The coronavirus became a phenomenon in 2020, which is making an unwanted but wide space for the study of various scientific disciplines. The COVID-19 pandemic situation which has reached almost the whole civilized world by its consequences thus offers a unique possibility to analyze the graphic space and the human activities inside it. The aim of this study is to predict and identify the potential rate of threat on the example of COVID-19 in Slovakia through an established model. This model consisted of an assessment of the partial phenomena of exposure, vulnerability, and overall risk. The statistical data used to evaluate these phenomena concerned individual cities in Slovakia. These represent the smallest administrative unit. Indirect methods based on the point method were applied in the paper. The spreading and transfer of the disease was influenced much more by the exposure presented by traffic availability, especially, but also the concentration of inhabitants in the selected locations (shops, cemeteries, and others). In the results, our modeling confirmed the regions with the highest intensity, especially in the districts (Bratislava, Košice, Prešov, and Nitra). The selection of the data and method used in this study together with the results reached and presented may serve as an appropriate tool for the support of decision-making of other measures for the future.

Tracking changes in the structure of landscape dynamics as a result of flood activity is a complex process. This study presents a model for determining changes to landscapes caused by flood events by evaluating a specific territory in Eastern Slovakia, which has been affected by repeated large-scale flood events in the past. The area has not been subject to a comprehensive monitoring of changes in the landscape structure. Based on the observation of several sets of data, a combination of statistical methods and GIS spatial analysis tools (visualizing tools for compare categories, mapping, and modelling techniques, spatial analysis models for land use change and flood modelling) were used to identify changes in the landscape structure in the period from 1998 to 2021. The results point to the significance of the year 2010, with the precipitation totals for this year showing a level significantly higher than the rolling average and confirming the occurrence of an extreme flood event. The dynamics of landscape structure changes were evaluated based on changes in the representation of selected types of land cover classes. The results of a spatial evaluation of the Corine Land Cover demonstrate that the most-significant area changes were recorded in 2012 in the pasture class, with a decrease of 31% or approximately 96.5 ha. The identified difference in the frequency of representation of individual values of the normalized differential vegetation index confirms the loss of landscape diversity and the emergence of a more homogeneous type of landscape. An assessment of the state of pastures in the study area shows that this class has completely disappeared from the site near the watercourse.