Spectrometric analyses in comparison to the physiological condition of heavy metal stressed floodplain vegetation in a standardised experiment
2010
Götze, Christian (Institute of Geosciences, Department of Remote Sensing and Cartography, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 4, D-06120 Halle (Saale), Germany) | Jung, András (Institute of Geosciences, Department of Remote Sensing and Cartography, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 4, D-06120 Halle (Saale), Germany) | Merbach, Ines (Division Biodiversity and Terrestrial Ecosystems, Helmholtz-Centre of Environment Research Leipzig-Halle, Hallesche Straße 44 D-06246 Bad Lauchstädt, Germany) | Wennrich, Rainer (Division of Analytics and Ecotoxicology, Helmholtz-Centre of Environment Research Leipzig-Halle, Permoserstr. 15 D- 04318 Leipzig, Germany) | Gläßer, Cornelia (Institute of Geosciences, Department of Remote Sensing and Cartography, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 4, D-06120 Halle (Saale), Germany)
Floodplain ecosystems are affected by flood dynamics, nutrient supply as well as anthropogenic activities. Heavy metal pollution poses a serious environmental challenge. Pollution transfer from the soil to vegetation is still present at the central location of Elbe River, Germany. The goal of this study was to assess and separate the current heavy metal contamination of the floodplain ecosystem, using spectrometric field and laboratory measurements. A standardized pot experiment with floodplain vegetation in differently contaminated soils provided the basis for the measurements. The dominant plant types of the floodplains are: Urtica dioica, Phalaris arundinacea and Alopecurus pratensis, these were also chemically analysed. Various vegetation indices and methods were used to estimate the red edge position, to normalise the spectral curve of the vegetation and to investigate the potential of different methods for separating plant stress in floodplain vegetation. The main task was to compare spectral bands during phenological phases to find a method to detect heavy metal stress in plants. A multi-level algorithm for the curve parameterisation was developed. Chemo-analytical and ecophysiological parameters of plants were considered in the results and correlated with spectral data. The results of this study show the influence of heavy metals on the spectral characteristics of the focal plants. The developed method (depth CR1730) showed significant relationship between the plants and the contamination.
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