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The paper discusses the impact that the quality of the digital elevation model (DEM) has on the final result of landslide susceptibility modeling (LSM). The landslide map was developed on the basis of the analysis of archival geological maps and the Light Detection and Ranging (LiDAR) digital elevation model. In addition, complementary field studies were conducted. In total, 92 landslides were inventoried and their degree of activity was assessed. An inventory of the landslides was prepared using a 1-m-LiDAR DEM and field research. Two digital photogrammetric elevation models with an elevation pixel resolution of 20 m were used for landslide susceptibility modeling. The first digital elevation model was obtained from a LiDAR point cloud (DEM–airborne laser scanning (ALS)), while the second model was developed based on archival digital stereo-pair aerial images (DEM–Land Parcel Identification System (LPIS)). Both models were subjected to filtration using a Gaussian low-pass filter to reduce errors in their elevation relief. Then, using ArcGIS software, a differential model was generated to illustrate the differences in morphology between the models. The maximum differences in topographic elevations between the DEM–ALS and DEM–LPIS models were calculated. The Weights-of-Evidence model is a geostatistical method used for the landslide susceptibility modeling. Six passive factors were employed in the process of susceptibility generation: elevation, slope gradient, exposure, topographic roughness index (TRI), distance from tectonic lines, and distance from streams. As a result, two landslide susceptibility maps (LSM) were obtained. The accuracy of the landslide susceptibility models was assessed based on the Receiver Operating Characteristic (ROC) curve index. The area under curve (AUC) values obtained from the ROC curve indicate that the accuracy of classification for the LSM–DEM–ALS model was 78%, and for the LSM–LPIS–DEM model was 73%.

Commission I, WG I/2 KEY WORDS: Susceptibility map, landslide, Weights of Evidence, LiDAR, Podhale region ABSTRACT:Podhale is a region in southern Poland, which is the northernmost part of the Central Carpathian Mountains. It is characterized by the presence of a large number of landslides that threaten the local infrastructure. In an article presents application of LiDAR data and geostatistical methods to assess landslides susceptibility map. Landslide inventory map were performed using LiDAR data and field work. The Weights of Evidence method was applied to assess landslides susceptibility map. Used factors for modeling: slope gradient, slope aspect, elevation, drainage density, faults density, lithology and curvature. All maps were subdivided into different classes. Then were converted to grid format in the ArcGIS 10.0. The conditional independence test was carried out to determine factors that are conditionally independent of each other with landslides. As a result, chi-square test for further GIS analysis used only five factors: slope gradient, slope aspect, elevation, drainage density and lithology. The final prediction results, it is concluded that the susceptibility map gives useful information both on present instability of the area and its possible future evolution in agreement with the morphological evolution of the area.

The research area is located on the boundary between two Paleozoic structural units: the Radom–Kraśnik Block and the Mazovian–Lublin Basin in the southeastern Poland. The tectonic structures are separated by the Ursynów–Kazimierz Dolny fault zone. The digital terrain model obtained by the ALS (Airborne Laser Scanning) method was used. Classification and filtration of an elevation point cloud were performed. Then, from the elevation points representing only surfaces, a digital terrain model was generated. The model was used to visually interpret the course of topolineaments and their automatic extraction from DTM. Two topolineament systems, trending NE–SW and NW–SE, were interpreted. Using the kernel density algorithm, topolineament density models were generated. Using the Empirical Bayesian Kriging, a thickness model of quaternary deposits was generated. A relationship was observed between the course of topolineaments and the distribution and thickness of Quaternary formations. The topolineaments were compared with fault directions marked on tectonic maps of the Paleozoic and Mesozoic. Data validation showed consistency between topolineaments and tectonic faults. The obtained results are encouraging for further research.

The cliff in Jastrzębia Góra is one of the most an active landslide areas along the Polish Baltic coast. The aim of these studies was to determine the dynamics of displacements in an active landslide and to identify the geology of the cliff. Two methods, ALS (Airborne Laser Scanning) and ERT (Electrical Resistivity Tomography), were used for this purpose. Multitemporal ALS data were used to determine the geomorphological changes within the cliff and find the causes of the rapid rate of cliff edge landslides. ALS differential models were the sources of new information about the dynamics of vertical displacement in the landslide and helped calculate the volume of displaced rock masses that occurred over 12 years. The cliff was found to become significantly an active in 2010. This process was observed by analysing the relief of multitemporal digital elevation models, differential models, AND morphological sections and by conducting long-term field observations. The ERT surveys made it possible to generate two 3D ERT electrical resistivity models that provided much new information about the geological structure of the cliff. Additionally, a 2D ERT profile was made through the landslide. The internal structure of the landslide was recognized, and the depth of the slip surface was estimated. The results permitted clarifying the cause of the high landslide activity and the rapid rate of retreat of the cliff edge over the past 12 years. In addition, by means of the results of electrical resistivity surveys and the use of archival boreholes, it was possible to extrapolate a model of the surface relief of the clay hill using geostatistical methods. It was found that at the boundary with the active landslide—the top of the clay layer—is tilted towards the north, i.e. towards the sea, which favours the activation of the landslide. The proposed research methodology, as well as the obtained information, may be of significant assistance in further diagnosis and prognosis of the dynamics of landslide development and the causes of landslide formation within cliff coasts.