Norway spruce dominates mountain forests in Europe. Natural variations in the mountainous coniferous forests are strongly influenced by all the main components of forest and landscape dynamics: species diversity, the structure of forest stands, nutrient cycling, carbon storage, and other ecosystem services. This paper deals with an empirical windthrow risk model based on the integration of logistic regression into GIS to assess forest vulnerability to wind-disturbance in the mountain spruce forests of Šumava National Park (Czech Republic). It is an area where forest management has been the focus of international discussions by conservationists, forest managers, and stakeholders. The authors developed the empirical windthrow risk model, which involves designing an optimized data structure containing dependent and independent variables entering logistic regression. The results from the model, visualized in the form of map outputs, outline the probability of risk to forest stands from wind in the examined territory of the national park. Such an application of the empirical windthrow risk model could be used as a decision support tool for the mountain spruce forests in a study area. Future development of these models could be useful for other protected European mountain forests dominated by Norway spruce.

Pluvial flash floods are among the most dangerous weather-triggered disasters, usually affecting watersheds smaller than 100 km², with a short time to peak discharge (from a few minutes to a few hours) after causative rainfall. Several warning systems in the world try to use this time lag to predict the location, extent, intensity, and time of flash flooding. They are based on numerical hydrological models processing data collected by on-ground monitoring networks, weather radars, and precipitation nowcasting. However, there may be areas covered by weather radar data, in which the network of ground-based precipitation stations is not sufficiently developed or does not even exist (e.g., in an area covered by portable weather radar). We developed a method usable for designing an early warning system based on a different philosophy for such a situation. This method uses weather radar data as a 2D signal carrying information on the current precipitation distribution over the monitored area, and data on the watershed and drainage network in the area. The method transforms (concentrates) the 2D signal on precipitation distribution into a 1D signal carrying information on potential runoff distribution along the drainage network. For sections of watercourses where a significant increase in potential runoff can be expected (i.e., a significant increase of the 1D signal strength is detected), a warning against imminent flash floods can be possibly issued. The whole curve of the potential runoff development is not essential for issuing the alarm, but only the significant leading edge of the 1D signal is important. The advantage of this procedure is that results are obtained quickly and independent of any on-ground monitoring system; the disadvantage is that it does not provide the exact time of the onset of a flash flooding or its extent and intensity. The generated alert only warns that there is a higher flash flooding hazard in a specific section of the watercourse in the coming hours. The forecast is presented as a dynamic map of the flash flooding hazard distribution along the segments of watercourses. Relaying this hazard to segments of watercourses permits a substantial reduction in false alarms issued to not-endangered municipalities, which lie in safe areas far away from the watercourses. The method was tested at the local level (pluvial flash floods in two small regions of the Czech Republic) and the national level for rainfall episodes covering large areas in the Czech Republic. The conclusion was that the method is applicable at both levels. The results were compared mainly with data related to the Fire and Rescue Service interventions during floods. Finally, the increase in the reliability of hazard prediction using the information on soil saturation is demonstrated. The method is applicable in any region covered by a weather radar (e.g., a portable one), even if there are undeveloped networks of rain and hydrometric gauge stations. Further improvement could be achieved by processing more extended time series and using computational intelligence methods for classifying the degree of flash flooding hazard on individual sections of the watercourse network.

The article presents the results of research focused on the speed and success rate of reading aerial images and topographic maps showing the same territory in the Czech Republic. Attention was focused on searching for objects of importance in terms of disaster management (railway and road bridges, road, watercourse, railway station, airport). The success rate was electronically evaluated by the Hypothesis software as a whole for the image, and the map was created for all respondents and for selected groups of respondents. The results showed that, with the exception of watercourse identification, other strategic objects are found faster and more reliably on color aerial images. No differences in speed and success of interpretation were found between men and women, laymen and experts. Soldiers and crisis management personnel were faster than laymen, but they were equally successful. Color aerial images or color aerial orthophotomaps have thus proved to be a key source of data for effective decision-making on a territory where a crisis event is taking place and where the deployment of a crisis unit is a need.

Two model municipality areas on the Czech-Bavarian (German) border were examined. The objective of research was to determine the changes which land use in different types of the natural environment on both sides of the border has undergone over the last 200 years with respect to the social driving forces. The task was based on historical studies of archived materials statistical a cartographic materials, recent fieldworks and finally carried out in the GIS environment, which encompassed maps of natural landscape units of both areas and land use maps of 1829–1840, 1935–1938 and in 2002–2007. Results show a high degree of similarity in the dominance of the main forms now as output of previous development: in forests, meadows and arable land, as well as in corresponding types of units on both sides of the border. Through clustering, the development trends of all the units have been detected. These trends tend to lead toward a similar form of present land use.

This paper presents the results of the analysis of more than 150 different printed newspaper weather forecasting maps, representing 91 global, national, regional and local daily news periodicals from 33 countries in 4 continents. The classification attention focused both on the character of the localizing background layer of the analysed maps as well as on the meteorological thematic layer. The results identify 12 types of background localizing maps and 47 used types of presentation of meteorological forecast information, only 19 of which were used repeatedly in more than one newspaper. All the findings were documented on comparable cartographic models. Conclusions suitable for practical applications are demonstrated in the discussion.