Spectrometric analyses in comparison to the physiological condition of heavy metal stressed floodplain vegetation in a standardised experiment
- 58 Downloads
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.
Keywordsvegetation indices plant stress heavy metals floodplain spectrometric measurements
Unable to display preview. Download preview PDF.
- Friese K., Witter B., Miehlich G., Rode M., Stoffhaushalt von Auenökosystemen — Böden und Hydrologie, Schadstoffe, Bewertungen, Springer-Verlag, Berlin, 2000Google Scholar
- Overesch M., Schwermetalle in Auenökosystemen. Bindungsformen in Böden und Gehalte in Pflanzen, diploma thesis, Münster, 2002Google Scholar
- Singhroy V., Kruse F., Detection of metal stress in Boreal Forest Species using the 0.67 μ chlorophyll absorption band, In: Rogers R.H. (ed.), Proceedings of the eight Thematic conference on geologic remote sensing, exploration, engineering and environment, Denver, 1991, 361–372Google Scholar
- Singhroy V., Stanton-Gray R., Springer J., Spectral geobotanical investigation of mineralized till sites. Proceedings of the Fifth Thematic Conference, Remote Sensing for Exploration Geology, Reno, 1986Google Scholar
- Curtiss B., Maecher A.G., Changes in Forest canopy reflectance associated with chronic exposure to high concentrations of soil trace metals. Proceedings of eighth Thematic Conference on Geologic Remote Sensing, Denver, 1991Google Scholar
- Schellekens J.H., Gilbes F., Rivera G.D., Ysa Y.C., Chardon S., Fong Y., Reflectance spectra of tropical vegetation as a response to metal enrichment in the substrate of West-central Puerto Rico, Caribb. J. Earth Sci., 2005, 39, 9–12Google Scholar
- Clevers J.P.G.W., Kooistra L., Assessment of heavy metal contamination river floodplains by using the red-edge index, Proceeding of the 3rd EARSeL Workshop on Imaging Spectroscopy, Hersching, 2003Google Scholar
- Kumar L., Schmidt K.S., Dury S., Skidmore, A.K., Imaging spectrometry and vegetation science. In: Van der Meer, F.D., De Jong, S.M. (eds.), Imaging spectrometry: Basic principles and prospective applications. Springer, 2001, 113–157Google Scholar
- Götze C., Gläßer C., Detection of vegetation stress characteristics in the lignite open pit mining landscape Goitsche using Hyperspectral remote sensing data. Proceedings 5th EARSeL Workshop on Imaging Spectroscopy, Bruges, 2007Google Scholar
- Kancheva R., Borisova D., Georgiev G., Informational potenfial of vegetation spectral reflectance anthropogenic impact studies, Annual of University of Mining and Geology, Sofia, 2003, 46, 355–359Google Scholar
- Erasmi S., Analyse spektroradiometrischer in situ Messungen als Datenquelle für die teilflächenspezifische Zustandsbeschreibung von Winter-weizenbeständen, PhD thesis, Göttingen, 2002Google Scholar