The presented study uses the recent colour aerial photographs, historical black and white aerial photographs, and detailed digital elevation model to assess the spatial distribution and long-term temporal dynamics of soil loss in agriculturally intensively exploited loess hilly land with a subcontinental temperate climate. The strongly eroded soils appear in the studied area as bright patterns, surrounded by darker soils, and they are well visible on aerial photos. Three approaches of interpretation of aerial photographs were tested: visual interpretation, pixel-based image classification, and object-based image classification. All three methods provided detailed maps of soil redistribution patterns. The bright areas as the areas of soil degradation characterized by erosion increased from 1949 until 2011 by 76%. A detailed map of areal erosion patterns was used for the validation of water erosion models. LS-factor of USLE and ED’ index of USPED were selected for expressing the relation of real erosion to the terrain. The relationship between surface morphology and real erosion is very complex, and the tested water erosion models do not express it sufficiently. Therefore, the first and second-order directional derivative of the surface elevations with respect to the tillage direction has been tested. The absolute value of the first-order directional derivative showed better results and better corresponded with the real erosion pattern than the other morphometric characteristics. The findings suggest that tillage is the dominant erosion factor in the area.

With its ability to estimate yield, winemakers may better manage their vineyards and obtain important insights into the possible crop. The proper estimation of grape output is contingent upon an accurate evaluation of the morphology of the vine canopy, as this has a substantial impact on the final product. This study’s main goals were to gather canopy morphology data using a sophisticated 3D model and assess how well different morphology characteristics predicted yield results. An unmanned aerial vehicle (UAV) with an RGB camera was used in the vineyards of Topoľčianky, Slovakia, to obtain precise orthophotos of individual vine rows. Following the creation of an extensive three-dimensional (3D) model of the assigned region, a thorough examination was carried out to determine many canopy characteristics, including thickness, side section dimensions, volume, and surface area. According to the study, the best combination for predicting grape production was the side section and thickness. Using more than one morphological parameter is advised for a more precise yield estimate as opposed to depending on only one.

The presented study introduces the most common and significant insect pests of the grapevine (Vitis vinifera) in Slovakia, specifically the occurrence of the European grapevine moth (Lobesia botrana) and the American grapevine leafhopper (Scaphoideus titanus). Historical records set prerequisites to studying the complex interactions between the pests and their host plant. If they are not understood sufficiently, they may have devastating consequences on the grape-growing. The research was carried out in the model vineyards in Jelenec, Ladice and Topoľčianky during the period from April to September 2019 and 2021. Jelenec and Ladice had six monitoring sites, Topoľčianky had seven monitoring sites. Data were collected in approximately 30-day cycles. The aim of research was to monitor the incidence of insect pests in selected vineyards and identify their relation to environmental conditions. Pheromone traps were used throughout the research. The insect traps in combination with species-specific pheromone represent a reliable method for the pest monitoring. Based on aim studying the link between insect pests and climate conditions, traps were dispersed at the place of installation of the microclimatic dataloggers and the automatic stations. Data on the occurrence of the pests were subsequently evaluated in the context of the climate variability (temperature, wind speed, precipitation) and distance of the locality from the forest using Redundancy Analysis. It was confirmed that the insect pests are unequally distributed in the studied region and also inside the vineyards. Using Redundancy Analysis, we were able to explain the bonds in a maximum of 40% insect pests-environmental factors relationships. This research results show the need for regular monitoring of insect species, taking into account microclimatic as well as other ecological factors to optimize agrotechnical interventions. URL: https://www.gcass.science.upjs.sk/

Managed broadleaf deciduous forests are an important type of forest vegetation in Central Europe, also in the Western Carpathians. These forests are both economically and environmentally valuable. However, little is known about ecological species groups and the inter-specific associations of dominant species in temperate deciduous managed forests in Central Europe. Since the forest stands are in a managed landscape, they are not consistent with the traditionally recognized and used vegetation associations in the Western Carpathians. For these reasons our research contributes to understanding the consequences of broadleaf deciduous forest management. The aim of this research was the determination of ecological species groups and an investigation into the main environmental drivers, in order to explain the distribution of ecological species groups. The numerical TWINSPAN classification was selected to distribute 146 relevés to the five ecological species groups. Of these, 77 relevés were divided into two groups with Fagus sylvatica dominant, while 63 relevés were Quercus petraea dominant. Carpinus betulus, Tilia cordata and Fraxinus excelsior were dominant in 19 relevés. Constrained Analysis of Principal Components was used to explain the vegetation–environment relationship on three transects in the Male Karpaty Mountains. Altitude, pH, Ca, C, K and Mg were selected as the significant environmental drivers responsible for a large part of the species group variability (31.8%). The main requirement for sustainable forest management is knowledge of the vegetation–environment relationship and this research was focused on gaining such understanding. This knowledge can be used as a decision support tool for sustainable management in managed deciduous forests.

The construction and operation of waterworks has a significant impact on natural ecosystems. The evaluation of their negative impact and the proposal to minimize their impact, as well as the revitalization, especially of large rivers, have been given great importance in recent decades. The main goal of the study is to present impact of Gabčíkovo Waterwork on forest ecosystems after 30 years of damming. Specially evaluated are monitoring sites where changes are observed in the Slovak part of the so-called inland delta, i.e., between old and new riverbed of the Danube. The assessment of changes in terrestrial vegetation on selected monitoring sites was compared with the assessment of parallel measured soil moisture data. At the same time, data from the National Forestry Centre were also used to monitor changes in the state of forest ecosystems in the whole area of interest. When comparing the species composition from state to 2015 and from the period before GW was put into operation (in 1990) an increase was found in the area share of hardwood floodplain forest by 5.77% and the area shares of softwood floodplain forests decreased by 1.71%. Between 1990 and 2015, 68.43% of the territory remained unchanged at the level of forest type groups. A change in habitat conditions towards drier forest types was recorded on 23.61% of the territory.

Using UAV images for semiautomatic detection of row-gaps in vineyards in Jelenec and Topoľčianky (Slovakia) The use of UAV (Unmanned Aerial Vehicles) in precision viticulture leads to a more flexible and efficient approach to vineyard management. Images from UAV help determine the condition of the vineyard. Identification of the missing roots of the vineyard in a row by semi-automatic image classification and its comparison with manual classification is a goal of the paper. This study presents a new methodology for the segmentation of vine and row gaps. RGB (Red-Green-Blue) images, multispectral images, Near-Infrared (NIR) images, and Normalized Differential Vegetation Index (NDVI) images were tested and compared with manual classification. The percentage of row gap and the accuracy of individual images were determined. Object-oriented classification of the vine and row gaps in the buffer zone of the vineyard is a core of our method. Using geostatistical methods, such as zonal and logistic regression statistics, the accuracy of individual data in buffer zones was evaluated. Areas of interest were parts of vineyards in Jelenec and Topoľčianky. Success of the method detectomg outage (compared to manual classification) was achieved by images in the RGB spectrum: 96.45% for the Jelenec vineyard and 82.61% for the Topoľčianky vineyard. By this method, we quickly determine row gaps/vine which can be used to optimize or reduce the application of fertilizers to be used only on the vine. The method can be also used by inspection authorities to reveal the actual condition of the vineyard.