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Impact of fluvial-morphological macrostructrus on the physical habitat of streams.
Strachota, Pavel ; Matoušková, Milada (advisor) ; Křížek, Marek (referee)
This thesis main goal is to nd the main parameters describing fluvial-morphological macrostructures due physical habitat of streams on example study of Zlatý potok stream and Mandát stream. To perform this study was used technique of neural network. Neural network method make possible to make both qualitative and quantitative survey of particular parameters and their weights. Fundamental data used for this thesis was got by mapping regions of interest with two ecohydromorphological methods EcoRivHab and RHS. Information about physical habitat of mapped streams was realized from map's basis (ZABAGED) and by mapping (e.g. valley relief by laser gradiometer, bed loads). Data processing was realized in two parts. In the first part the regions of interest were quali ed to both of the methods. Neural network was seeded by data from mapping of the Zlatý potok stream. In the second part results of mapping for all of the streams were compared by technique of neural network. This way it was possible to evaluate di erences among natural parts of streams in geographically di erent areas and also major and minor parameters both of the used methods for mappings.
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Impact of fluvial-morphological macrostructrus on the physical habitat of streams.
Strachota, Pavel ; Matoušková, Milada (advisor) ; Křížek, Marek (referee)
This thesis main goal is to nd the main parameters describing fluvial-morphological macrostructures due physical habitat of streams on example study of Zlatý potok stream and Mandát stream. To perform this study was used technique of neural network. Neural network method make possible to make both qualitative and quantitative survey of particular parameters and their weights. Fundamental data used for this thesis was got by mapping regions of interest with two ecohydromorphological methods EcoRivHab and RHS. Information about physical habitat of mapped streams was realized from map's basis (ZABAGED) and by mapping (e.g. valley relief by laser gradiometer, bed loads). Data processing was realized in two parts. In the first part the regions of interest were quali ed to both of the methods. Neural network was seeded by data from mapping of the Zlatý potok stream. In the second part results of mapping for all of the streams were compared by technique of neural network. This way it was possible to evaluate di erences among natural parts of streams in geographically di erent areas and also major and minor parameters both of the used methods for mappings.
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