Mr. Stefan Sommer Profile

Stefan Sommer

at European Commission

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Proceedings Article | 22 October 2004 Paper

Use of airborne hyperspectral data to estimate residual heavy metal contamination and acidification potential in the Guadiamar floodplain Andalusia, Spain after the Aznacollar mining accident

Thomas Kemper, Stefan Sommer

Proceedings Volume 5574, (2004) https://doi.org/10.1117/12.565626

KEYWORDS: Contamination, Pyrite, Metals, Reflectivity, Arsenic, Soil contamination, Lead, Shape memory alloys, Mining, Oxidation

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Field and airborne hyperspectral data was used to map residual contamination after a mining accident, by applying spectral mixture modelling. Test case was the Aznalcollar Mine (Southern Spain) accident, where heavy metal bearing sludge from a tailings pond was distributed over large areas of the Guadiamar flood plain. Although the sludge and the contaminated topsoils have been removed mechanically in the whole affected area, still high abundance of pyritic material remained on the ground. During dedicated field campaigns in two subsequent years soil samples were collected for geochemical and spectral laboratory analysis and spectral field measurements were carried out in parallel to data acquisition with the HyMap sensor. A Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) tool was used providing possibilities of multiple endmember unmixing, aiming to estimate the quantities and distribution of the remaining tailings material. A spectrally based zonal partition of the area was introduced to allow the application of different submodels to the selected areas. Based on an iterative feedback process, the unmixing performance could be improved in each stage until an optimum level was reached. The sludge abundances obtained by unmixing the hyperspectral spectral data were confirmed by the field observations and chemical measurements of samples taken in the area. The semi-quantitative sludge abundances of residual pyritic material could be transformed into quantitative information for an assessment of acidification risk and distribution of residual heavy metal contamination based on an artificial mixture experiment. The unmixing of the second year images allowed identification of secondary minerals of pyrite as indicators of pyrite oxidation and associated acidification.

Proceedings Article | 22 October 2004 Paper

Options for compiling an inventory of mining waste sites throughout Europe by combining Landsat-TM derived information with national and pan-European thematic data sets

Anca-Marina Vijdea, Stefan Sommer

Proceedings Volume 5574, (2004) https://doi.org/10.1117/12.565620

KEYWORDS: Mining, Minerals, Earth observing sensors, Remote sensing, Databases, Metals, Iron, Pollution control, Geographic information systems, Landsat

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Presently no reliable synoptic picture of number, extent, distribution and emissions from mining waste sites exists, neither for EU member states, nor for the Accession and Candidate Countries. At EU level, this information is needed to assess the large range of environmental impacts caused by mining wastes and their emissions in a coherent way across the different policies addressing the protection and sustainable use of environmental resources. The core task lies in the harmonised collection and standardised compilation and evaluation of existing data and in connecting them to a geographical reference system compatible with other European data sets. In the proposed approach information from national registers of mining wastes is linked to related standardized spatial data layers such as CORINE Land Cover (the classes of mineral extraction sites, dump sites) or other data sets available in the EUROSTAT GISCO data base, thus adding the spatial dimension at regional scale. Higher level of spatial detail and distinction between mineral extraction site and waste sites with or without accumulation of potentially hazardous material is added by remote sensing, applying a semi-automated principal component analysis (PCA) to selected spectral channels of geo-referenced Landsat-TM full scenes. The method was demonstrated on large areas covering approximately 120000 km2 of Slovakia and Romania and was validated against mining-related features from Pan-European and/or national databases, detailed geological maps, mineral resource maps, as well as by a GIS analysis showing the distribution of anomalous pixels in the above-mentioned features compared to the main land cover classes.

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