Due to the suburbanisation process, it is becoming more difficult to properly define rural and urban areas in the Czech Republic. This delimitation problem has been intensively studied in Europe, including the Czech Republic, for decades, but only so-called ‘crisp’ rules have been set for the categorisation of urban and rural. This is no longer satisfactory because of substantial population movements. Our research focuses on applying fuzzy set theory to the delimitation of rural and urban areas and on the subsequent advanced cartographic visualisation. We used the principles of fuzzy regulation, or fuzzy inference systems, on socio-economic data to show the transitional character of municipalities. The generated Main map is at scale of 1:500,000, whereas secondary maps are at scale of 1:2,500,000. Map visualisation of municipalities in the Czech Republic provides a very unique combination of geographical information science, cartography and modern geo-computational methods. Information perception via a map is an adequate way to analyse geographic information, and the problem of delimiting rural and urban areas can be suitably visualised using these methods.

This paper describes a study of the evaluation of cartographic quality of urban plans in the Czech Republic using eye-tracking. Although map visualization is a crucial part of the urban planning process, only a few studies have focused on the evaluation of these maps. The plans of four Czech cities with different styles of visualization and legends were used in this eye-tracking experiment. Respondents were required to solve spatial tasks consisting of finding and marking a certain symbol on a map. Statistical analyses of various eye-tracking metrics were used, and the differences between experts and students and between the map and legend sections of the stimuli were explored. The study results showed that the quality of map symbols and the map legend significantly influence the legibility and understandability of urban plans. For correct decision-making, it is essential to produce maps according to certain standards, to make them as clear as possible, and to perform usability testing on them.

The differences in welfare amongst European countries are especially evident in border regions, and this affects cross-border cooperation and relationships. Due to the historical development of Central and Eastern European countries over the last century, the affected countries are unique “laboratories” for geographical research. This study assesses disparities in socio-economic indicators representing socio-economic phenomena in the Czech-Polish border region, through the analysis of cross-border (spatial) continuity, using quantitative methods (multivariate statistics and socio-economic profiling), GIS analysis and cartographic visualisation. It is demonstrated how such a combination of methods is useful for the comparison and evaluation of the complex socio-economic situations in neighbouring countries. This research project identifies the most suitable common indicators for a proper evaluation of cross-border (spatial) continuity, and it reveals the spatial patterns as reflected by a cluster analysis. The greatest cross-border (spatial) continuity is apparent in the easternmost part of the borderlands, while significant differences on both sides of the border are evident in the very central part of the areas under study. The paper also describes methodological aspects of the research in order to provide a quantitative approach to borderland studies.

This paper presents the results of a quantitative study in the Czech Republic to understand travellers’ attitudes towards and motivation to use different means of transport. Two Czech cities, Olomouc and Ostrava, are compared from the point of view of factors influencing spatial and temporal patterns and citizen’s selection of transport mode and transport behaviour (range and daily movements of the population, perception of the quality of public transport etc.). The data for the analysis were obtained from the survey with more than 500 respondents in each city. Spatial and temporal behaviour represented by the pattern of the movement in Olomouc and Ostrava city was identified by statistical and visual analytics methods. Based on a case study of two cities of a different size, we conclude that the size and shape of the city centre (spatial structure) influence not only the distances travelled but also the average speed of public transportation (slower for a smaller city). Distances and choice of transport mode also vary with the density of urban areas but can also be influenced by the spatial structure of the city. The walking distance to a public transport stop does not influence the most frequently used mode of transport. Temporal patterns in both cities are very similar and are not dependent on city size or city spatial structure. The spatial patterns of the car and public transport flows are similar in both cities. Different patterns can be observed for walking and shopping routes.

The present paper focuses on the epipelic cyanobacteria and algae (particularly desmids). Altogether 45 sediment samples were taken at ponds covering a pH/conductivity and trophic gradients. Statistic evaluation based on environmental variable...

Due to the current situation, and preventive measures taken to tackle COVID-19, it is crucial to keep society well-informed. Besides media and official news, that often include tabular data, it has also become a new standard for information sources to incorporate a map application or geovisualization. This paper offers a comprehensive and systematic overview describing the most prominent and useful map applications and map visualizations. News outlets should place the same importance on data analysis and interpretation as they place on data visualization. This paper emphasizes the role of geospatial data and analysis during the COVID-19 pandemic and aims to provide insights into the topic in order to better understand the consequences caused by the disease. Specifically, the paper deals with the COVID-19 Community Mobility Reports dataset, offering unique information about changes in human activity due to the pandemic. We show how this dataset can be utilized in terms of geovisual analytics and clustering in order to reveal the spatial pattern of such changes in human behavior.