Application of imaging spectroscopy in monitoring of vegetation stress caused by soil pollutants in the Sokolov lignite basin
| Autor: | Mišurec, Jan |
|---|---|
| Přispěvatelé: | Kupková, Lucie, Pavelka, Karel, Homolová, Lucie |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
water content
Norway spruce radiative transfer model modely přenosu záření obsah karotenoidů hyperspektrální obrazová data leaf area index obrazová spektroskopie zdravotní stav vegetace chlorophyll content vegetation health status obsah chlorofylu index listové plochy imaging spectroscopy LIBERTY FRT digital hemispherical photography carotenoids content PROSPECT-5 hyperspectral image data digitální hemisférické fotografie smrk ztepilý obsah vody |
| Popis: | Forests can be considered as one of the most important Earth's ecosystems not only because of oxygen production and carbon sequestration via photosynthesis, but also as a source of many natural resources (such as wood) and as a habitat of many specific plants and animals. Monitoring of forest health status is thus crucial activity for keeping all production and ecosystem functions of forests. The main aim of the thesis is development of an alternative approach for forest health status based on airborne hyperspectral data (HyMap) analysis supported by field sampling. The proposed approach tries to use similar vegetation parameters which are used in case of the current methods of forest health status assessment based on field inspections. It is believed that importance of such new methods will significantly increase in the time when the planned satellite hyperspectral missions (e.g. EnMap) will move into operational phase. The developed forest health monitoring approach is practically demonstrated on mature Norway spruce (Picea abies L. Karst) forests of the Sokolov lignite basin which were affected by long-term coal mining and heavy industry and therefore high variability of forest health status was assumed in this case. Two leaf level radiative transfer models were used for simulating spectral... |
| Databáze: | OpenAIRE |
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