Possibilities of soil spectroscopy for the classification of contaminated areas in river floodplains
Autor: | Ron Wehrens, Lammert Kooistra, Lutgarde M. C. Buydens, Piet H. Nienhuis, Rob S. E. W. Leuven |
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Rok vydání: | 2001 |
Předmět: |
chemistry.chemical_classification
Hydrology Global and Planetary Change geography geography.geographical_feature_category Floodplain Soil test Soil science Management Monitoring Policy and Law Soil contamination VNIR chemistry Tributary Environmental science Organic matter Spatial variability Computers in Earth Sciences Subsoil Earth-Surface Processes |
Zdroj: | International Journal of Applied Earth Observation and Geoinformation. 3:337-344 |
ISSN: | 1569-8432 |
DOI: | 10.1016/s0303-2434(01)85041-8 |
Popis: | During the past decades, large amounts of diffuse contaminated soil material have been deposited in the floodplains of the river Rhine in the Netherlands. The dynamic character of this river causes a large spatial variability in the contamination level of its floodplain soils. Characterisation of the spatial variability exclusively based on soil sampling and analysis is often insufficient and expensive. Hyperspectral images can provide additional spatial information for a proper characterisation of the contamination situation of river floodplains. This paper describes the possible application of soil spectroscopy to estimate metal concentration levels in river floodplains. Soil reflectance spectra in the visible-near infrared region (VNIR) were measured in the laboratory for soil samples taken from two river floodplains along the river Waal, the main tributary of the river Rhine in the Netherlands. A multivariate calibration procedure using partial least squares (PLS) regression was applied to establish a relationship between reflectance spectra in the visible-near infrared (VNIR) region and spectrally active soil characteristics (organic matter and clay content) that are intercorrelated with concentration levels of Cd and Zn. Results of the analysis of two river floodplains are summarised and the influence of scale-level and sub soil material on the prediction capability is discussed. |
Databáze: | OpenAIRE |
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