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  • There are 10 forest altitudinal zones for forest ecosystem on the territory of the Czech republic are described by phytocoenological studies using bioindicator species of plants. This classification is influenced by many abiotic factors. Using factors describing the site requirements of bioindicator species, allow estimating forest altitudinal zones by comprehensive modeling. As the potentially relevant factors the average temperature, precipitation, solar radiation, topographic exposure, aspect, slope, curvature, stream distance, soil and geology were identified. Their spatial distribution was mapped using spatial analysis techniques and Python regression code. Resulting rasters were subjected to discriminant analyzes to identify the significant abiotic factors. Results helped to merge the factors in a comprehensive analytical model based on the maximum likelihood classification and classification function of discriminant analysis, were match of result models and input typological data reaches 70-90 %.
  • There are 10 forest altitudinal zones for forest ecosystem on the territory of the Czech republic are described by phytocoenological studies using bioindicator species of plants. This classification is influenced by many abiotic factors. Using factors describing the site requirements of bioindicator species, allow estimating forest altitudinal zones by comprehensive modeling. As the potentially relevant factors the average temperature, precipitation, solar radiation, topographic exposure, aspect, slope, curvature, stream distance, soil and geology were identified. Their spatial distribution was mapped using spatial analysis techniques and Python regression code. Resulting rasters were subjected to discriminant analyzes to identify the significant abiotic factors. Results helped to merge the factors in a comprehensive analytical model based on the maximum likelihood classification and classification function of discriminant analysis, were match of result models and input typological data reaches 70-90 %. (en)
Title
  • Using GIS and maximum likelihood classification to model forest altitudinal zones
  • Using GIS and maximum likelihood classification to model forest altitudinal zones (en)
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  • Using GIS and maximum likelihood classification to model forest altitudinal zones
  • Using GIS and maximum likelihood classification to model forest altitudinal zones (en)
skos:notation
  • RIV/62156489:43410/13:00200297!RIV14-MSM-43410___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 113122
http://linked.open...ai/riv/idVysledku
  • RIV/62156489:43410/13:00200297
http://linked.open...riv/jazykVysledku
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  • climate; classification; forest altitudinal zones (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B631D9EC340E]
http://linked.open...v/mistoKonaniAkce
  • Zvolen
http://linked.open...i/riv/mistoVydani
  • Zvolen
http://linked.open...i/riv/nazevZdroje
  • Implementation of DSS Tools into Forestry Practice
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Klimánek, Martin
  • Vahalík, Petr
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Technical univerzity in Zvolen
https://schema.org/isbn
  • 978-80-228-2510-8
http://localhost/t...ganizacniJednotka
  • 43410
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