Zbyněk Janoška

Bio: Zbyněk Janoška is an academic researcher. The author has contributed to research in topics: Correlation dimension & Multifractal system. The author has an hindex of 3, co-authored 3 publications receiving 24 citations.

Forest vulnerability zones in the Czech Republic

Abstract: The accompanying Main Map shows forest vulnerability zones calculated for the Czech Republic, covering a total area of almost 79,000 km2. Calculating forest vulnerability zones over such a large area requires a unique approach due to its complexity. The map includes additional information on forest areas and topography. The model of forest vulnerability zones (FVZ) constitutes an alternative to existing zones of forest health hazard caused by emissions. It was created based on subjective classification of existing incidence of damage in forests. Moreover, the model of forest vulnerability zones estimates the risk of forest health degradation caused by abiotic factors.

Fractal dimension as a descriptor of urban growth dynamics

Abstract: The objective of this paper is to examine the development of the urban form of the city of Olomouc since the 1920s in terms of fractal dimension, and to link the observation with two other descriptors of shape - area and perimeter. The fractal dimension of built-up areas and fractal dimension of the boundary of the city are calculated employing the box-counting method; the possibilities of their interpretation and usage in urban planning are discussed. The process of urban growth is observed with respect to its fractality and perspectives of this approach are discussed. An interesting dependence between area and its fractal dimension is derived.

From Mental Maps to GeoParticipation

Abstract: Ever since behavioural geographers started working with place perception; and Peter Gould and Kevin Lynch used mental maps to explore city visualization and spatial preferences, participation has become an integral part of geographical research. Later, when Robert Chambers and others introduced maps into Participatory Rural Appraisal, Participatory GIS and Public Participation GIS were also recognized by quantitative geographers as research methods and visualization tools. In the era of smartphones and global Internet coverage, applications such as FixMyStreet, ArcGIS Online, CartoDB and Maptioannaire allow users to cross the technology gap and become neocartographers without the need for GIS knowledge. GeoParticipation based on using spatial tools in order to involve citizens in community participation can be the future development of Public Participation GIS as it provides an easy-to-use environment and social engagement while creating the feeling of belonging to a certain social group or community. The...

Using a fuzzy inference system to delimit rural and urban municipalities in the Czech republic in 2010

Abstract: 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 ma...

Modelling of Climate Conditions in Forest Vegetation Zones as a Support Tool for Forest Management Strategy in European Beech Dominated Forests

Abstract: The regional effects of climate change on forest ecosystems in the temperate climate zone of Europe can be modelled as shifts of forest vegetation zones in the landscape, northward and to higher elevations. This study applies a biogeographical model of climate conditions in the forest vegetation zones of the Central European landscape, in order to predict the impact of future climate change on the most widespread tree species in European deciduous forests—the European beech (Fagus sylvatica L.). The biogeographical model is supported by a suite of software applications in the GIS environment. The model outputs are defined as a set of conditions - climate scenario A1B by the Special Report on Emission Scenarios (SRES) for a forecast period, for a specified geographical area and with ecological conditions appropriate for the European beech, which provide regional scenarios for predicted future climatic conditions in the context of the European beech’s environmental requirements. These predicted changes can be graphically visualized. The results of the model scenarios for regional climate change show that in the Czech Republic from 2070 onwards, optimal growing conditions for the European beech will only exist in some parts of those areas where it currently occurs naturally. Based on these results, it is highly recommended that the national strategy for sustainable forest management in the Czech Republic be partly re-evaluated. Thus, the presented biogeographical model of climate conditions in forest vegetation zones can be applied, not only to generate regional scenarios of climate change in the landscape, but also as a support tool for the development of a sustainable forest management strategy.

Design of Experiment

Abstract: A well-designed and constructed experiment will be robust under questioning, and will focus criticism on conclusions [1], rather than potential experimental errors [2]. A sound experimental design should follow the established scientific protocols and generate good statistical data [3]. As an example, experiments on an industrial scale can cost millions of dollars. Repeating the experiment because it had poor control groups [4], or insufficient samples for a statistical analysis, is not an option. For this reason, the design phase is possibly the most crucial.