to approx. 20 m deep. Landslides on the right banks of the Sava and Danube have deep sliding surfaces, formed on the contact of the weathered zone and unaltered clay and marl sediments. The basic trigger of the processes, apart from the precipitation, is prolonged erosion of the right banks of the Sava and Danube rivers. Most of the landslides are active or suspended, where periods between reactivation phases could be several years long. The IPL-181 Project started in November 2012. The study area is located on the right bank of Sava River, 25 km southwest of Belgrade, Serbia. The project focused on review and analysis of previous detailed site investigations and field instrumentation, analysis of aerial photo and orthophoto images, and analysis of monitoring results. Project beneficiaries will be the local community, and local and regional authorities. Here we present results of the 1st year of proposed project targets—a review and analysis of previous field investigations performed by Project participants.

Machine Learning and Landslide Assessment in a GIS Environment

This chapter introduces theoretical and practical aspects for applying GIS and geocomputation methods in landslide assessment problems. Machine Learning techniques in combination with GIS are proven useful for computation and building of complex non-linear spatial models, which is why they have been chosen in our work. Modeling principles that include basic Machine Learning techniques (Artificial Neural Networks, Decision trees, Support Vector Machines) and additional useful procedures are described to show how they can be applied to address a complex problem such as landslide assessment. Two types of models are proposed in the work herein that are useful for describing landslide susceptibility and landslide prediction. The region of Halenkovice in Czech Republic is presented as a case study to illustrate and bring closer the practical aspects of landslide assessment. These aspects consider data preparation and preprocessing, scale effects, model optimization, and evaluation. The results show that Support Vector Machines and similar Machine Learning (ML) techniques can be successfully applied to address the zoning of landslide susceptibility, which might be an important breakthrough for potential applications in regional planning and decision-making.

Relative Landslide Risk Assessment for the City of Valjevo

This paper represents a relative landslide risk assessment of the City of Valjevo in Western Serbia. After the extreme rainfall during the May 2014, many new landslides were triggered, and Valjevo was one of the most affected areas in Serbia. The modeling was preceded by the data selection, and included ranging and preprocessing of the conditioning factors. The following eight factors were chosen as representative: stream distance, slope, lithology, elevation, distance from hydrogeological borders, land use, erodibility and aspect. Landslide susceptibility analysis was completed using the Analytical Hierarchy Process (AHP) multi-criteria method. Validation was performed by cross-referencing with an existing landslide inventory, which was made by field mapping and interpretation of satellite images. Finally, the relative risk was determined for the City of Valjevo by using a realistic population distribution model as a source for elements at risk. The results show the distribution of risk and suggest that 20% of the inhabited area falls into the high risk class, but this encompasses less than 5% of the total population.