Applicability of hyperspectral technology for in situ phytoremediation71-78Views:87
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.
Usage of Different Spectral Bands in Agricultural Environmental Protection123-126Views:78
Hyper and multispectral imaging systems are widely used in agricultural and environmental protection. Remote sensing techniques are suitable for evaluating environmental protection hazarsd, as well as for agriculture resource exploration. In our research we compared aerial hyper and multispectral images, as well as multispectral digital camera images with the background data from the test site. Hyperspectral records were obtained using a new 80-channeled aerial spectrometer (Digital Airborne Imaging Spectrometer /DAIS 7915/. We have chosen two farms where intensive crop cultivation takes place, as test sites, so soil degradation and spreading of weeds can be intensive as a result of land use and irrigation. We took additional images of air and ground with a TETRACAM ADC wide band multispectral camera, which can sense blue, green and near infrared bands. We had detailed GIS database about the test site. Weed and vegetation map of the area in the spring and the summer was made in 2002. For soil salt content analysis, we gathered detailed data frome an 80x100 m area. When analyzing the images, we evaluated image reliability, and the connection between the bands and the soil type, pH and salt content, and weed mapping. In the case of hyperspectral images, our aim was to choose and analyze the appropriate band combinations. With a TETRACAM ADC camera, we made images at different times, and we calculated canopy, NDVI and SAVI indexes. Using the background data mentioned above, the aim of our study was to develop a spectral library, which can be used to analyze the environmental effects of agricultural land use.
Spectral analysis of stress symptoms caused by apple powdery mildew (Podosphaera leucotricha83-88Views:154
An orchard can be examined on the basis of spectral data, using methods with which the reflected radiation can be divided into a large number of (several hundreds) small spectral channel (some nm). Calculated on the basis of such hyperspectral data from different index numbers the water supply of foliage conditions can be well characterized.
The research site is an intensive apple orchard, which located in University of Debrecen, Agricultural Sciences Centre, Farm and Regional Research Institute at Pallag. During my experiments the preliminary evaluation of spectral, non-invasive measurement method are carried out for detecting stress symptoms caused by Podosphaera leucotricha.
Based on the results narrow band greenness indices (NDVI705, mNDVI705, mSR705 and REP) can be used for determination of diseased canopy and for the detection of stress symptoms of Podosphaera leucotricha,. These statements can be utilized in precision plant protection systems, since it can be a basis for such integrated active sensors with LED or laser light source, measuring reflectance at the certain spectral range, which can facilitate real time status assessment of orchards and can control precision fungicide utilization.