<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>According to Zlatnik (1976) there are 10 forest vegetation zones on the territory of the former Czechoslovakia. These are at present being modeled by phytocenological studies using bioindicator species of plants. Their incidence is affected by many abiotic factors, like temperature, precipitation or influence of climatic-inverse locations. By effective modelling of factors affecting the site requirements of bioindicator species, it is possible to make a comprehensive modelling of vegetation zonation. For the process of modelling, however, it is essential to identify the abiotic factors influencing this phenomenon and determine the extent of their influence. Hence, all the selected factors were analyzed using geoinformation tools and then combined with a typological map, which describes, among others, vegetation zonation in forest stands. The outcome of this combination was subjected to discrimination analysis, which identified influential factors and determined the extent of their influence. For modelling forest vegetation zones two methods were tested, first maximum likelihood clasification and second classification function of discriminant analysis in three territories with different reliefs. Both methods create a new raster of vegetation zonation based on geospatial relationship of individual factors and vegetation zones. Match of result models and input typological dates reaches 70 % - 90 %.</p></abstract>

According to Zlatnik (1976) there are 10 forest vegetation zones on the territory of the former Czechoslovakia. These are at present being modeled by phytocenological studies using bioindicator species of plants. Their incidence is affected by many abiotic factors, like temperature, precipitation or influence of climatic-inverse locations. By effective modelling of factors affecting the site requirements of bioindicator species, it is possible to make a comprehensive modelling of vegetation zonation. For the process of modelling, however, it is essential to identify the abiotic factors influencing this phenomenon and determine the extent of their influence. Hence, all the selected factors were analyzed using geoinformation tools and then combined with a typological map, which describes, among others, vegetation zonation in forest stands. The outcome of this combination was subjected to discrimination analysis, which identified influential factors and determined the extent of their influence. For modelling forest vegetation zones two methods were tested, first maximum likelihood clasification and second classification function of discriminant analysis in three territories with different reliefs. Both methods create a new raster of vegetation zonation based on geospatial relationship of individual factors and vegetation zones. Match of result models and input typological dates reaches 70 % - 90 %.

Possibilities of Forest Altitudinal Vegetation Zones Modelling by Geoinformatic Analysis

Department of Geoinformation Technologies, Mendel University in Brno, Czech Republic, Zemědělská 1, 613 00 Brno

Journal of Landscape Ecology

According to Zlatnik (1976) there are 10 forest vegetation zones on the territory of the former Czechoslovakia. These are at present being modeled by...

Possibilities of Forest Altitudinal Vegetation Zones Modelling by Geoinformatic Analysis

Published Online: Aug 08, 2012

Page range: 49 - 61

DOI: https://doi.org/10.2478/v10285-012-0038-8

Keywords
vegetation zonation, classification, climate, relief

This content is open access.

Possibilities of Forest Altitudinal Vegetation Zones Modelling by Geoinformatic Analysis

Published Online: Aug 08, 2012

Page range: 49 - 61

DOI: https://doi.org/10.2478/v10285-012-0038-8

Keywordsvegetation zonation, classification, climate, relief

This content is open access.

Keywords
vegetation zonation, classification, climate, relief