UAV-based photogrammetry has many applications today. Measuring of snow depth using Structure-from-Motion (SfM) techniques is one of them. Determining the depth of snow is very important for a wide range of scientific research activities. In the alpine environment, this information is crucial, especially in the sphere of risk management (snow avalanches). The main aim of this study is to test the applicability of fixed-wing UAV with RTK technology in real alpine conditions to determine snow depth. The territory in West Tatras as a part of Tatra Mountains (Western Carpathians) in the northern part of Slovakia was analyzed. The study area covers more than 1.2 km² with an elevation of almost 900 m and it is characterized by frequent occurrence of snow avalanches. It was found that the use of different filtering modes (at the level point cloud generation) had no distinct (statistically significant) effect on the result. On the other hand, the significant influence of vegetation characteristics was confirmed. Determination of snow depth based on seasonal digital surface model subtraction can be affected by the process of vegetation compression. The results also point on the importance of RTK methods when mapping areas where it is not possible to place ground control points.

Water retention is an important hydrological ecosystem service of active floodplain soils. The aim of the study was to evaluate the soil chemical, physical, and hydrological properties in Fluvisols in three different ecosystems that have an impact on water retention hydrological ecosystem services (WRHESs). We selected 16 localities along the Štiavnica River in Central Slovakia, 8 located in riparian zones (RZ), 5 in arable lands (AL), and 3 in grasslands (GL). Soil samples were collected from two layers (0–10 and 20–30 cm). In the laboratory, the soil physical (soil texture) and soil chemical properties (pH, soil organic carbon content, humic and fulvic acid ratio) were determined. Using undisturbed soil samples, the soil physical characteristics (particle density, bulk density, porosity, and actual soil moisture–SMa) were measured. With the help of pedotransfer functions, hydrological soil properties (field water capacity–FWC, wilting point–WP, available water capacity–AWC) were estimated. The recorded properties differed between the localities, ecosystems, and two layers. The SMa values showed a higher soil water retention potential of extensively used ecosystems, such as GL and RZ. However, the hydrological properties estimated by pedotransfer functions (FWC, WP, AWC) showed a higher soil water retention potential in AL localities. This indicated that for calculations, selected pedotransfer functions (particle size fractions, organic matter, and bulk density) and other soil or ecosystem properties (e.g., vegetation cover, meteorological conditions) have an impact on WRHESs. One such soil factor can be the quality of organic matter. On the basis of the results of the ANOVA, significant differences emerged between the different ecosystems for selected basic chemical, physical, and hydrological properties. The effect of the soil layer on the soil properties was revealed only in the case of SOC. The results indicated the effect of different ecosystems on soil WRHES and the importance of extensively managed ecosystems, such as RZ and GL. From this point of view, the reduction in the RZ and GL areas during a period of the last 70 years is negative. The findings should be taken into account in future sustainable floodplain management and landscape architecture.

Our work aimed to compare the chip pile volumes calculated by laser ground scanning, UAV technology, and laser ground measurement and also to determine the accuracy, speed, and economic efficiency of each method. The large chip pile was measured in seven different ways: band measurement, laser measurement with Vertex, global navigation satellite system, handheld mobile laser scanner, terrestrial laser scanner, drone, and smartphone with a light detection and ranging sensor. All the methods were compared in terms of accuracy, price, user-friendliness, and time required to obtain results. The calculated pile volume, depending on the method, varied from 2588 to 3362 m³. The most accurate results were provided by the terrestrial laser scanning method, which, however, was the most expensive and the most demanding in terms of collecting and evaluating the results. From a time and economic point of view, the most effective methods were UAVs and smartphones with LiDAR.

Slovenská akadémia vied vykonáva špičkový základný výskum, dlhodobý strategický a aplikovaný výskum a vývoj a poskytuje prístup k vedeckej infraštruktúre.

Land change models offer an essential resource for predicting future land use and land cover (LULC) change. Model accuracy and proper validation are essential for supporting the decision process related to landscape planning. The paper's main aim is to test and analyse the accuracy of the LULC trend model based on the land cover changes from 1990 to 2012. The Land Change Modeler (TerrSet) and Corine Land Cover data for the area of Slovakia was used. The obtained model was compared with the real changes captured in the next period (2012 to 2018). Different model reliability was observed in different types of land cover. From a relatively low level of reliability to a level of more than 80% concordance. Results pointed on significance and limits of tools for predictive modelling in a specific type of landscape (included very heterogeneous natural conditions) after period of strong institutional changes impact on LULC.