Characterization of heavy metal polluted abandoned mining sites is complicated, as the spatial distribution of pollutants often changes dramatically.
In our study, a hyperspectral data analysis of the Gyöngyösoroszi abandoned Pb-Zn mine, located in northern Hungary, where Záray (1991) reported serious heavy metal contamination, was carrie
Spectral angle mapper (SAM) and BandMax classification techniques were applied to obtain rule mineral images. Each pixel in these rule images represents the similarity between the corresponding pixels in the hyperspectral image to a reference spectrum.
As a result of hyperspectral imagery the distribution of pyritic minerals (sphalerite, galena) in the area was defined. Both of the mineral formations occur, especially in mine tailings, the area of the ore preparatory, and the Szárazvölgyi flotation sludge reservoir. According to the results, jarosite and goethite have similar distributions to sphalerite and galena. The results showed that hyperspectral remote sensing is an effective tool for the
characterization of Pb, Zn and Fe containing minerals at the examined polluted sites and for modelling the distribution of heavy metals and minerals in extensive areas.
This classification method is a basis of further detailed investigations, based on field measurements, to map the heavy metal distribution of the studied area and to quantify the environmental risks caused by erosion, which include DEM (digital elevation model) and climatic and hydrological data sources. Furthermore, it can be used primarily to support the potentially applicable phytostabilization technique and to isolate hot spots where only ex-situ remediation techniques can be applied.
The characterization of heavy metal polluted abandoned mining sites is a complicated assignment due to the variable spatial distribution of the pollutants, therefore complex integrated method is required in order to assess precisely the amount and the distribution of the contaminants. The examined area is flotation sludge reservoir of abandoned... Pb-Zn mining site with serious heavy metal contamination. located in Gyöngyösoroszi, Northern Hungary.
The hyperspectral image of the flotation sludge is obtained by using a Digital Airborne Imaging Spectrometer DAIS 7915, in the frame of DLR HySens first Hungarian hyperspectral flight campaign (21/08/2002). Parallel to the flight campaign heavy metal content of soil samples were examined from the area of the flotation sludge. The analysis of hyperspectral data was verified by the examination of mine tailing samples by FPXRF (Field Portable X-ray Fluorescence spectrometry) (NITON XL-703).
Determinations of heavy metal containing minerals are based on the spectral profiles of the pixels of the area with using USGIS standard spectral profiles of the examined materials (galena, pyrite, sphalerite, goethite and jarosit).
Applying the Spectral Angle Mapper with BandMax classification the distribution of minerals (galena, pyrite, sphalerite, goethite, jarosit) in the area was defined. The mineral formation occurs especially at the levees and the barren places of the Szárazvölgyi flotation sludge reservoir. Based on the statistic results of the samples, principal component analysis and correlation coefficient between the different metal content of the samples were calculated. The highest correlations were found between Pb-Zn, Fe-Zn and between Fe-Pb. This prove the results of the principal component analysis, where usually Pb, Zn, Fe introduce the main component.
Canopy analysis was also carried out with the hyperspectal image in order to classify the differences between vegetation types at the Szárazvölgy flotation sludge reservoir and analyse the applicability of it. Supervised classification methods were used to distinguish 8 vegetation types based on the spectral properties of the area. The results of the classifications were compared to a ground truth image, based on ortophoto, topographic map, and GPS based field data collection. According to results of the comparison, the paralellpiped classification method is proved to be appropriate method based on the overall accuracy of canopy classification, which was 54% due to heterogeneity of the vegetation.
The results of hyperspectral data and FPXRF analysis suggest that Pb, Zn and Fe containing minerals have similar spatial distribution in the examined and barren area.
Based on this study hyperspectral remote sensing is likely to be an effective tool for the characterization and modeling the distribution of Pb, Zn and Fe containing minerals at the examined heavy metal polluted sites. Further more, based on the vegetation analysis plant species for phytoremediation can be defined.
Some physiological effects of bacteria containing fertilizer and some wood ash were examined in the experiments. The minimization of the use of chemicals in agriculture has been an ongoing challenge. One option lies in the intenzification of soil life. The release of organic matters by the roots and bacteria play a significant role in the uptak...e of minerals. The main problem to usilize wood ash in agriculture is its heavy metal contents. The
solubility of heavy metals is very low, therefore there is no risk to use the wood ash in the agriculture and in the horticulture according to our experiments. The wood ash and biofertilizer contains several micronutrients in an optimum composition for forestry and agricultural plants.
Some physiological effects of bacteria containing fertilizer and some wood ash were examined in the experiments. The minimization of the use of chemicals in agriculture has been an ongoing challenge. One option lies in the intenzification of soil life. The release of organic matters by the roots and bacteria play a significant role in the uptak...e of minerals. The main problem to usilize wood ash in agriculture is its heavy metal contents. The solubility of heavy metals is very low, therefore there is no risk to use the wood ash in the agriculture and in the horticulture according to our experiments. The wood ash and biofertilizer contains several micronutrients in an optimum composition for forestry and agricultural plants.